⚽ Upside Soccer Study (1): The Evolution of Match-Play in Major League Soccer (2018–2023)

Published in the International Journal of Sports Science & Coaching (2026) by Callum J. McCaskie and Christopher Wing.

Study: The Evolution of Match-Play in Major League Soccer from 2018 to 2023

Authors: Callum J. McCaskie and Christopher Wing

Institution: Edith Cowan University, Nutrition and Health Innovation Research Institute, Australia.

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🧩 Introduction

How has Major League Soccer evolved over the past six seasons, and what separates successful MLS teams from those that fail to qualify for the playoffs?

This study examined 2,519 MLS regular-season matches from 2018 to 2023, analyzing 21 technical and tactical performance indicators to understand changes in playing style, attacking effectiveness, passing behavior, and team success.

Despite the league’s rapid expansion and growing investment in coaching, analytics, and player development, the researchers found that MLS match-play remained relatively stable in its overall structure.

However, several important attacking indicators declined significantly, including goals, expected goals (xG), total shots, and shots on target.

One of the most important findings was that successful MLS teams consistently demonstrated superior attacking output and better ability to move the ball into dangerous areas, rather than simply accumulating more passes.

🧪 Study Overview

Design: Retrospective observational analysis of MLS match performance.

Seasons analyzed: 2018–2023 (six seasons).

Data source: FBref, using Opta match-performance data.

Matches by season:

The 2020 season was disrupted by COVID-19, resulting in fewer matches.

The researchers evaluated performance indicators including goals, xG, shots, passing volume and accuracy, progressive passing, carries into attacking areas, crosses, and tackles.

Teams were also grouped by their final playoff achievement: did not qualify, first round, quarterfinals, semifinals/conference finals, and finalists.

Statistical methods included principal component analysis (PCA), mixed-effects modeling, and sensitivity analyses.

📊 Key Findings

⚽ 1. MLS Match-Play Remained Structurally Stable

Despite the growth of the league, the researchers did not identify a major structural transformation in match-play characteristics between 2018 and 2023.

The first two principal components explained 62.1% of the variance in performance indicators:

• 44.1% was associated primarily with attacking and possession characteristics.

• 18.0% was associated with goal scoring and penalty-area actions.

There was substantial overlap between seasons, suggesting that the underlying technical and tactical structure of MLS remained relatively stable.

This does not mean individual teams did not change their playing styles. Rather, the league-wide statistical patterns did not show a distinct structural shift.

📉 2. Attacking Output Declined Significantly

One of the most striking findings was the decline in several attacking performance indicators.

All four indicators showed statistically significant negative trends across the study period.

The researchers suggested that improved collective defending, greater tactical organization, and more sophisticated opposition analysis could be contributing factors.

However, defensive organization was not measured in sufficient detail to establish this explanation.

Implication: MLS teams may need to dedicate more attention to creating high-quality scoring opportunities against increasingly organized defensive structures.

🎯 3. Successful MLS Teams Generated More Goals, Shots and xG

The study identified clear differences between teams that qualified for the playoffs and those that did not.

All playoff groups scored significantly more goals and registered more shots on target than non-qualifying teams.

Teams reaching the later playoff rounds also generally demonstrated stronger expected-goals performance.

Notable comparisons included:

• Goals: Finalists versus non-qualifiers showed a large effect size (Cohen’s d = 2.00 in magnitude).

• Shots on target: Semifinalists versus non-qualifiers showed a large effect (d = 1.38 in magnitude).

• xG: Finalists versus non-qualifiers showed a large effect (d = 1.50 in magnitude).

These results reinforce the importance of both the quantity and quality of attacking opportunities.

The findings are associations with season success, not proof that increasing one statistic independently will produce a higher league finish.

🥅 4. Passing Into Dangerous Areas Was More Important Than General Passing Volume

Another important finding concerned passing performance.

The researchers found that successful teams were differentiated more clearly by where they moved the ball than by overall passing volume.

Quarterfinalists and semifinalists generally demonstrated higher levels of:

• Passes into the final third.

• Passes into the penalty area.

• Progressive passing distance.

• Short passes attempted and completed.

Meanwhile, total passing volume and medium- and long-pass counts did not consistently differentiate finishing positions.

This suggests that counting passes alone provides limited insight into attacking effectiveness.

For performance analysts, the location, progression, and attacking purpose of passes may be more informative than simple passing totals.

📉 5. Long Passing and Progressive Ball Movement Declined

Several ball-movement indicators also declined significantly across the six seasons.

The reduction in long passing may indicate a movement away from some direct playing styles.

However, the researchers did not find the broad increase in possession-based passing observed in certain European leagues.

This raises an interesting possibility: MLS may be developing along a different tactical trajectory rather than simply following European soccer trends.

🛡️ 6. Better Defensive Organization Could Be Contributing to Lower Scoring

The researchers proposed that improvements in collective defending could help explain the reduction in attacking output.

Possible contributing factors include more organized defensive structures, improved opponent analysis, and greater tactical preparation.

However, the study measured only one defensive indicator directly: total tackles.

Consequently, it cannot establish whether pressing effectiveness, defensive compactness, or other defensive improvements caused the decline in attacking metrics.

This is an important area for future research.

🧠 Implications for MLS Teams and Practitioners

The study has several implications for coaching, player development, performance analysis, and sports science departments.

For coaching staff, the findings highlight the importance of training attacking patterns that create high-quality scoring opportunities. This could include combination play, movement into the penalty area, and decision-making against compact defensive structures.

For performance analysts, the research supports using contextual attacking indicators rather than relying on passing volume or possession statistics alone.

For academy directors, the findings suggest exposing young players to realistic attacking scenarios, including breaking down organized defenses and progressing the ball into dangerous areas.

For sports performance departments, the findings provide a tactical context for designing training sessions. However, the study did not measure GPS loads, sprint demands, accelerations, or other physical performance variables, so it cannot establish how MLS physical demands changed.

📌 Recommendations

For MLS Coaches and Technical Staff

• Prioritize training scenarios that improve chance creation and finishing.

• Develop attacking solutions against organized defensive blocks.

• Train players to progress the ball effectively into the final third and penalty area.

• Incorporate realistic match scenarios that challenge attacking decision-making.

• Evaluate attacking effectiveness through xG, shots on target, and contextual passing metrics.

For Sports Performance and Strength & Conditioning Staff

• Collaborate with technical coaches to design physically realistic attacking drills.

• Integrate accelerations, decelerations, changes of direction, and repeated movements into attacking scenarios where appropriate.

• Use GPS and movement tracking to measure the physical demands of these exercises.

• Evaluate whether training exposure reflects the demands of the team’s tactical approach.

These are practical extensions of the research, not physical-training interventions directly tested in the study.

For Performance Analysts

• Monitor xG, goals, shots on target, and passes into dangerous areas.

• Evaluate progressive passing and ball carries within tactical context.

• Compare attacking metrics across opponents and match situations.

• Avoid relying exclusively on total passes or possession percentages.

• Investigate how attacking efficiency changes against different defensive systems.

For Academy and Player Development Staff

• Prepare young players for congested defensive environments.

• Develop decision-making in the final third.

• Emphasize progressive passing, combination play, and movement into space.

• Train players to recognize and exploit scoring opportunities.

• Align development objectives with the technical and tactical demands observed at the professional level.

⚠️ Limitations

The authors identified several important limitations:

1. Limited defensive data: Total tackles was the only defensive indicator analyzed. Pressing, defensive compactness, and other tactical behaviors were not captured.

2. Six-season observation period: The study covered 2018–2023, limiting conclusions about longer-term league evolution.

3. COVID-19 disruption: The 2020 season included fewer matches and unusual competitive conditions. Sensitivity analyses excluding that season generally supported the principal findings.

4. Aggregated season-level data: The researchers used team averages rather than detailed match-by-match tactical analysis.

5. Missing contextual factors: Weather, home versus away conditions, match timing, and other situational variables were not included.

6. Small finishing-position groups: Finalists and other advanced playoff groups had relatively small samples, limiting the precision of some comparisons.

7. No physical performance measurements: The study did not evaluate running distances, sprinting, high-speed running, or acceleration demands.

Future research should incorporate physical tracking data, detailed defensive indicators, and comparisons with other professional soccer leagues.

✅ Conclusion

This study provides important insights into how MLS match-play evolved between 2018 and 2023.

Despite substantial league growth, the underlying technical and tactical structure of MLS remained relatively stable.

At the same time, goals, expected goals, total shots, and shots on target declined significantly.

The strongest differences between successful and unsuccessful teams were found in attacking output, shot creation, and the ability to progress the ball into dangerous areas.

For MLS coaches and practitioners, the findings reinforce the value of designing training programs that improve attacking effectiveness, rather than focusing exclusively on possession or passing volume.

For performance analysts, the study highlights the importance of contextualizing technical and tactical data to identify the indicators most relevant to competitive success.

The central takeaway is simple:

In MLS, success is not just about how much a team passes or possesses the ball. It is about how effectively that team creates and converts dangerous attacking opportunities.

⚽ Upside EPL Study (2): Are Optical Tracking Technologies Overestimating Sprint Running Demands in the Premier League?

Published in Science and Medicine in Football (2023), Volume 7, Issue 4, pp. 374–383.

Study: Interchangeability of Optical Tracking Technologies: Potential Overestimation of the Sprint Running Load Demands in the English Premier League

Authors: Matt Taberner, Tom Allen, Jason O’Keefe, Chris Richter, Daniel Cohen, Damian Harper and Martin Buchheit.

Organizations represented: Liverpool John Moores University, Arsenal FC, University of Central Lancashire, Everton FC, Kaia Health, University of Santander, Colombian Ministry of Sport, Kitman Labs and Lille OSC.

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🧩 Introduction

Professional soccer teams increasingly rely on optical tracking technologies to monitor player running loads, quantify match demands, design training programs, and guide return-to-play decisions.

But what happens when two tracking technologies produce significantly different results for the same player during the same match?

This study investigated the interchangeability of two optical tracking systems historically used in the English Premier League: PROZONE and TRACAB.

The researchers compared total distance, high-speed running, and sprint distance recorded simultaneously by both systems during competitive matches.

The findings revealed a significant concern:

PROZONE reported substantially greater sprint distances than TRACAB, with an average reported bias of 61%.

This discrepancy raises important questions about the accuracy of historical EPL running-load data, the interpretation of player performance, and the validity of forecasts suggesting that sprint demands are increasing dramatically.

For sports scientists, strength and conditioning coaches, rehabilitation specialists, and technology providers, the study highlights why tracking systems should not automatically be considered interchangeable.

🧪 Study Overview

Design: Observational technology-comparison study using simultaneous optical tracking during competitive soccer matches.

Data collection: 2014–2015 EPL season.

Participants:

• 20 EPL first-team players (average age 27.0 ± 5.1 years).

• 11 under-21 players (average age 17.5 ± 1.3 years).

Matches analyzed:

Technologies Compared

Both systems recorded the same matches, and their final post-processed tracking outputs were compared.

Running Metrics Examined

The researchers used correlation analysis, Bland–Altman agreement analysis, mixed-effects regression, and calibration equations to evaluate differences between the technologies.

📊 Key Findings

1. Sprint Distance Was Substantially Overestimated by PROZONE

The most important finding concerned sprint distance.

Despite a strong positive correlation between the two systems, PROZONE consistently reported substantially higher sprint volumes.

The reported results included:

• Mean bias: 61%.

• Correlation: r = 0.73.

• Standard error of estimate: 34%.

• Effect size: Cohen’s d = 0.76.

Although both systems identified similar relative patterns between players, they produced substantially different absolute sprint-distance measurements.

The mean raw difference was approximately 99 meters per observation.

This is particularly relevant because sprint exposure is commonly used to guide high-speed training, hamstring rehabilitation, and return-to-sport progression.

2. Total Distance Showed Excellent Agreement Between Systems

In contrast to sprint distance, total distance measurements were closely aligned.

The authors concluded that total-distance data could be interpreted across the two systems with relatively limited concern.

Although the systems produced an average difference of approximately 484 meters, the researchers considered the magnitude unlikely to meaningfully alter training decisions in most professional soccer contexts.

Practical implication: Total distance appears considerably more robust to differences between these particular optical tracking technologies than sprint distance.

3. High-Speed Running Showed Reasonable Agreement, but With Greater Variability

High-speed running measurements were also relatively similar between the two systems.

The researchers considered the overall mean bias relatively small, but highlighted meaningful variability between matches and individual observations.

This distinction is important: two technologies can produce similar group averages while still generating considerable uncertainty for individual players.

4. Stadium Design and Camera Positioning May Influence Tracking Accuracy

The researchers observed substantial differences in sprint-distance bias across stadiums.

The sprint-distance bias increased from 31% at Emirates Stadium to 71% and 84% during matches at Goodison Park.

The authors suggested that differences in camera positioning, stadium geometry, resolution, and tracking configuration may have contributed.

Emirates Stadium features a relatively consistent open-bowl design, whereas Goodison Park had a more traditional four-stand configuration with varying heights and camera angles.

These findings suggest that stadium characteristics may influence optical tracking outputs, although the study could not isolate stadium design as the cause.

5. Camera Sampling Frequency and Data Processing May Explain the Differences

The two systems used different camera technologies.

PROZONE recorded positional data at 10 Hz, compared with 25 Hz for TRACAB.

That corresponds to one positional measurement every 100 milliseconds for PROZONE versus every 40 milliseconds for TRACAB.

The researchers identified several potential sources of disagreement:

• Camera sampling frequency.

• Image resolution.

• Camera positioning and distribution.

• Positional-data smoothing and filtering.

• Proprietary algorithms used to calculate velocity and distance.

Sprint measurements may be particularly sensitive to these differences because small errors in instantaneous speed can change whether a movement exceeds the sprint threshold.

The study reinforces that the accuracy of a tracking system depends not only on its cameras, but also on the algorithms used to transform positional data into performance metrics.

6. Historical EPL Sprinting Demands May Have Been Overestimated

An important implication of the research concerns how the physical demands of professional soccer have evolved.

Earlier EPL research reported approximately a 35% increase in sprint distance between the 2006/07 and 2012/13 seasons.

These findings have contributed to the perception that modern soccer is becoming progressively faster and more physically demanding.

However, the current study suggests that historical PROZONE data may have overestimated the absolute amount of sprint running performed by players.

Importantly, the authors did not dispute the historical upward trend itself. Instead, they questioned the absolute sprint-distance values and the magnitude of forecasts based on them.

The study’s Figure 5 illustrates how applying calibration equations reduces the estimated sprint distances while preserving the general upward trajectory.

Implication: Before concluding that modern players must prepare for dramatically greater sprint volumes, clubs should consider whether historical and contemporary tracking data are directly comparable.

7. Tracking Differences Can Significantly Affect Individual Player Monitoring

The researchers illustrated how these measurement differences could affect an individual EPL full-back.

For one player, the study identified an approximately 126-meter difference in sprint distance after applying the calibration equation.

That difference represented roughly 40% of the player’s reported match sprint load.

Another example from Figure 6 compared the player’s season-long sprint-distance measurements:

These differences could change how practitioners interpret whether a player has received sufficient sprint exposure during matches.

They could also affect decisions about supplementary sprint training, weekly conditioning, and rehabilitation progression.

🧠 Implications for EPL Teams and Practitioners

For Heads of Sports Performance

The study highlights the importance of understanding the measurement limitations of tracking technologies before integrating their outputs into performance-management systems.

Clubs may use optical tracking for matches and GPS or local positioning systems during training. When these technologies produce different measurements, comparisons of match and training loads may be misleading.

A player could appear to have completed more sprint running during competition than the underlying physical demands justify.

This could influence weekly training plans and the interpretation of cumulative workloads.

For Strength & Conditioning Coaches

Sprint-distance data are frequently used to guide the amount of high-speed exposure players receive throughout the training week.

If match sprint distance is overestimated, practitioners could incorrectly conclude that a player has received sufficient sprint exposure.

The authors discuss how these discrepancies could influence decisions about additional positional speed or speed-endurance training.

For Rehabilitation and Return-to-Play Specialists

The implications may be particularly important during hamstring rehabilitation.

Sprint running places substantial mechanical demands on the posterior chain, and progressive sprint exposure is an important component of return-to-sport preparation.

If the reference match demands are inaccurate, rehabilitation staff may set sprint-distance targets that do not accurately reflect competition.

This could result in unnecessary additional running or inappropriate progression targets.

For Performance Analysts and Data Scientists

The findings emphasize the importance of validating data compatibility before combining information from different providers.

A historical database containing multiple tracking technologies should not automatically be treated as a single continuous dataset.

Even when two systems correlate strongly, meaningful differences in absolute measurements may remain.

📌 Recommendations

For Sports Performance Departments

• Validate agreement between tracking systems before comparing their outputs.

• Establish consistent definitions for total distance, HSR, and sprint distance.

• Record the technology, software version, and processing methods associated with each dataset.

• Review historical sprint-distance benchmarks before using them to prescribe training.

• Consider individual player speed profiles alongside fixed speed thresholds.

For Strength & Conditioning Coaches

• Avoid relying exclusively on optical sprint-distance measurements when prescribing running loads.

• Combine match tracking data with training observations and other validated monitoring tools.

• Consider the uncertainty associated with sprint measurements when planning supplementary speed sessions.

• Evaluate sprint exposure within the context of playing position, tactical role, and match demands.

For Medical and Rehabilitation Staff

• Confirm the reliability of match-derived sprint benchmarks before using them as return-to-sport targets.

• Monitor rehabilitation sprint exposure using consistent measurement technologies where possible.

• Avoid assuming that sprint volumes from different systems are directly interchangeable.

• Integrate tracking data with physical assessments, movement quality, symptoms, and functional progression.

For Sports Technology Companies

This research also has important implications for companies developing optical tracking, GPS, local positioning, and athlete management technologies.

Potential priorities include:

• Cross-platform validation: Demonstrate agreement with other commonly used tracking systems.

• Transparent processing: Explain how raw positional data are filtered and transformed into running metrics.

• Calibration: Develop validated methods for comparing historical and contemporary datasets.

• Data integration: Help teams identify when measurements from different technologies should not be directly combined.

• Uncertainty reporting: Communicate expected measurement error rather than presenting every output as equally precise.

For athlete management system providers, this creates an opportunity to help practitioners distinguish real changes in athlete performance from changes caused by measurement technology.

These are proposed applications of the findings, rather than products or solutions directly evaluated by the researchers.

⚠️ Limitations

The study has several important limitations.

1. Small sample: Only 31 players from one EPL club were included.

2. Limited number of matches: The comparison covered three competitive matches, restricting generalizability across clubs and stadiums.

3. Historical technology: The data were collected during the 2014/15 season using older generations of PROZONE and TRACAB.

4. Limited stadium representation: Only two stadiums were evaluated, making it difficult to isolate the influence of stadium architecture.

5. No simultaneous independent reference standard: The study compared two optical systems rather than directly validating both against a separate ground-truth measurement system.

6. No acceleration or deceleration analysis: These important performance variables were excluded because their calculation methods were not sufficiently known.

7. Uncertainty in calibration: The sprint-distance correction equations had substantial estimation error, meaning corrected values should not be considered exact.

8. Limited applicability to newer technologies: The results cannot automatically be generalized to contemporary tracking systems or newer software generations.

The authors specifically characterized their findings as preliminary and called for further research using larger samples and additional matches.

✅ Conclusion

This study raises important questions about the accuracy and interchangeability of optical tracking technologies used in professional soccer.

While PROZONE and TRACAB demonstrated strong agreement for total distance and reasonable agreement for high-speed running, their sprint-distance outputs differed substantially.

PROZONE reported higher sprint volumes than TRACAB, with an average reported bias of 61%.

These differences may have important implications for how clubs interpret historical match demands, design training programs, monitor sprint exposure, and guide rehabilitation.

The findings also challenge the assumption that historical and contemporary datasets can always be compared directly to establish how the physical demands of professional soccer are evolving.

However, the study does not establish that modern soccer is becoming less demanding or that historical increases in sprinting did not occur.

Instead, it demonstrates the importance of understanding measurement uncertainty before drawing conclusions from tracking data.

For professional teams and sports technology companies, the central takeaway is clear:

Collecting more athlete data is not enough. Teams must also understand how that data is measured, how accurate it is, and whether it can be meaningfully compared across technologies.

🧬 Upside Sports Science Study (3): Unveiling Muscle Fatigue — Identifying Key Gene Biomarkers and Therapeutic Targets

Published in Molecular and Cellular Biochemistry (2026), Springer Nature.

Study: Unveiling Muscle Fatigue: Identifying Key Gene Biomarkers and Therapeutic Targets

Authors: Yifei Zhang, Zehan Zhang, Xiaoyao Chen, Miao Dai, Yuxiao Zheng, Weiyue Zhang and Feng Li.

Institution: Beijing University of Chinese Medicine, China.

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🧩 Introduction

Muscle fatigue is one of the most important challenges facing elite athletes and sports performance departments.

Whether in the NBA, NFL, NHL, MLS, or European soccer, understanding fatigue is essential for managing training loads, optimizing recovery, maintaining performance, and supporting injury-risk management.

Today, professional teams rely on technologies such as GPS, force plates, athlete management systems, heart rate monitoring, blood biomarkers, and subjective wellness questionnaires to assess fatigue and recovery.

But what if teams could identify fatigue at a deeper biological level, by examining the genes associated with fatigue susceptibility?

A new 2026 study published in Molecular and Cellular Biochemistry investigated this possibility.

Researchers from Beijing University of Chinese Medicine used genetic association analysis, bioinformatics, molecular modeling, and animal experiments to identify potential molecular biomarkers of fatigue.

Their research identified six genes associated with fatigue in both skeletal muscle and blood, raising the possibility that future fatigue-monitoring approaches could incorporate molecular biomarkers alongside existing performance technologies.

The researchers also explored potential therapeutic compounds that interact with some of these genetic targets.

However, these findings remain preliminary. The study did not establish a validated blood test for athletic fatigue, demonstrate that any treatment improves recovery, or evaluate professional athletes.

🧪 Study Overview

Design: Genetic association and computational drug-discovery study, supported by experimental validation in a rat model of physical fatigue.

Genetic Data Sources

These datasets were analyzed computationally. They do not represent 449,019 athletes undergoing exercise-fatigue testing.

Research Methods

The study involved five main stages:

1. Summary-data-based Mendelian randomization (SMR): Investigated associations between genetically predicted gene expression and fatigue.

2. Bayesian colocalization: Evaluated whether fatigue and gene-expression associations could share underlying genetic variants.

3. Functional enrichment analysis: Explored biological pathways associated with fatigue-related genes.

4. Drug screening and molecular docking: Identified compounds with potential interactions involving candidate proteins.

5. Animal validation: Examined muscle fatigue and gene expression in 12 male Wistar rats, divided into control and fatigue groups.

The experimental evaluation included grip strength, exhaustive swimming performance, muscle glycogen, blood biochemical markers, and gene-expression measurements.

📊 Key Findings

1. Researchers Identified Six Potential Fatigue-Related Gene Biomarkers

The most important finding was the identification of six genes associated with fatigue in both skeletal muscle and blood.

Genetic discovery pipeline

The six genes were:

These biological functions help explain why the genes may warrant further investigation. They do not establish the mechanism by which each gene contributes to exercise-induced fatigue.

Implication: The findings provide a starting point for developing molecular approaches to fatigue assessment, but further human validation is essential.

2. Gene Expression Was Associated With Different Levels of Fatigue Susceptibility

The researchers identified differences in how individual genes were associated with fatigue.

Three genes showed consistent associations with lower fatigue susceptibility when genetically predicted expression was higher:

• ISYNA1

• PABPC4

• UBOX5

ATP11B showed an association with increased fatigue susceptibility.

Interestingly, ZDHHC5 and KATNAL1 showed different directions of association between skeletal muscle and blood.

Selected odds ratios for genetically predicted expression

An odds ratio below 1 indicates an association with lower fatigue susceptibility, while a value above 1 indicates an association with higher susceptibility.

These estimates concern the study’s self-reported fatigue phenotype. They should not be interpreted as predicted changes in an athlete’s fatigue after training.

Practical implication: The relationship between gene expression and fatigue may depend on the tissue being examined. Blood measurements may not always reflect what is happening inside skeletal muscle.

3. Fatigue-Related Genes Were Linked to Inflammatory and Protein-Regulation Pathways

Functional enrichment analysis identified several biological processes associated with the genes detected in skeletal muscle.

Two particularly relevant areas were:

Interleukin-6 (IL-6) signaling

IL-6 is involved in inflammatory and exercise-related signaling. The researchers identified enrichment in IL-6-mediated signaling pathways, cellular responses to IL-6, and related biological processes.

Ubiquitin-mediated proteolysis

The study also identified enrichment in processes associated with protein ubiquitination and protein degradation.

These pathways may be relevant to understanding the cellular processes associated with fatigue and muscle function.

However, pathway enrichment does not prove that IL-6 signaling or protein degradation caused fatigue in the study population.

4. Animal Experiments Confirmed Significant Changes in the Six Candidate Genes

The researchers developed a fatigue model involving 12 male Wistar rats.

Compared with controls, fatigued rats demonstrated:

• Reduced grip strength.

• Shorter exhaustive swimming duration.

• Reduced muscle glycogen.

• Elevated blood lactate.

• Elevated creatine kinase, blood urea nitrogen, and lactate dehydrogenase.

• Reduced quadriceps muscle fiber cross-sectional area.

These results supported the presence of physical fatigue and associated physiological changes in the experimental model.

Importantly, all six candidate genes demonstrated statistically significant differences in skeletal muscle expression.

The direction of these changes broadly supported the researchers’ candidate-gene findings.

Implication: The experimental results strengthen the biological plausibility of the six genes as fatigue-associated markers, but animal gene-expression changes do not establish diagnostic performance in humans.

5. Researchers Identified Potential Compounds That Interact With Fatigue-Related Targets

The study also explored whether the identified genes could help researchers discover new therapeutic approaches to muscle fatigue.

Using the Drug Signatures Database (DSigDB), researchers identified 308 potential chemical compounds associated with the six candidate genes.

Among the compounds investigated were valproic acid, hesperidin, and cannabidiol.

The researchers then performed molecular docking simulations to evaluate potential interactions between these compounds and selected target proteins.

Selected molecular docking results

More negative docking energies suggest stronger predicted binding under the modeling conditions.

The researchers identified ISYNA1 as a potentially important therapeutic target because several compounds demonstrated predicted interactions with it.

However, none of these compounds was administered as a treatment in the animal experiment, and no therapeutic efficacy was demonstrated.

Molecular docking does not establish that a compound reduces fatigue, accelerates recovery, or is safe or appropriate for athletes.

This distinction is especially important in elite sports, where medication safety, side effects, and anti-doping regulations must be considered.

6. Blood-Based Gene Biomarkers Could Become an Important Area of Future Research

One of the most interesting aspects of the study is that the six candidate genes were associated with fatigue in both skeletal muscle and blood.

Collecting skeletal muscle samples is invasive and generally impractical for routine athlete monitoring.

Blood samples, by comparison, are much more accessible.

This creates an opportunity to investigate whether blood-based molecular measurements could eventually provide additional information about fatigue-related biological processes.

For example, future studies could explore whether changes in blood gene expression are associated with:

• Fatigue following intensive training or competition.

• Recovery following congested match schedules.

• Changes in neuromuscular performance.

• Persistent fatigue during rehabilitation.

• Individual differences in responses to training loads.

These are proposed future applications, not capabilities demonstrated by the current study.

The researchers did not measure blood expression of the six genes longitudinally during athlete training or recovery. They also did not establish diagnostic thresholds, sensitivity, specificity, or individual prediction accuracy.

🧠 Implications for Elite Sports Teams and Practitioners

For Heads of Sports Performance

The study introduces a potential additional dimension to athlete monitoring: molecular biology.

Most performance departments currently evaluate fatigue through a combination of external workload, physiological measurements, neuromuscular testing, and athlete feedback.

In the future, molecular biomarkers could potentially complement these measurements.

However, the first step would be to establish whether the identified genes reliably change in response to exercise-induced fatigue in human athletes.

For Strength & Conditioning Coaches

The research raises questions about why athletes may respond differently to similar training loads.

Two players completing comparable workloads can experience different levels of perceived fatigue and recovery.

Genetic and molecular factors may contribute to this variability, alongside sleep, nutrition, conditioning, training history, and other influences.

Future research could investigate whether the six candidate genes help explain these differences.

At present, the study does not justify changing training prescriptions based on an athlete’s gene expression or genetic profile.

For Athletic Trainers and Rehabilitation Specialists

Understanding the molecular processes associated with fatigue could eventually contribute to more personalized rehabilitation strategies.

Potential research applications include monitoring recovery following prolonged inactivity, identifying biological responses to progressive exercise, and investigating persistent fatigue during return-to-play.

Nevertheless, the study did not evaluate injured athletes or test whether these biomarkers predict reinjury or rehabilitation outcomes.

For Sports Scientists and Performance Analysts

The findings highlight the possibility of integrating molecular information with existing performance datasets.

Future research could investigate relationships between candidate gene expression and:

• GPS-derived running loads and sprint exposure.

• Countermovement jump and force-plate metrics.

• Heart rate and heart rate variability.

• Subjective wellness and fatigue questionnaires.

• Sleep and recovery measurements.

Such work would help determine whether molecular biomarkers provide information beyond established monitoring methods.

🚀 Implications for Sports Technology Companies

This study could have longer-term implications for several areas of sports technology.

One particularly interesting opportunity concerns the intersection of AI, genomics, and athlete monitoring.

For example, future systems might combine workload information, sleep, neuromuscular performance, and molecular measurements to build more comprehensive models of athlete recovery.

But these models would require substantial validation before being used to guide decisions in professional sports.

📌 Recommendations

For Professional Sports Teams

• Continue using validated workload, neuromuscular, physiological, and subjective fatigue measurements.

• Monitor emerging research on gene-expression biomarkers and muscle fatigue.

• Explore collaborations with universities specializing in exercise physiology, molecular biology, and genomics.

• Avoid implementing genetic fatigue scores or treatment decisions based on these six genes without clinical and sport-specific validation.

• Consider the privacy and ethical implications of collecting athletes’ genetic or molecular data.

For Universities and Research Laboratories

• Replicate the findings in human athletes.

• Evaluate the six candidate genes before and after exercise.

• Investigate gene-expression changes during recovery periods.

• Compare blood gene expression with skeletal muscle responses.

• Examine whether biomarkers differ between trained and untrained populations.

• Determine whether these biomarkers offer predictive value beyond existing fatigue measurements.

For Sports Technology Startups

• Explore partnerships with molecular diagnostics laboratories.

• Investigate the feasibility and reproducibility of blood-based gene-expression measurements.

• Evaluate whether molecular markers improve fatigue classification or recovery assessment.

• Prioritize longitudinal validation rather than relying on single-time-point measurements.

• Avoid commercial claims about fatigue diagnosis, injury prediction, or treatment until supported by appropriate human evidence.

For Sports Medicine and Rehabilitation Departments

• Monitor research into the biological mechanisms underlying fatigue.

• Continue using comprehensive assessments rather than isolated biomarkers.

• Evaluate future molecular tests based on their clinical validity, reliability, and relevance to individual athletes.

• Ensure that any potential pharmacological intervention is assessed for safety, medical appropriateness, and anti-doping compliance.

⚠️ Limitations

The study has several important limitations.

1. Self-reported fatigue phenotype: The primary genetic analysis used a GWAS of self-reported fatigue, not direct measurements of exercise-induced muscle fatigue in athletes.

2. No human athletic validation: The researchers did not test the six candidate genes in professional or recreational athletes undergoing training or competition.

3. Small animal sample: Experimental validation involved only 12 male rats, with six animals in each group.

4. Blood and muscle differences: Two genes, ZDHHC5 and KATNAL1, showed opposite directions of genetic association between blood and skeletal muscle.

5. No validated diagnostic test: The study did not establish whether measuring these genes can accurately distinguish fatigued from recovered individuals.

6. No longitudinal recovery analysis: The researchers did not track how gene expression changes throughout exercise and recovery in human athletes.

7. Computational drug predictions: Drug candidates were identified through database screening and molecular docking, without experimental evidence of treatment effectiveness.

8. Limited causal certainty: Although SMR and colocalization strengthen genetic associations, they do not conclusively establish the biological mechanisms or prove that modifying these genes will change fatigue.

9. No injury prediction: The study did not investigate whether these biomarkers predict muscle injuries or other sports-related injuries.

Future studies will need to address these limitations before the findings can be translated into practical applications for elite sports.

✅ Conclusion

This 2026 study provides an interesting contribution to our understanding of the molecular mechanisms potentially associated with fatigue.

Using genetic association analyses, computational modeling, and experimental validation in rats, researchers identified six candidate genes linked to fatigue in both skeletal muscle and blood:

ISYNA1, PABPC4, ZDHHC5, KATNAL1, UBOX5, and ATP11B.

The study also highlighted biological pathways involving inflammatory signaling and protein regulation, while identifying potential molecular targets for future therapeutic research.

For elite sports, the findings raise the possibility that future athlete-monitoring systems could incorporate molecular biomarkers alongside GPS, force plates, wearables, and subjective wellness measurements.

However, there remains a substantial gap between identifying fatigue-associated genes and developing clinically validated tools that can guide training, recovery, or injury-risk decisions.

At Upside, we believe one of the most interesting opportunities for sports science and sports technology will be the integration of multiple layers of athlete data, from external workload and biomechanics to physiology and, potentially, molecular biology.

The future of athlete monitoring may not simply be about measuring how much work an athlete performs, but also understanding how their body responds to that work at a cellular and molecular level.

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How Physical AI, robotics, digital twins, and intelligent simulation could transform athlete performance, injury management, rehabilitation, and sports technology.

Introduction: AI Is Moving From the Digital World Into the Physical World

Over the past three years, artificial intelligence has attracted enormous attention across the sports industry.

Professional teams across the NBA, NFL, NHL, MLS, MLB, NCAA, and European soccer are increasingly exploring AI-powered solutions for athlete monitoring, scouting, performance analytics, injury-risk assessment, and operational productivity.

Much of this innovation has focused on large language models (LLMs), generative AI assistants, predictive algorithms, and automated data analysis.

But another development could have even greater long-term implications for elite sports: Physical AI.

Companies such as NVIDIA, Google DeepMind, and robotics researchers are developing AI systems capable of understanding physical environments, learning how objects and bodies move, predicting physical interactions, and controlling actions in the real world.

NVIDIA describes this shift through technologies that combine AI foundation models, physical simulation, robotics, and autonomous systems.

For elite sports, the potential implications are substantial.

Imagine a future in which:

• An NBA team can simulate thousands of basketball landing movements to investigate how different movement strategies affect joint loading.

• An NFL team can create a biomechanical model of a quarterback to explore how changes in throwing mechanics influence performance.

• An NHL team can use intelligent robotic systems to create repeatable, adaptive rehabilitation exercises.

• An MLS club can develop a personalized digital twin of a player to explore training loads, movement patterns, and recovery scenarios.

• A sports scientist can test proposed training interventions in a simulation before deciding whether they warrant evaluation with athletes.

Some underlying technologies already exist in research environments. Others remain speculative, particularly when it comes to accurate, individualized predictions of injury or training outcomes.

The central opportunity is not simply to collect more athlete data.

It is to move from observing and analyzing human movement toward modeling, simulating, and eventually interacting intelligently with the physical demands of elite sports.

That could represent a major evolution in how professional teams train, evaluate, rehabilitate, and develop athletes.

What Is Physical AI?

Physical AI refers to artificial intelligence systems that can perceive, reason about, predict, or act within the physical world.

Unlike AI systems that primarily generate text or analyze digital information, Physical AI must account for real-world constraints such as gravity, movement, force, balance, collisions, spatial relationships, and the behavior of physical objects.

A Physical AI system might use cameras, sensors, and other inputs to understand an environment, then apply learned models or physical simulation to predict outcomes or control an action.

The core components of Physical AI

For example, an AI-powered robotic table tennis system must identify the ball’s location and velocity, predict its trajectory, determine how to position a racket, and execute a physical movement quickly enough to return the shot.

That is fundamentally different from asking ChatGPT to summarize a match or explain table tennis tactics.

Physical AI is not simply another name for sports analytics

This distinction is important.

A machine-learning model that predicts an athlete’s workload from GPS data is not automatically a Physical AI system.

Similarly, markerless motion capture does not necessarily constitute Physical AI on its own.

However, motion capture can become an important component of a broader Physical AI system when its measurements are integrated with physical models, simulation, decision-making, and potentially real-world control.

For sports, I would divide the emerging opportunity into three categories:

1. Embodied Physical AI: Robots and intelligent machines that perceive and interact with the real world.

2. Physics-aware athlete simulation: Systems that combine biomechanics, physics-based models, and AI to simulate movements or training scenarios.

3. Intelligent physical environments: Training facilities and equipment that adapt to athletes using sensors, AI, and real-time feedback.

The first category most closely matches the conventional definition of Physical AI. The second and third represent adjacent technologies that could become important sports applications.

Physical AI vs. Large Language Models: What’s the Difference?

LLMs and Physical AI share some underlying machine-learning technologies, but they are designed to solve different problems.

Example: An NFL quarterback

Consider a quarterback whose throwing mechanics are being evaluated.

An LLM-based sports assistant could analyze existing reports and answer questions such as:

How has this quarterback’s throwing velocity changed over the past six weeks?

A physics-aware simulation system could potentially investigate a different question:

What happens to estimated joint loading and ball release characteristics when the quarterback changes trunk rotation or arm position?

An embodied Physical AI system might eventually control a robotic training device that adapts defensive pressure or ball delivery in response to the quarterback’s actions.

These systems are not mutually exclusive.

In fact, I expect the most interesting sports technology platforms to combine conversational AI, biomechanical modeling, physical simulation, and sensor-driven feedback.

LLMs could become the interface, while physical models and intelligent machines provide the underlying physical understanding and execution.

Seven Potential Use Cases for Physical AI in Elite Sports

The greatest opportunity is likely to come from combining Physical AI with technologies that professional teams already use: GPS, force plates, motion capture, IMUs, athlete management systems, and video analysis.

Use case 1: Athlete digital twins and personalized simulation

investing.com

An athlete digital twin is a computational representation of an athlete that can be updated using relevant measurements.

A sophisticated version might combine body geometry, joint kinematics, muscle-tendon models, force measurements, workload history, and other physiological variables.

The long-term ambition is to simulate how an individual athlete might respond to specific physical demands.

For example, a performance department could investigate how different landing techniques affect modeled knee loading, or how changes in running mechanics influence estimated muscle forces.

The distinction between a generic biomechanical model and a truly personalized digital twin is critical. A system must be calibrated and validated against the individual athlete before its predictions can be treated as reliable.

Potential applications: Movement optimization, rehabilitation planning, technique analysis, equipment evaluation, and training research.

Use case 2: Biomechanics and skill acquisition

Physical AI could help teams understand how athletes execute complex sporting movements.

Potential examples include:

• NFL: Quarterback throwing mechanics, footwork, and movement under pressure.

• NBA: Shooting mechanics, jumping, landing, and change of direction.

• NHL: Skating biomechanics, acceleration, and shooting mechanics.

• MLB: Pitching, batting, and throwing.

• Soccer: Kicking, sprinting, cutting, and deceleration.

Today, markerless motion capture and biomechanical modeling already make aspects of these analyses possible.

The next step would be to connect movement analysis with physics-aware simulations and individualized training interventions.

Rather than simply telling an athlete that their mechanics differ from a reference pattern, a system could explore the consequences of alternative movement strategies.

However, the most efficient movement is not necessarily identical across athletes, and a simulation cannot independently establish that a technique change will improve performance.

Use case 3: Injury-risk research and return-to-play

Physical AI could be particularly relevant to sports medicine and rehabilitation.

Consider an athlete recovering from an ACL reconstruction.

A future system could combine repeated motion assessments, force plate data, muscle strength, and a calibrated musculoskeletal model to investigate how loading changes across rehabilitation exercises.

This could help practitioners understand movement strategies and select appropriate assessments.

But there is a major distinction between estimating joint loading and accurately predicting a future injury.

Physical AI should not be presented as a proven solution for injury prediction.

Current evidence supports carefully defined biomechanical measurements more strongly than reliable individual injury forecasting.

Use case 4: Intelligent robotic training partners

newatlas.com

This is one of the clearest examples of Physical AI moving beyond conventional sports analytics.

Researchers have demonstrated robots that learn to play simplified soccer and table tennis using reinforcement learning, simulation, and real-world control.

In the future, robotic training partners could provide repeatable or adaptive challenges in tennis, table tennis, goalkeeper training, and other skill-based environments.

A robotic system could vary ball trajectories, speed, timing, and difficulty according to an athlete’s responses.

The opportunity is not necessarily to replace human coaches or training partners, but to create controlled practice environments.

Use case 5: Intelligent training facilities

Imagine a professional training facility where multiple systems communicate in real time.

Cameras capture athlete movement, sensors measure physical outputs, and intelligent equipment adjusts training conditions within predefined safety limits.

Potential applications include adaptive resistance devices, automated ball delivery, controlled rehabilitation equipment, and responsive training environments.

Many components already exist independently. The longer-term Physical AI opportunity is to coordinate them through a shared understanding of the physical environment.

Use case 6: Tactical simulation and player development

Physical simulation could also become useful for tactical training.

For example, a soccer club might explore how players move into available space under different defensive arrangements.

An NFL team could simulate constrained movement scenarios involving quarterbacks, receivers, and defenders.

A basketball team might investigate spacing, movement trajectories, and player interactions.

These applications would require models that capture not only physical constraints but also human decisions and tactical behavior.

Consequently, they should be viewed as decision-support or research tools rather than accurate predictions of how real athletes will behave in every situation.

Use case 7: Automated physical operations

Some of the earliest commercial applications of Physical AI in sports may occur outside direct athlete performance.

Autonomous systems could potentially assist with equipment movement, inventory management, facility inspection, field maintenance, and selected operational tasks.

These are attractive applications because their success can often be measured more clearly than improvements in athletic performance.

For example, teams could evaluate time saved, task completion rates, operational reliability, and safety.

Which use cases should teams prioritize?

Upside assessment of potential adoption—not a ranking of clinically proven effectiveness.

My assessment is that biomechanics, physical modeling, and movement assessment are likely to offer more practical near-term opportunities than fully autonomous robotic coaches or highly accurate athlete digital twins.

Latest Research: What Does the Science Actually Show?

Several important studies published between 2023 and October 2026 illustrate the progress being made in Physical AI and closely related technologies.

It is important to distinguish studies of actual embodied AI from studies of biomechanical measurement and simulation.

Study 1: Google DeepMind — Robots Learning to Play Soccer

Science Robotics | April 2024

Paper: Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

Researchers trained miniature humanoid robots to play simplified one-on-one soccer using deep reinforcement learning.

The robots learned skills such as walking, turning, kicking, recovering from falls, and reacting to an opponent.

Improvements relative to a scripted robotic baseline, not human athletes.

The system learned in simulation and transferred its behavior to real robots.

Why it matters for elite sports: This demonstrates that AI can learn coordinated physical sporting skills rather than merely classify or describe movement.

It does not demonstrate improved training outcomes for human soccer players.

Study 2: Google DeepMind — Competitive Robotic Table Tennis

Research preprint, 2024; ICLR workshop version, 2025

Paper: Achieving Human Level Competitive Robot Table Tennis

Google DeepMind developed a robotic table tennis system that combined real-time perception, learned movement policies, and simulation-to-reality transfer.

The robot won 13 of 29 matches against previously unseen human players, achieving amateur-level performance. It lost against the most advanced players in the evaluation.

Why it matters: Intelligent training machines may eventually adapt to human opponents in real time, creating new possibilities for skill development.

Study 3: LATENT — Humanoid Robots Learning Tennis From Imperfect Human Motion Data

arXiv preprint | March 2026

Paper: Learning Athletic Humanoid Tennis Skills from Imperfect Human Motion Data

Researchers introduced LATENT, a framework that enables humanoid robots to learn tennis movements using incomplete human motion demonstrations.

Rather than requiring complete recordings of every possible movement, the system learned from fragments of tennis-related skills and combined them into more complex behaviors.

The researchers demonstrated the approach on a Unitree G1 humanoid robot, including multi-shot rallies with human players.

Why it matters: Human movement data may become a valuable training resource for physical AI systems, including robotic training partners.

This is an experimental robotics result, not evidence that the system improves human tennis performance.

Study 4: ATHLETE — Reactive Humanoid Tennis

arXiv preprint | October 2026

Paper: ATHLETE: Learning Reactive Humanoid Tennis via Trajectory-Guided Motion Matching

This recent research explores how humanoid robots can learn responsive tennis movements using locomotion data and ordinary tennis videos.

The researchers reported the following real-robot results:

These results were achieved under the researchers’ experimental conditions and should not be interpreted as general competitive tennis performance.

Why it matters: Physical AI systems are becoming better at combining human movement examples with real-time responses to moving objects.

Study 5: Stanford — OpenCap and Human Movement Dynamics

PLOS Computational Biology | October 2023

Paper: OpenCap: Human Movement Dynamics From Smartphone Videos

This is one of the most relevant studies for sports performance practitioners, although OpenCap is better described as an AI-assisted biomechanics and simulation platform than a complete embodied Physical AI system.

Researchers combined smartphone video, computer vision, machine learning, and musculoskeletal simulation to estimate movement kinematics and dynamics.

In a field study involving 100 participants, the researchers reported that their approach estimated musculoskeletal dynamics approximately 25 times faster than a laboratory-based approach at less than 1% of the cost.

Why it matters: Physics-based biomechanical analysis could become more accessible to professional teams, universities, and rehabilitation departments without requiring every assessment to take place in a sophisticated biomechanics laboratory.

Study 6: OpenCap Validation During Return-to-Sport Tasks

Journal of Biomechanics | June 2024

Paper: Validation of OpenCap: A Low-Cost Markerless Motion Capture System for Lower-Extremity Kinematics During Return-to-Sport Tasks

Researchers evaluated OpenCap against a traditional marker-based motion capture system in athletes recovering from ACL reconstruction.

The study examined 437 movement trials involving hopping and landing tasks.

The reported grand mean error across joint angles and movements was 3.85° for mean absolute error and 4.34° for root mean squared error.

Agreement was strongest for selected sagittal-plane hip and knee movements, with weaker agreement in other planes.

Why it matters: Accessible movement analysis is promising, but measurement accuracy varies by joint, movement, and plane. Teams should validate the specific metrics they intend to use.

Study 7: Markerless Motion Capture vs. Wearable Sensors

Medicine & Science in Sports & Exercise | March 2025

Paper: The Validity and Usability of Markerless Motion Capture and Inertial Measurement Units for Quantifying Dynamic Movements

This study compared several movement analysis technologies across dynamic exercises, including jumps, squats, lunges, and cutting movements.

The researchers found that the evaluated markerless system generally demonstrated higher validity than the tested IMU and RGB-depth camera systems, although errors varied considerably across joints and movement planes.

Why it matters: Physical AI applications will depend heavily on the quality of the underlying movement data. A sophisticated simulation built on inaccurate measurements can still produce misleading results.

Study 8: Athlete-AI — Multimodal Monitoring and Training Simulation

Scientific Reports | October 22, 2026

Paper: Athlete-AI: A Multi-Modal Artificial Intelligence Framework for Personalized Athlete Monitoring and Injury Risk Forecasting

This newly published study presents a computational framework combining wearable sensor information, human motion features, multimodal machine learning, and reinforcement learning.

Its significance lies in demonstrating how different sources of athlete information can be combined in a simulation environment.

However, the authors explicitly state that the results are preliminary computational findings and do not constitute prospective real-world athlete validation.

Why it matters: The research illustrates a possible direction for intelligent athlete simulation, while reinforcing the need to distinguish experimental modeling from clinically validated injury-risk prediction.

What does the evidence tell us?

The scientific literature supports three important conclusions.

First, Physical AI can already learn and execute complex physical behaviors in controlled robotic environments.

Second, AI-assisted biomechanics and physics-based simulation can provide useful movement estimates, although accuracy depends on the specific task and measurement system.

Third, evidence that these technologies improve long-term athlete performance, reduce injury incidence, or reliably predict individual injury outcomes remains much less mature.

A 2026 scoping review of AI in sports science similarly found that technical measurement applications have stronger evidence than injury prediction and athlete digital twins, with a lack of demonstrated sustained improvements in real-world organizational or athlete outcomes.

How Physical AI Could Transform Elite Sports

I believe Physical AI could create five major shifts in how sports organizations operate.

A. From descriptive analytics to physical simulation

Today, teams use GPS, force plates, and athlete management systems to understand what happened during training or competition.

Physical AI could introduce another layer: investigating what might happen under alternative physical conditions.

For example, instead of only reporting that an athlete experienced a certain external workload, a team could use a calibrated biomechanical model to estimate how different movements distribute forces across joints and muscles.

This could help performance departments formulate more precise questions and design better experiments.

B. From generic training programs to individualized movement models

Most professional teams already individualize training.

Physical AI could potentially take personalization further by combining an athlete’s movement characteristics with physical simulation.

Rather than assuming that one technical intervention works equally well for every player, practitioners could investigate athlete-specific responses.

However, individualization would require reliable calibration, longitudinal data, and validation against actual training outcomes.

C. From static equipment to adaptive training environments

Many training technologies currently follow predefined programs.

Future systems could adjust the physical environment based on an athlete’s actions.

For example, a robotic ball-delivery system could adapt its trajectories based on the player’s reaction time, accuracy, or movement strategy.

Similarly, intelligent resistance equipment could adjust within safe operating limits according to measured performance.

This could support more repeatable and individualized skill acquisition.

D. From isolated technology platforms to integrated intelligence

One of the biggest challenges in elite sports is that technologies often operate independently.

A team might use:

• GPS to measure external workload.

• Force plates to assess neuromuscular performance.

• Motion capture to evaluate biomechanics.

• Wearables to collect physiological information.

• An AMS to organize athlete information.

Physical AI could increase the value of these systems by providing models that connect measurements to physical mechanisms.

This creates an opportunity for technology vendors that can integrate high-quality data across different modalities.

E. From reactive rehabilitation to simulation-informed rehabilitation

Sports medicine departments could potentially use biomechanical simulations to investigate movement strategies and rehabilitation exercises before implementing changes.

For example, clinicians could compare estimated loading patterns across different exercises or movement techniques.

The objective would not be to automate return-to-play clearance.

Instead, Physical AI could provide additional information to support practitioners’ decisions.

The biggest transformation may be the shift from collecting information about athletes to building validated models of how athletes move and respond to physical demands.

Main Companies and Technology Platforms to Watch

The Physical AI ecosystem includes foundational technology companies, robotics developers, biomechanics platforms, and sports-specific vendors.

Not every company in this section currently markets a Physical AI product. Some provide essential components that could enable future applications.

A. Foundational Physical AI and robotics companies

Other organizations worth monitoring include Boston Dynamics, Figure AI, and robotics research groups developing vision-language-action models. Their relevance to sports is primarily prospective rather than evidence of established elite-team deployments.

B. Sports biomechanics and simulation platforms

These companies and platforms occupy different positions in the technology stack. Most are not autonomous Physical AI vendors today.

Their potential importance lies in providing the movement data, measurement tools, and biomechanical models that future Physical AI systems may require.

For example, Theia’s 2026 baseball developments illustrate how markerless capture is expanding beyond athlete movement to include bat and ball tracking in a single system.

C. Where could new sports technology startups emerge?

I expect new opportunities in several categories:

1. Athlete digital twin platforms: Combining motion capture, force measurements, and musculoskeletal modeling to create individualized simulation environments.

2. AI-powered biomechanics companies: Moving beyond descriptive joint-angle reporting toward validated physics-aware assessments.

3. Intelligent robotic training systems: Developing adaptive equipment for skill acquisition and controlled practice.

4. Simulation platforms for sports medicine: Supporting research into exercise selection, joint loading, and rehabilitation progression.

5. Physical AI infrastructure for sports: Integrating video, wearables, force plates, and other sensors into reusable simulation and modeling environments.

For investors, the critical question will be whether these startups have defensible technology and demonstrated value rather than simply incorporating the term Physical AI into their marketing.

What Will Elite Sports Look Like With Physical AI?

A possible scenario for 2030–2035, not a forecast of confirmed deployments. Imagine the daily workflow of a professional soccer club.

In this environment, Physical AI would not replace coaches, sports scientists, or medical professionals.

It would provide an additional layer of modeling, experimentation, and feedback.

The most sophisticated organizations could develop integrated systems connecting performance departments, biomechanics laboratories, rehabilitation teams, and technology vendors.

However, not every team will need humanoid robots or expensive simulation infrastructure.

For many organizations, the most valuable implementation could be a relatively modest system that combines reliable movement measurements with validated biomechanical models.

Recommendations to Professional Teams

I would recommend that teams take a proactive but disciplined approach to Physical AI.

1. Understand what Physical AI can and cannot do

Performance directors and medical staff should distinguish among robotics, biomechanical simulation, motion capture, conventional machine learning, and generative AI.

These technologies overlap, but they are not interchangeable.

2. Audit existing movement and performance data

Before investing in advanced simulation, determine whether the organization has sufficiently accurate, consistent, and accessible data.

A team may already possess valuable information from GPS, force plates, motion capture, and rehabilitation assessments.

The challenge is making those measurements usable together.

3. Start with one or two measurable applications

Prioritize problems such as improving movement assessment workflows, estimating selected biomechanical variables, or automating repetitive analysis.

Avoid beginning with ambitious promises about predicting injuries or accurately simulating an athlete’s entire season.

4. Partner with universities and research laboratories

Universities with expertise in biomechanics, robotics, AI, and computational modeling could become important partners.

Research groups at Stanford, Carnegie Mellon, and other institutions provide examples of relevant technical expertise.

Such partnerships could help teams evaluate emerging technologies before making large commercial commitments.

5. Require independent validation

Teams should ask vendors to demonstrate measurement accuracy, repeatability, external validity, and meaningful improvements in practitioner workflows.

For high-stakes applications, simulation predictions should be evaluated against real-world outcomes before being relied upon.

6. Protect athlete data and maintain human oversight

Detailed movement models and athlete digital twins may involve sensitive biometric and health-related information.

Teams need clear policies covering consent, data ownership, cybersecurity, access permissions, model training, and retention.

Medical and return-to-play decisions should remain under appropriately qualified professional oversight.

Recommendations to Sports Technology Companies

Physical AI could also create significant opportunities for established sports technology vendors and startups.

A. Motion capture and biomechanics companies

Companies such as Qualisys, Theia, and Vicon could explore how their movement data might support more advanced physical simulations.

Potential development priorities include:

• Improved interoperability with musculoskeletal modeling software.

• APIs for research and simulation environments.

• Validated estimates of biomechanical variables.

• Support for longitudinal athlete assessments.

• Integration with physics-aware AI models.

The opportunity is to move beyond reporting movement measurements toward supporting more advanced biomechanical decision-making.

B. Athlete Management System providers

Companies operating in the AMS ecosystem could eventually integrate simulation outputs alongside conventional athlete monitoring data.

For example, a performance director might ask an AI assistant to compare selected movement measurements across rehabilitation sessions or retrieve model-based loading estimates.

However, AMS companies do not necessarily need to build Physical AI foundation models themselves.

Partnerships with biomechanics specialists, universities, and simulation providers may be more practical.

C. Sports AI startups

For startups, I see three priorities.

First, build defensible technology around a clearly defined physical problem.

Second, validate the technology with appropriate research partners and real sporting environments.

Third, demonstrate that the solution improves an existing workflow or enables a useful capability that teams could not previously access.

A startup that can reliably solve one important biomechanics problem may be more valuable than a company promising a complete AI-powered digital twin of every athlete without sufficient evidence.

D. Strategic partnerships with Physical AI leaders

Sports technology companies should monitor developments from NVIDIA, Google DeepMind, robotics laboratories, and simulation researchers.

They may not need to develop every underlying model internally.

Instead, their competitive advantage could come from combining foundational Physical AI technology with proprietary sports data, domain expertise, validated workflows, and established team relationships.

Key Challenges and Barriers to Adoption

Despite its potential, Physical AI faces substantial technical and commercial challenges.

One of the biggest challenges will be the difference between creating an impressive demonstration and delivering a dependable product that can be used every day by professional sports organizations.

This is particularly important for startups.

Teams should not confuse technological sophistication with commercial readiness or scientific validity.

Conclusion: Physical AI Could Become a New Frontier in Sports Performance

The emergence of Physical AI represents an important development in artificial intelligence.

While large language models have transformed how organizations interact with information, Physical AI is expanding what intelligent systems can learn and accomplish in the physical world.

For elite sports, the potential implications extend across biomechanics, skill acquisition, rehabilitation, athlete monitoring, intelligent training equipment, and facility operations.

Research from Google DeepMind has already demonstrated that AI-powered robots can learn complex sporting movements.

Developments in markerless motion capture and musculoskeletal simulation are also making detailed biomechanical analysis more accessible.

And emerging research into athlete digital twins and multimodal simulation suggests that more personalized physical models may eventually become possible.

However, the industry must distinguish between what Physical AI can demonstrate in a laboratory and what has been proven to improve outcomes in professional sports.

That distinction will be essential for teams evaluating new technologies and investors assessing sports technology startups.

I believe the most significant near-term opportunities will emerge from combining three elements:

High-quality athlete movement data + validated physical models + practitioner expertise.

Over time, these capabilities could support more sophisticated simulation, intelligent training environments, and new forms of athlete-specific decision support.

For established sports technology companies, Physical AI could become an opportunity to expand beyond data collection and visualization.

For startups, it could create entirely new product categories.

For professional teams, it could provide new ways to investigate human movement and evaluate training interventions.

My prediction for the next 5–10 years

We will see growing collaboration between Physical AI companies, robotics laboratories, universities, biomechanics specialists, and professional sports organizations.

I expect progress to begin with narrowly defined applications where accuracy and practical value can be measured, before expanding toward more ambitious athlete simulation and adaptive training systems.

The biggest winners may not be the companies building the most sophisticated robots.

They may be the companies that successfully connect advanced physical modeling with the real-world needs of coaches, sports scientists, medical professionals, and athletes.

The next chapter of AI in elite sports may not simply be about understanding athlete data. It may be about understanding, simulating, and intelligently interacting with human movement itself.

And that could fundamentally change the future of sports performance technology.

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Dear Colleague,

We are excited to announce that LightBack is the latest sports technology startup confirmed to present at our upcoming Upside VIP Lunch during the 2026 PSPA Conference in Atlanta!

⚽ Upside VIP Lunch
📅 December 18, 2026 | 12:00 PM – 2:30 PM
📍 US Soccer HQ, Atlanta, Georgia

The event will bring together approximately 250 leading MLS and NWSL practitioners and decision-makers, including Performance Directors, Heads of Athletic Therapy, Directors of Rehabilitation, Sports Scientists, and representatives from clubs across both leagues.

Each presenting startup will have the opportunity to deliver a 15-minute presentation, showcase its technology at a dedicated booth, and participate in a speed-dating session with MLS and NWSL practitioners.

Due to high demand, we have expanded the number of presenting startups to ten. Only three presentation spots remain!

🚀 Meet Our New Presenting Startup: LightBack

LightBack is an innovative sports performance tool and methodology developed by physiotherapist and osteopath Thomas Serafin, alongside CEO Alexandre Dars, designed to maximize hip mobility, release deep gluteal tension, and optimize athletic performance and recovery.

The solution focuses on one of the key drivers of athletic performance: hip mobility and functional movement. For professional athletes, optimal hip mobility is fundamental to movement efficiency, speed, power, and career longevity.

LightBack provides performance directors, strength and conditioning coaches, physical therapists, and sports performance professionals with a fast, practical solution to unlock that mobility.

Picture: Eduardo Camavinga (Real Madrid) using the LightBack.

Its effects have been evaluated in two published, peer-reviewed randomized controlled trials (PeerJ, 2025; Physiotherapy Research International, 2026). In healthy, physically active adults, a single one-minute protocol improved posterior chain flexibility and reduced sciatic nerve stiffness, as measured by elastography.

Applications in Elite Sports

• Hip Mobility: Maximize range of motion and functional movement.

• Performance Preparation: A one-minute protocol that integrates seamlessly into warm-ups and pre-competition routines.

• Recovery: Release deep muscular tension following demanding training sessions and competitions.

• Movement Quality: Enhance mobility work within strength, conditioning, and performance programs.

• Daily Athlete Management: A fast, repeatable tool that fits into everyday performance routines.

At the upcoming Upside VIP Lunch, LightBack will introduce its technology and methodology to MLS and NWSL professionals, demonstrate its practical applications, and explore opportunities for evaluation and collaboration with professional teams.

Here is a video interview of Eduardo Camavinga (Real Madrid) who has been using LightBack as part of his weekly routine.

We look forward to seeing how LightBack’s approach can complement existing performance, mobility, and recovery protocols.

⚠️ Only Three Presentation Spots Remain

Selected sports technology vendors will have the opportunity to:

• Present directly to MLS and NWSL teams and practitioners

• Demonstrate and exhibit their technology

• Receive feedback from experienced sports performance professionals

• Participate in meaningful conversations with key decision-makers

• Explore potential pilots, partnerships and commercial opportunities

• Build relationships in an intimate, highly targeted environment

We already have 7 vendors confirmed to present so if you are Interested in the last 3 spots to present please reach out to us ASAP at julien@upsideglobal.co before the last spots are gone. We have lots of startups who are interested so we won’t be able to accommodate everyone.

Last year’s Upside VIP Dinner welcomed more than 50 practitioners representing over 20 MLS clubs.

You can view the recap and recorded panel discussions and presentations here:

🚀 COMING IN Q1 2027: UPSIDE SPORTS TECH INVESTMENT VIP DINNER — NYC!

Upside is also planning an exclusive Sports Tech Investment VIP Dinner in New York City in Q1 2027!

The goal? Bring together leading investors, sports team owners, executives, and innovative startup founders for an evening of investment opportunities, meaningful connections, and networking.

📍 Location: An exclusive private club in NYC
📅 Date: Q1 2027 (TBA)
👥 50 top executives, including Top sports tech VCs, team owners, sports executives, and founders
🚀 8 selected sports tech startups will have the opportunity to pitch directly to investors
🤝 Networking with key decision-makers across sports, technology, and venture capital

Our mission is simple: Connect the next generation of sports tech startups with the investors and industry leaders who can help them grow.

📩 Are you a sports tech startup looking to raise capital?

We’re now welcoming expressions of interest from startups interested in pitching at the event.

Email julien@upsideglobal.co to learn more and express your interest.

More details coming soon!

📅 What’s Next for Upside

🇫🇷 Upside Tech Summit—France
📅 2nd half of 2027
📍 France

We are planning to host this summit at a major stadium, bringing together leading organizations from Ligue 1, the Premier League, LaLiga, international rugby, basketball, the NBA, MLS, the NFL and other elite sports.

We are also developing additional Upside VIP events with major leagues, teams, VCs across the United States and Europe in 2026 and 2027.

Interested in attending, speaking, presenting, exhibiting or sponsoring an upcoming Upside event? Contact me at julien@upsideglobal.co.

Best,

Julien

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This week we have the honor to interview again a group of experts in thermography to discuss the best practices, latest trends and innovation.

• Mauricio Elizondo, Director of Sports Medicine, Austin FC (MLS).

• Meshari Alwashmi, CEO, AmplifAI Health.

• Chris Stackpole, VP Performance, New Jersey Devils (NHL).

• Eric Roman, Head Athletic Trainer, Sporting JAX.

Here are the topics that we covered during the video interview:

• Q1. Best practices: How should teams actually use thermography? For teams using or considering thermography, what does best practice look like? When should athletes be scanned, how frequently, and how can it realistically fit into the daily workflow of an NHL or MLS , or USL performance department?

• Q2. From thermal asymmetry to an actual decision: When you identify a temperature difference or asymmetry, how do you determine whether it is meaningful? How should thermography be combined with GPS, force plates, workload, medical assessments, wellness data and other information to make better decisions?

• Q3. Injury risk and the limits of thermography: What can thermography legitimately tell practitioners today about injury risk, inflammation and recovery—and what can’t it tell them? How should teams think about claims around injury prediction?

• Q4. What are teams learning today? From what you’re seeing in elite sports today, where is thermography providing the most value? Are there particular injuries, body areas, athlete populations or situations where you’ve found thermal imaging especially useful?

• Q5. The future: AI + thermography + multimodal data: Looking 3–5 years ahead, how could AI and thermography evolve together? Could thermal data eventually be combined with workload, movement, sleep, biomarkers and other athlete data to identify changes earlier and potentially help practitioners intervene before a problem becomes an injury?

You can watch the video interview below by clicking on the Youtube link. You can also listen to the audio interview by clicking on the link at the top of the page:

Here are some of the best quotes of our conversation with Chris, Mauricio, Meshari and Eric:

Q1. Best practices: How should teams actually use thermography?

Chris Stackpole — New Jersey Devils (NHL)

“With our NHL schedule and the frequency of games, we’ve found two different pathways for using thermography. On the rehabilitation side, we use it with players who are out for prolonged periods to track their progression back to sport. For healthy players, once or twice a week is probably the maximum we can realistically manage. We try to use the days between games, particularly after days off, to assess players in a standardized way and potentially guide what we’re doing. The challenge is fitting it into an extremely demanding schedule”.

Mauricio Elizondo — Austin FC (MLS)

“For long-term rehabilitation, we can use thermography daily to see how tissue temperature evolves and modify interventions when needed. For team monitoring, we like to scan around match day minus four, approximately 60 hours after the previous game, to understand the player’s response and establish a baseline. If something appears outside that player’s normal profile, we may reassess on match day minus two or minus one to determine whether another intervention is needed”.

Eric Roman — Sporting JAX (USL)

“We’re implementing thermography this year and having players scan daily before training. That allows us to track changes from day to day and understand how each individual responds. Looking ahead, we’re considering scanning both before and after training to better understand the impact of each session on the athlete”.

Meshari Alwashmi — AmplifAI Health

“When we built our thermography solution, we wanted it to fit into the team’s existing workflow rather than force teams to change their routines. That’s why we made it self-operated. Players can take their own images without requiring a staff member to spend time scanning every athlete. The objective is to make thermal monitoring practical and consistent, even when athletes are coming into the facility at different times”.

Recommendations for teams

1. Adapt scanning frequency to the competition schedule: NHL teams may prioritize 1–2 scans per week, while other organizations may implement daily monitoring.

2. Prioritize rehabilitation monitoring: Use repeated scans to track individual tissue-temperature changes during recovery.

3. Standardize scanning conditions: Maintain consistent timing, positioning and environmental conditions.

4. Minimize workflow disruption: Integrate scanning into existing pre-training or athlete-monitoring routines.

Q2. From thermal asymmetry to an actual decision

Chris Stackpole — New Jersey Devils

“The longitudinal data is the most impactful because tissue temperatures change daily. One interesting thing we discovered when combining thermography with groin strength testing was that the hotter side wasn’t necessarily the weaker side. Sometimes the hotter side was actually stronger, while the opposite side showed a deficit on our force-frame testing. That suggested the stronger side might be compensating and taking on more load. We were able to modify our interventions to address the weaker side while also supporting the side carrying the additional workload”.

Mauricio Elizondo — Austin FC

“The thermal image gives you information, but you need to add context. Sometimes a player has tightness in one adductor, but the opposite side appears hotter. That could indicate fatigue or compensation, and it changes how you approach treatment and workload. If thermography flags a hamstring, Nordic testing shows weakness and the player has just completed a demanding game, you now have several indicators pointing toward the need for further investigation. An asymmetry doesn’t automatically mean there’s an injury. It tells you to look deeper”.

Eric Roman — Sporting JAX

“If thermography flags an asymmetry, you really have to consider everything else. For players returning from surgery or previous injuries, certain areas may show increased temperature after harder sessions. We combine thermography with jump testing, squeeze testing and clinical assessments. If multiple measures are showing abnormalities, that’s when we investigate further. But sometimes we know a particular athlete will have a thermal response in a certain area, so we have to interpret that in context rather than reacting to every change”.

Meshari Alwashmi — AmplifAI Health

“Thermography gives you a signal, and then you need to investigate what that signal means. That’s why we’ve integrated with VALD and wearables such as Oura, Apple and WHOOP. If an athlete isn’t sleeping well, has significant thermal asymmetry and performs poorly on a strength assessment, those are three different signals suggesting something deserves attention. The objective is to bring those signals together and use AI to help practitioners identify potential concerns earlier and make better-informed decisions”.

Recommendations for teams

1. Establish individual thermal baselines: Interpret changes against each athlete’s historical profile rather than relying only on group averages.

2. Triangulate multiple datasets: Combine thermography with force plates, GPS, strength testing, wellness and medical assessments.

3. Investigate rather than assume: A hotter area may reflect compensation, previous injury or normal physiological variation.

4. Create a decision-making protocol: Define when a thermal flag should trigger additional assessment, athlete communication or workload modification.

Q3. Injury risk and the limits of thermography

Chris Stackpole — New Jersey Devils

“Thermography requires a dedicated process. You need athletes to buy into scanning, you need accurate images, and someone has to interpret the information and decide what to do with it. There are so many factors involved in why athletes get injured that we cannot control. What thermography does well is provide another conversation point about how someone is doing without requiring them to jump, sprint or perform another physical test. But it doesn’t tell you exactly what intervention to make. You still need professional judgment, and there’s noise in the data that you have to work through”.

Mauricio Elizondo — Austin FC

“Thermography is a good tool to add to injury prevention and athlete monitoring, but you can’t simply tell a coach that a player is unavailable because his hamstring is hot. There’s a much bigger assessment process involved. AI interpretation also has limitations, and thermal changes need to be considered alongside everything else we know about the athlete. We need more research, but I believe there’s enough evidence to justify investigating thermography as another monitoring variable”.

Eric Roman — Sporting JAX

“You definitely have to position athletes correctly when capturing thermal images, especially when AI is interpreting them. If the athlete turns slightly or isn’t positioned consistently, the image and the resulting interpretation can change. That’s important when you’re comparing images over time. You need to make sure you’re actually measuring the same areas under similar conditions”.

Meshari Alwashmi — AmplifAI Health

“One limitation is the time required to capture images, particularly when a dedicated practitioner has to perform every scan. We’ve addressed that by developing a self-operated system and using AI on the device to help ensure athletes are positioned correctly before an image is captured. The objective is to improve consistency, reduce the workload on practitioners and allow athletes to participate more actively in their rehabilitation and monitoring”.

Recommendations for teams

1. Avoid injury-prediction claims: Treat thermography as an additional monitoring signal, not a standalone method of predicting injuries.

2. Maintain clinical oversight: Thermal abnormalities should prompt further assessment rather than automatic restrictions.

3. Control measurement variability: Standardize athlete positioning, room temperature, timing and pre-scan activities.

4. Support further research: More sport-specific studies, particularly in hockey, are needed to establish practical applications and limitations.

Q4. What are teams learning today?

Mauricio Elizondo — Austin FC

“The biggest value I’ve seen is during rehabilitation, particularly with acute injuries. We can track how the temperature of a specific body part changes over time. It doesn’t necessarily guide the entire rehabilitation process, but it often correlates with how the athlete is feeling. We’ve observed temperature decreases following acute injuries, followed by changes as the athlete recovers. We’ve also monitored temperature changes following PRP injections. For me, the most powerful application so far is one-to-one rehabilitation monitoring, where you can track the same tissue over time and compare those changes with symptoms and clinical progress”.

Chris Stackpole — New Jersey Devils

“We had a goaltender with a knee issue where thermography allowed us to see a very localized area of concern. Following an injection treatment, we observed the tissue temperature returning toward its normal baseline as the player’s pain decreased significantly. Being able to show the athlete those changes was valuable. It gives you another objective piece of information to discuss alongside how they’re feeling and progressing through treatment”.

Meshari Alwashmi — AmplifAI Health

“There are still many interesting thermography applications that haven’t been fully explored. One area is understanding how specific interventions, whether injections, acupuncture, heat, cold or exercises, influence tissue temperature. We’ve developed a feature that allows practitioners to compare images before and after an intervention and track the changes over time. The goal is to help teams better understand how athletes respond to different treatments”.

Recommendations for teams

1. Focus on rehabilitation use cases: Prioritize monitoring athletes recovering from acute injuries, surgery or prolonged absence.

2. Track responses to interventions: Compare thermal images before and after treatment while also assessing symptoms and function.

3. Monitor sport-specific body areas: Consider adductors, hamstrings and other areas exposed to high loads, while accounting for individual movement demands.

4. Use thermal imaging to improve athlete communication: Show athletes changes over time alongside other rehabilitation measures.

Q5. The future: AI + thermography + multimodal data

Mauricio Elizondo — Austin FC

“In the future, I think we’ll see much deeper analysis, potentially down to individual muscles. Maybe cameras will eventually differentiate between the adductor longus and adductor brevis rather than looking at a broader body region. I’d also like to see research examining whether athletes with repeated hamstring injuries share certain thermal profiles. We’ve been collecting data for several years, and the next step is understanding whether there are meaningful relationships between those profiles and injury histories. But we’re still in the data-collection phase, and it’s too early to know whether workload information can reliably explain or predict those temperature changes”.

Eric Roman — Sporting JAX

“I think the future comes back to consistency. The more scans you collect, the more data points AI has to learn from. It will be interesting to go back retrospectively and examine what athletes’ thermal images looked like before an injury occurred. If we can identify consistent trends in those historical datasets, that could help develop better AI models. But the quality and consistency of the data will be critical for making those interpretations meaningful”.

Meshari Alwashmi — AmplifAI Health

“We’re really just scratching the surface when it comes to AI and thermography. We’ve already integrated VALD data and wearable information, and we’re working on bringing those signals together consistently. Our goal is to make it easy for teams to collect different data sources in one place and understand what the results mean. As we continue developing these capabilities, the opportunity is to support more personalized treatment decisions, helping practitioners provide the right intervention to the right athlete at the right time. But consistency and data quality are essential if we want these systems to support meaningful decisions”.

Recommendations for teams

1. Build longitudinal datasets now: Consistent thermal monitoring creates the historical data needed for future AI analysis.

2. Integrate complementary technologies: Connect thermography with workload, force plates, movement, sleep and other athlete-monitoring systems.

3. Explore retrospective injury analysis: Investigate whether meaningful thermal patterns existed before previously documented injuries.

4. Validate AI-generated insights: Evaluate new algorithms against clinical findings and athlete outcomes before using them to guide decisions.

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Today we have the honor of interviewing a group of NBA sports performance experts.

• Bill Burgos is an experienced NBA Strength & Conditioning coach. He has worked for many NBA teams (Orlando Magic, NY Knicks, Timberwolves..). He also worked in the MiLB with the Pittsburgh pirates. He is also the CEO of LONU a next generation AI based nutrition platform.

• Derek Millender, the head S&C coach of the Cleveland Cavaliers, a top NBA team.

📝Show Notes: Through this interview, we touched on the following questions and topics:

• Q1. With training camp already done, what should an ideal final few weeks of the offseason look like for an NBA player—physically, technically, and mentally?

• Q2. Many players work with private coaches during the offseason. What does strong collaboration between a player’s private coach and NBA team staff look like, and where can problems arise?

• Q3. What are the biggest offseason mistakes you see players make—such as overtraining, playing too much live basketball, chasing social-media workouts, or neglecting recovery?

• Q4. How should offseason preparation be individualized based on a player’s age, injury history, role, expected minutes, and the way their team plans to use them?

• Q5. When you look at players who consistently have successful, healthy seasons, what habits or decisions during the offseason separate them from everyone else?

• Q6. If you could give every NBA player one piece of advice before the season begins, what would it be?

You can also watch the full video interview below:

Here are some of the best quotes of our conversation with them:

Q1. What should the ideal final weeks of offseason preparation look like?

Derek Millender — Cleveland Cavaliers

For me, it’s definitely an interdepartmental focus. As a strength and conditioning coach, I’m collaborating with our sports science group, reviewing baseline testing and analyzing how players are trending. If it’s a returning player, how do they compare to where they were last year? Do they have the capacity they need? We’re also communicating with basketball coaches to understand whether there are conditioning, agility or other physical limitations affecting their performance. Ultimately, all that feedback needs to get back to the player so they understand exactly what we’re working on and why.

Bill Burgos — LONU

Training camp in the NBA is quite short. It’s enough to expose players to high loads, but I don’t think it’s enough to create significant physical changes. Some guys come prepared and some don’t. It’s our job to develop programs that mitigate those challenges and reduce injury risks. That’s why, during the offseason, we travel and stay connected with players to make sure they’re prepared. Strength coaches, physical therapists, athletic trainers, sports scientists and dietitians all collaborate to make sure what players are doing during the offseason prepares them for training camp.

Recommendations for NBA teams

1. Establish offseason readiness benchmarks: Compare preseason testing with historical performance data to identify physical limitations and areas requiring attention.

2. Create integrated performance plans: Align strength coaches, sports scientists, medical staff and basketball coaches around shared player objectives.

3. Monitor workload progression: Track training loads, particularly for players with previous injuries or lower training capacity.

4. Communicate individualized priorities: Give each player a clear understanding of their development goals for the opening weeks of the season.

Q2. How should private coaches and NBA team staff collaborate?

Bill Burgos — LONU

When I’m working privately with a player, I’m there all the time. I’m traveling with him, so I get to see what’s happening and can make adjustments and progressions throughout the offseason. When collaborating with an NBA team’s staff, I just need to know their goals and what they expect from the player. They have access to testing and resources, like force plates, that I might not have. All that information is beneficial for programming. I’m really trying to be an extension of the performance staff of whichever team the player is with. At the end of the day, we’re all trying to help the player succeed.

Derek Millender — Cleveland Cavaliers

It’s great when you have harmony. Players have the opportunity to choose who they want to work with during the offseason, and I’m interested in understanding why they chose that professional. Ideally, we have conversations with that person throughout the summer, or we visit the player and observe how they’re training. I think it’s important that team strength coaches support the professionals these athletes choose and work together. If they don’t have access to certain testing equipment, we can bring it or share specific goals. Different coaches have different experiences, and there’s always something we can learn from them.

Recommendations for NBA teams

1. Establish regular communication with private coaches: Schedule offseason check-ins to align training objectives and monitor player progress.

2. Share relevant performance data: Provide private trainers with testing results, injury considerations and development priorities, with appropriate player consent.

3. Visit players during the offseason: Observe their training environments and evaluate how private programs complement team objectives.

4. Build collaborative relationships: Treat private coaches as potential partners rather than competitors, while maintaining clear responsibilities.

Q3. What are the biggest offseason mistakes NBA players make?

Bill Burgos — LONU

I personally think the biggest issue is structure. I’m used to working with periodized programs, and it takes time to gain power, strength and other physical qualities. If there’s no structure and players keep traveling, getting tired and recovering from travel, suddenly three or four weeks have gone by. Then it’s August and they’re trying to rush everything. I think that’s where injuries can happen. If players maximize their time and stay consistent, even dedicating a few hours in the morning to training, it can make a significant difference. If I had to sum it all up in one word, it would be structure.

Derek Millender — Cleveland Cavaliers

During the season, everything is organized for the players. The court is available, the weight room is there, the chef is at the facility and recovery services are scheduled. During the offseason, players have to think ahead. If you’re going on vacation for ten days, have you planned where you’re going to do your basketball work? Are you taking a deload? What equipment is available at your hotel? A lot of younger players aren’t used to organizing those things themselves. We’re not saying vacations are bad, but you need to plan ahead so you can maintain your training routine and the progress you’ve made.

Recommendations for NBA teams

1. Provide structured offseason programs: Develop periodized training plans with clear objectives, progression and recovery periods.

2. Support players during travel: Help identify suitable training facilities and adapt programs based on available equipment.

3. Monitor training consistency: Maintain regular communication to identify missed sessions, disrupted routines or sudden workload increases.

4. Educate younger players: Teach offseason planning, training logistics and recovery management to encourage greater independence.

Q4. How should offseason preparation be individualized?

Derek Millender — Cleveland Cavaliers

It starts with a discussion with the player. At the end of the season, we have exit meetings where we reflect on what went well and what needs improvement. Those conversations lay the foundation for the offseason program. We also need to understand what’s happening in the player’s personal life. Maybe they’re getting married, traveling or playing for their national team. A young player preparing for Summer League will have a completely different program from a veteran who’s been in the league for six or seven years. You have to consider their injury history, goals, culture and circumstances. There’s not just one way to approach it. The program needs to be built around the individual player.

Recommendations for NBA teams

1. Conduct comprehensive exit meetings: Review each player’s performance, injury history, development needs and personal objectives.

2. Differentiate programs by player profile: Adjust preparation based on career stage, expected basketball demands and competition schedules.

3. Integrate injury-specific monitoring: Reassess previously injured areas throughout the offseason and preseason to guide training progression.

4. Account for personal circumstances: Adapt training schedules around international competition, travel and other commitments.

Q5. What separates players who consistently have successful, healthy NBA seasons?

Derek Millender — Cleveland Cavaliers

Players have to make that software upgrade every offseason. Just like when you update software to fix bugs and improve performance, athletes need to identify what they can improve and commit to doing the work. Maybe a coach tells you your defensive capacity isn’t good enough or your second and third efforts need improvement. Is it a basketball understanding issue or a conditioning issue? You have to listen to that feedback and make the decision to improve. The other thing is that successful players genuinely love basketball. When you combine that passion with a willingness to improve their physical limitations, nutrition and habits, you have an athlete who can continue getting better.

Recommendations for NBA teams

1. Promote year-round consistency: Encourage sustainable training habits rather than isolated periods of excessive intensity.

2. Educate players on workload management: Help athletes understand when to increase intensity, reduce loads and prioritize recovery.

3. Build individual development plans: Identify specific physical and technical weaknesses after each season and establish measurable improvement goals.

4. Strengthen athlete education: Teach players how nutrition, recovery, training and daily habits influence performance and career longevity.

Q6. What’s the one piece of advice every NBA player should hear?

Bill Burgos — LONU

I’ve always said to make sure you’re doing the right thing at the right time, no matter where you are. That’s been my biggest message. A lot of players work with outside trainers and the training itself might be good, but sometimes it’s happening at the wrong time. They might peak too soon or follow a program that doesn’t match where they should be in their preparation. It’s not just about training hard or choosing the right exercises. It’s about understanding when to do certain things so you’re ready when it matters most.

Derek Millender — Cleveland Cavaliers

The few things you can control, make sure you control them. Being on time, eating the quality food the team provides, your attitude and the energy you bring to your teammates every day. Sometimes players get frustrated because they’re doing everything right but aren’t getting the playing time they expected. You can’t always control that. But you can control how you show up and how you support your teammates. Even if you’re not playing, find a way to bring positive energy and help the team win. When your opportunity comes again, you need to be physically and mentally ready for it.

Recommendations for NBA teams

1. Align training with the competitive calendar: Ensure strength, conditioning and recovery programs reflect each stage of the season.

2. Develop player accountability: Reinforce consistent habits around nutrition, punctuality, preparation and professionalism.

3. Support psychological readiness: Help players manage frustration, changing roles and uncertainty around playing time.

4. Maintain readiness for non-rotation players: Implement individualized training and conditioning plans so athletes remain prepared when opportunities arise.

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Another exciting week ahead at the intersection of elite sports, sports science, artificial intelligence, technology, investment, and business!

Next week, we’ll host two Upside group podcasts featuring leading experts from the NBA, NHL, MLS, and sports technology industry. We’ll also follow major sports industry conferences, technology earnings, AI product developments, and emerging opportunities for sports-tech startups.

🏆 One of the biggest highlights will be Monday’s 2026 Ballon d’Or ceremony in London, where the world’s top soccer players will be recognized. Harry Kane, Lamine Yamal, and Kylian Mbappé are among the leading contenders for the men’s award.

We’ll also announce one new sports-tech vendor joining our Upside VIP Lunch in Atlanta on December 18! We’re excited to introduce another innovative company to our growing lineup of presenting vendors.

With the NBA regular season underway and AI continuing to reshape multiple industries, there will be plenty to discuss.

At Upside, our focus remains on identifying emerging trends, best practices, promising innovations, and practical applications that can help professional sports organizations improve performance, rehabilitation, athlete health, and operational efficiency.

Here’s what we’ll be following next week.

🏟️ MAIN SPORTS INDUSTRY CONFERENCES

Two sports-focused conferences are on our radar next week, bringing together executives, technology providers, event organizers, and commercial partners.

🏟️ TEAMS Conference + Expo 2026 — Birmingham, Alabama | October 26–29

🌐 Official Website

TEAMS is a major conference dedicated to sports events, sports tourism, and the business of sports.

The event attracts executives from sports organizations, event managers, sponsors, sports commissions, and technology providers.

Discussions cover sports-event development, technology, digital platforms, commercial partnerships, and strategies for improving event operations.

Upside Take: While TEAMS focuses more on sports business than athlete performance, AI, automation, and data analytics are increasingly influencing how sports organizations manage events and commercial operations.

What to watch: Sports-event technology, digital platforms, AI-powered automation, sponsorship technology, and partnerships.

🚀 Sports Innovation Forum — The Woodlands, Texas | October 28–30

🌐 Official Website

The Sports Innovation Forum focuses on emerging trends in sports marketing, events, digital engagement, and business operations.

The event provides opportunities for sports industry professionals to exchange ideas and explore technologies that could transform the sports business ecosystem.

Upside Take: Innovation in sports extends well beyond athlete performance.

AI, digital platforms, fan engagement technologies, and data analytics are creating opportunities for startups to develop new products and business models.

What to watch: Sports innovation, AI applications, fan engagement, digital experiences, and emerging technology partnerships.

🏆 Ballon d’Or 2026 — Who Will Be Crowned the World’s Best Soccer Player?

📅 Monday, October 26, 2026
📍 London Palladium, London, UK
🕒 8 PM London time / 4 PM ET

The prestigious Ballon d’Or ceremony takes place Monday, celebrating the world’s best soccer players and marking the award’s 70th anniversary. For the first time, the ceremony will be held in London rather than Paris.

Who is likely to win?

The men’s competition is shaping up to be a fascinating battle between two leading candidates:

• Harry Kane (Bayern Munich / England): Currently the betting favorite after an outstanding season, scoring 61 goals in 51 games for Bayern Munich and helping England reach the World Cup semifinals.

• Lamine Yamal (FC Barcelona / Spain): Kane’s closest challenger following his performances for Barcelona and Spain’s World Cup triumph.

• Kylian Mbappé (Real Madrid / France): Another contender following an impressive individual season and his record-breaking World Cup performances.

What do the polls and betting markets say?

According to betting odds reported ahead of the ceremony:

These are bookmaker-implied probabilities, not official voting percentages, and they include the bookmaker’s margin.

A reported survey by The Athletic of 100 football professionals—including coaches, executives, scouts, and players—also ranked Kane first with 1,103 points, ahead of Yamal (991) and Mbappé (728).

Women’s Ballon d’Or

Alexia Putellas is considered the leading favorite for the women’s award, with Ewa Pajor and defending winner Aitana Bonmatí among her closest challengers.

Why it matters beyond soccer

The Ballon d’Or is more than an individual sporting award. It can influence players’ commercial value, sponsorship opportunities, personal brands, and the global visibility of their clubs.

It also raises an interesting question about how we evaluate elite performance. While goals, assists, trophies, and individual achievements remain central, advanced analytics, tracking data, and AI are increasingly providing additional ways to assess player contributions.

Upside Take: As soccer becomes more data-driven, it will be interesting to see how advanced analytics influence player evaluation, scouting, and eventually the way individual excellence is recognized.

Our prediction: Harry Kane is the favorite, but Lamine Yamal could still create an upset.

Who do you think deserves the 2026 Ballon d’Or?

📈 MAIN EARNINGS TO WATCH

Next week will be important for technology and financial markets, with several major companies scheduled to report quarterly earnings.

For sports-tech startups and investors, these announcements provide useful signals about AI investment, cloud infrastructure, healthcare innovation, and the broader technology economy.

💻 Microsoft — October 28

Microsoft’s earnings will provide insights into Azure cloud growth, Copilot adoption, enterprise AI, and AI infrastructure spending.

Upside Take: Microsoft’s AI and cloud technologies are increasingly relevant to companies developing sophisticated analytics, automation, and data integration solutions.

For professional teams, enterprise AI could eventually help connect information from athlete management systems, medical departments, performance monitoring platforms, and scouting tools.

What to watch: Azure, Copilot, AI infrastructure, enterprise adoption, and cloud profitability.

🤖 Alphabet / Google — October 28

Alphabet’s results will highlight developments in Google Cloud, Gemini, AI infrastructure, and the company’s broader AI strategy.

Upside Take: Google’s research through DeepMind is particularly relevant to the future of Physical AI, computer vision, robotics, and intelligent simulation.

These technologies could eventually support new applications in biomechanics, skill acquisition, athlete digital twins, and intelligent training environments.

What to watch: Gemini, Google Cloud, DeepMind, Physical AI, and AI commercialization.

📦 Amazon — October 29

Amazon’s earnings will provide insights into AWS, AI infrastructure investment, automation, and robotics.

Upside Take: Cloud computing is a critical component of the modern sports technology ecosystem.

Many startups rely on cloud infrastructure to process data, develop AI models, and deliver analytics to professional teams.

Advances in robotics and computer vision could also influence future training and rehabilitation technologies.

What to watch: AWS, AI investment, cloud demand, robotics, and automation.

🏥 Eli Lilly — October 29

Eli Lilly’s earnings will provide updates on pharmaceutical research, metabolic health, and commercial growth.

Upside Take: The convergence of healthcare and sports performance continues to create opportunities for innovation.

Developments in medical science, diagnostics, and physiological monitoring may influence how athletes are assessed and supported in the future.

What to watch: Healthcare innovation, metabolic health, research investment, and clinical development.

💳 Visa — October 27

Visa’s earnings will provide insights into digital payments, consumer spending, and financial technology.

Upside Take: Financial technology continues to transform ticketing, sponsorships, fan engagement, and commercial operations across professional sports.

What to watch: Digital transactions, payment innovation, consumer spending, and commercial trends.

The Bigger Question for Sports-Tech Startups

Major technology companies continue investing billions of dollars in AI infrastructure and new products.

But investors increasingly want to understand how these investments translate into revenue, productivity, and profitability.

For sports-tech startups, the lesson is clear:

Developing innovative technology is important, but demonstrating measurable value and a sustainable business model is just as critical.

🚀 PRODUCT & TECHNOLOGY DEVELOPMENTS TO WATCH

Several major technology events next week could introduce capabilities with potential implications for sports technology companies.

🍎 Apple — Computing & AI Developments

We’ll be watching for developments in Apple’s computing hardware and AI capabilities.

Upside Take: Improvements in processing power, AI capabilities, and device integration could benefit sports technology companies developing video analysis, biomechanics, and computer vision applications.

More powerful devices may enable faster processing of movement data and more sophisticated AI applications.

What to watch: Computing hardware, AI processing, device performance, and developer opportunities.

🤖 Oracle — AI World

Oracle AI World will feature developments in enterprise AI, cloud infrastructure, automation, and data management.

Upside Take: One of the biggest opportunities for AI in professional sports is helping organizations connect data across departments.

Teams collect large amounts of information from GPS systems, force plates, wearables, medical assessments, and athlete management systems.

AI-powered tools could help practitioners analyze these different data sources more efficiently.

What to watch: AI agents, enterprise automation, cloud platforms, and data integration.

💻 GitHub — GitHub Universe

GitHub Universe will focus on AI-assisted software development, coding agents, and developer productivity.

Upside Take: AI-powered development tools could help early-stage sports technology startups accelerate product development and reduce engineering costs.

For companies operating with limited resources, these tools could become an important competitive advantage.

What to watch: AI coding agents, software automation, developer productivity, and new platform capabilities.

⌚ Wearables, Biomechanics & Athlete Monitoring

We’ll also continue following innovations across several sports performance technology categories:

• Advanced GPS and athlete tracking.

• Markerless motion capture and biomechanics.

• Continuous physiological monitoring.

• Sleep and recovery technologies.

• AI-powered athlete management systems.

• Intelligent training equipment and Physical AI.

Upside Take: The next generation of sports technology will increasingly combine multiple data sources to provide a more comprehensive understanding of athlete performance.

However, collecting more data is not necessarily better.

The real value comes from delivering accurate, validated, and actionable insights that help practitioners make better decisions.

🚀 UPSIDE VIP LUNCH — ATLANTA, DECEMBER 18

We’ll also continue preparations for our upcoming Upside VIP Lunch at the new U.S. Soccer Headquarters in Atlanta.

📅 December 18, 2026 | 12:00–2:30 PM

📍 U.S. Soccer Headquarters, Atlanta, Georgia

👥 Approximately 250 MLS and NWSL practitioners and decision-makers expected.

The event will bring together performance directors, athletic trainers, rehabilitation specialists, sports scientists, and innovative sports technology companies.

Selected startups will have opportunities to present their technologies, participate in speed-dating sessions with teams, demonstrate their products, and network directly with decision-makers.

🚀 New Vendor Announcement Coming Next Week!

Next week, we’ll be announcing one additional sports-tech vendor confirmed to present at our Upside VIP Lunch in Atlanta!

We already have 7 startups confirmed to present. We only have 3 spots left for startups to present so if you are interested in presenting please email us at julien@upsideglobal.so before we are sold out.

We’re excited to introduce this company to our network and share more about its technology, innovative approach, and potential applications in elite sports.

The new vendor will join our growing lineup of companies showcasing technologies and solutions to MLS and NWSL practitioners.

Stay tuned for the official announcement!

Upside Take

One of the biggest challenges facing sports-tech startups is gaining access to professional teams and the practitioners responsible for evaluating new technologies.

Our goal is to create an environment where innovative companies can showcase their products, receive meaningful feedback, and develop relationships with leading sports organizations.

By bringing startups and practitioners together, we hope to accelerate innovation and help teams identify technologies that address real performance, rehabilitation, and sports medicine challenges.

🎙️ AT UPSIDE NEXT WEEK — TWO GROUP PODCASTS

🏀 NBA Group Podcast — Performance, Recovery & Innovation

Next week, we’re excited to welcome two experienced NBA sports performance experts:

• Bill Burgos: Former NBA Strength & Conditioning Coach with experience at the Orlando Magic, New York Knicks, Minnesota Timberwolves, and Pittsburgh Pirates’ minor league organization. He is also CEO of LONU, an AI-powered nutrition platform.

• Derek Millender: Head Strength & Conditioning Coach of the Cleveland Cavaliers.

🌡️ Group Podcast — The Future of Thermography in Elite Sports

We’ll also bring together four experts to discuss best practices, emerging research, and innovation in thermography.

Our guests:

• Mauricio Elizondo: Director of Sports Medicine, Austin FC (MLS).

• Meshari Alwashmi: CEO, AmplifAI Health.

• Chris Stackpole: VP Performance, New Jersey Devils (NHL).

• Eric Roman: Head Athletic Trainer, Sporting JAX.

🔮 THE BIG PICTURE — FIVE TRENDS WE’RE WATCHING

Several important themes stand out heading into next week.

1. AI investment and commercialization

Major technology companies continue investing heavily in AI infrastructure, but investors increasingly expect measurable returns.

For sports-tech startups, demonstrating a clear return on investment will become increasingly important.

2. Athlete health remains a major innovation opportunity

Technologies focused on recovery, rehabilitation, biomechanics, and athlete monitoring continue attracting interest.

However, accuracy, scientific evidence, and practical usefulness remain critical.

3. Wearables, biomechanics, and healthcare technologies are converging

The boundaries between consumer health, medical devices, and professional sports performance technologies continue to blur.

This convergence could create opportunities for startups, investors, and sports organizations.

4. Sports technology companies need more than great products

Developing innovative technology is only the first step.

Successful startups must demonstrate credibility, validate their solutions, build strong relationships with practitioners, and provide excellent customer support.

5. Practitioners remain at the center of innovation

At Upside, we believe the most successful technologies are developed through close collaboration with the people who use them every day.

That’s why our upcoming NBA and thermography group podcasts are particularly exciting.

They provide opportunities to hear directly from practitioners about their challenges, best practices, and experiences with emerging technologies.

CONCLUSION — CONNECTING INNOVATION WITH REAL-WORLD SPORTS PERFORMANCE

Next week highlights what makes the sports industry so exciting: world-class competition, emerging technologies, growing commercial opportunities, and the people driving innovation behind the scenes.

🏆 The Ballon d’Or will celebrate individual excellence in global soccer, while also raising interesting questions about how we evaluate player performance and the increasing influence of data and analytics.

⚽ Our preparations for the Upside VIP Lunch in Atlanta continue, with seven startups confirmed and three remaining opportunities for companies to showcase their technologies to MLS and NWSL decision-makers.

🎙️ Through our upcoming practitioner discussions and podcasts, we’ll continue exploring the challenges teams face in training, athlete health, rehabilitation, recovery, and technology adoption.

At Upside, our goal remains the same: connecting teams, practitioners, startups, and investors while identifying technologies and ideas that can make a meaningful difference in elite sports.

We’re looking forward to another exciting week of conversations, innovation, and opportunities across the global sports ecosystem.

What are you most looking forward to next week? Who do you think will win the 2026 Ballon d’Or?

Stay tuned!

Best,

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Upside Weekend Analysis | October 24–25, 2026

Three major events. Three different business models. One common theme: technology is reshaping elite sports.

Introduction

This weekend, three major sporting events will capture the attention of millions of fans around the world: the NFL’s historic first regular-season game in Paris, Game 4 of the WNBA Finals, and the Formula 1 United States Grand Prix in Austin, Texas.

While these events represent very different sports, they share several important characteristics. All three are becoming increasingly international, attracting investment, developing new commercial opportunities, and adopting advanced technologies to improve performance, athlete health, and the fan experience.

For sports executives, investors, technology companies, and performance practitioners, there is much more to watch than the final scores.

The NFL’s expansion into France illustrates how professional leagues are developing new international markets. The WNBA Finals highlight the commercial growth of women’s sports and the need for more investment in female athlete performance and health. Formula 1 remains one of the most technologically sophisticated sports in the world, offering lessons in data analytics, engineering, and real-time decision-making.

At Upside, we believe these events offer a useful perspective on the future of elite sports, sports technology, and the business of sports.

NFL in Paris: A Historic Moment for American Football and International Expansion

Sunday, October 25

9:30 AM ET · Stade de France, Paris

The Pittsburgh Steelers will face the New Orleans Saints in the first NFL regular-season game ever played in France.

The game will take place at the Stade de France, one of Europe’s most recognizable sporting venues, with a capacity of approximately 80,000 spectators.

Why people should watch

1. A historic milestone for the NFL

For decades, the NFL has worked to expand its presence beyond the United States through international games, media partnerships, grassroots programs, and commercial initiatives.

The Paris game represents another major step in that strategy.

France is particularly interesting because of its strong sporting culture, large consumer market, and international visibility.

The Saints also have a natural historical connection to France through New Orleans, making this matchup an attractive opportunity for the NFL to introduce its product to French fans.

2. The economics of NFL international expansion

The NFL’s international strategy is about much more than selling tickets for one game.

It creates opportunities across several revenue streams:

• International media and broadcasting rights.

• Corporate sponsorships and partnerships.

• Merchandise and licensing.

• Ticketing, hospitality, and tourism.

• Long-term fan development and grassroots participation.

According to Associated Press reporting, approximately 70% of tickets for the Paris game were purchased locally, with roughly 20% of attendees expected to travel from the United States. The NFL also arranged free-to-air coverage in France, underscoring its ambition to develop a broader audience.

This matters because successful international expansion requires local demand rather than relying exclusively on American fans traveling overseas.

For the NFL, Paris could become an important European market alongside its established international destinations.

3. An unusual performance and recovery challenge

From a sports performance perspective, international NFL games create significant logistical and physiological challenges.

Traveling from the United States to Europe can involve changes in sleep schedules, circadian rhythms, meal timing, training routines, and recovery strategies.

Practitioners must balance travel logistics with player readiness, particularly when athletes are expected to compete at maximum intensity shortly after crossing multiple time zones.

Relevant technologies include sleep-monitoring wearables, athlete management systems, GPS tracking, physiological monitoring, and recovery assessment tools.

One particularly interesting detail this weekend is the playing surface. Preparations for the Paris game involved producing grass near Milan and installing a hybrid field at Stade de France, illustrating the engineering involved in adapting a major European venue for American football.

The impact of technology

NFL teams already operate in highly data-intensive environments, but international competition increases the importance of translating information into practical decisions.

Sleep and readiness monitoring can help staff identify changes in athletes’ routines. GPS and workload data can help coaches manage training intensity. Biomechanics and medical assessments can inform return-to-play decisions.

However, no single technology can reliably determine whether an athlete will perform well after international travel. Teams still need to interpret data alongside individual athlete responses, medical assessments, and practitioner judgment.

An additional factor: Event security and operational resilience

This year’s Paris game also comes amid reports of civil unrest and increased security measures. The NFL has continued its preparations, while some other sporting activities in Paris have been disrupted.

For league executives, the situation highlights another challenge of international expansion: ensuring that venue operations, transportation, security, and contingency planning meet the demands of a major live sporting event.

Upside Take

The NFL’s international expansion is creating new opportunities for sports technology companies specializing in sleep, recovery, athlete monitoring, travel management, and performance optimization.

As leagues schedule more international games, performance departments will increasingly need practical solutions to manage travel demands while protecting athlete readiness.

The Paris game is an opportunity to examine how teams prepare athletes for international competition—and which technologies genuinely help.

WNBA Finals: Women’s Basketball, Commercial Growth, and the Future of Female Athlete Performance

Saturday, October 24

1:00 PM ET · State Farm Arena, Atlanta

The Atlanta Dream will host the Golden State Valkyries in Game 4 of the 2026 WNBA Finals.

Atlanta enters the game with a 2–1 series lead following a commanding 97–71 victory in Game 3. Both teams are pursuing their first WNBA championship.

Why people should watch

1. A potentially defining moment in the championship series

Game 4 could dramatically change the direction of the Finals.

Atlanta has an opportunity to move within one victory of the championship, while Golden State is trying to even the series before returning home.

The matchup is particularly compelling because the teams represent two different stories: Atlanta’s pursuit of a long-awaited title and Golden State’s rapid emergence as a championship contender.

The series also showcases the growing depth and competitiveness of women’s professional basketball.

2. The economics of women’s sports are changing

The WNBA’s commercial development is one of the most important stories in professional sports.

For years, women’s sports were often evaluated primarily through traditional television audiences and sponsorship arrangements.

Today, investors and team owners increasingly recognize opportunities across franchise ownership, media rights, corporate partnerships, merchandise, premium hospitality, and direct-to-consumer engagement.

The league’s new labor agreement has also changed its financial structure. The 2026 salary cap increased substantially, from approximately $1.5 million in 2025 to $7 million in 2026, according to CBS Sports.

That represents a significant shift in how the league allocates resources to players.

But the broader economic question extends beyond compensation.

As women’s sports become more valuable, organizations will need to invest more in the infrastructure that supports elite athletes: performance departments, sports science, rehabilitation, nutrition, facilities, and medical technology.

3. Women’s sports represent an important growth market for sports technology

Historically, much of the sports performance technology industry has developed products, datasets, and research programs around male athletes.

That creates an important opportunity—and a responsibility—for companies serving women’s professional sports.

Performance technologies should account for relevant physiological, anatomical, and training differences while avoiding assumptions that every female athlete requires the same approach.

Areas of particular interest include:

• Strength and conditioning and individualized workload monitoring.

• ACL injury research, rehabilitation, and return-to-play.

• Sleep, recovery, and fatigue assessment.

• Nutrition, energy availability, and athlete health.

• Biomechanical assessment and movement analysis.

• Menstrual-cycle-related research and athlete-led symptom tracking, where clinically appropriate.

The important distinction is that a product marketed specifically to women is not automatically more scientifically valid.

Teams should expect rigorous validation, transparent limitations, and evidence that the technology supports meaningful decisions.

The impact of technology

The WNBA Finals offer a useful opportunity to examine the relationship between performance technology and athlete availability.

During a playoff series, teams must manage limited recovery time, tactical preparation, accumulated fatigue, and potentially changing player roles.

GPS and indoor tracking systems can help quantify movement demands. Force plates and biomechanical assessments may contribute information about neuromuscular function. Athlete management platforms can consolidate medical, training, and wellness information.

Computer vision and AI-powered video analysis could also help teams evaluate movement patterns and tactical performance.

However, technologies should complement—not replace—the expertise of medical and performance practitioners.

There is also a commercial technology story.

As the WNBA attracts larger audiences, teams and sponsors have opportunities to develop more sophisticated digital experiences, personalized content, fan analytics, and commercial partnerships.

Upside Take

The growth of women’s professional sports could become one of the most important catalysts for innovation in athlete health and performance technology over the next decade.

Sports technology companies that invest in research involving female athletes, build relationships with WNBA practitioners, and develop scientifically credible products may be particularly well positioned.

This is also one reason we’re excited about our planned 2027 Upside WNBA VIP Dinner in Miami, bringing together performance and medical representatives from WNBA teams to exchange best practices and explore emerging technologies.

The opportunity is not simply to sell more technology to women’s teams. It is to develop better solutions through direct collaboration with female athletes and the practitioners supporting them.

Formula 1 United States Grand Prix: The Ultimate Laboratory for Performance Technology and Data Analytics

Sunday, October 25

4:00 PM ET · Circuit of The Americas, Austin, Texas

The Formula 1 United States Grand Prix takes place this Sunday at Circuit of The Americas (COTA), one of the most recognizable tracks in North America.

The race will cover 56 laps of the 5.513-kilometer circuit. Qualifying takes place Saturday, with the Grand Prix scheduled for Sunday at 3:00 PM local time.

Why people should watch

1. An important weekend in the championship race

Formula 1 is entering a crucial stage of the season.

Young driver Kimi Antonelli arrives in Austin with a potential opportunity to secure the world championship, while competitors are looking to challenge his position.

Meanwhile, Charles Leclerc led Friday’s practice sessions, adding another interesting storyline ahead of qualifying.

Fans should watch how qualifying, tire management, race strategy, and execution influence the outcome.

Unlike many sports, Formula 1 makes the relationship between engineering, technology, human performance, and competitive results unusually visible.

2. The economics of Formula 1 extend far beyond racing

Formula 1 has evolved into a global sports and entertainment business built around multiple revenue streams.

These include broadcasting and streaming rights, race-hosting agreements, sponsorships, premium hospitality, licensing, merchandising, and commercial partnerships.

For host cities, a Grand Prix can also create demand for hotels, restaurants, transportation, entertainment, and tourism.

Austin is an example of how a sporting event can become part of a city’s broader international identity.

For corporate sponsors, Formula 1 offers a combination of global visibility, technological sophistication, premium hospitality, and access to influential commercial audiences.

The sport is particularly attractive to technology, automotive, financial services, and enterprise software companies because its competitive product is closely connected to engineering and innovation.

3. Formula 1 demonstrates the commercial value of advanced analytics

In Formula 1, small improvements can produce meaningful competitive advantages.

Teams use extensive sensor systems, simulation, engineering models, and race-strategy software to evaluate performance.

The objective is not simply to collect data. It is to make better decisions under pressure.

That is an important lesson for professional sports teams and technology startups.

A performance department with dozens of technologies is not necessarily more effective than one with fewer, better-integrated systems.

The key is understanding which information is reliable, which variables matter, and how to translate data into action.

The impact of technology

Formula 1 offers several particularly relevant technology applications.

Driver biometrics and physiological monitoring

Drivers experience significant physical and cognitive demands, including heat exposure, high gravitational forces, muscular fatigue, and sustained concentration.

Physiological monitoring and driver conditioning can help support preparation and recovery, although access to detailed individual biometric data varies by team and application.

Real-time data analytics

Cars generate large quantities of telemetry that engineers use to evaluate vehicle behavior, tire performance, mechanical systems, and race strategy.

The lesson for sports performance departments is the importance of turning complex information into timely, practical decisions.

Digital twins and simulation

Formula 1 teams rely heavily on simulation and modeling to explore different vehicle setups and race scenarios.

Similar principles could support emerging applications in sports biomechanics, training simulation, rehabilitation, and skill acquisition.

However, modeling a race car is not the same as modeling a human athlete. Biological variability, uncertainty, and the limits of current measurement systems make athlete digital twins a more complex proposition.

AI and predictive analytics

AI and machine learning can help identify patterns in large datasets, support scenario analysis, and improve engineering workflows.

In professional sports, related approaches may eventually support athlete monitoring, video analysis, training personalization, and operational planning.

The challenge remains validation: a sophisticated prediction is only valuable if it is sufficiently accurate and improves real-world decisions.

Technology is also changing how fans watch Formula 1

An especially interesting development this weekend is the evolution of F1’s U.S. broadcast experience.

Apple TV is offering coverage of the United States Grand Prix with English and Spanish commentary and access to multiple additional feeds, including driver tracking, onboard cameras, timing data, and race-position information.

This reflects a broader trend toward personalized sports broadcasting.

Instead of watching a single television feed, fans can increasingly select data-rich viewing experiences and follow the competitors or storylines that interest them most.

For sports leagues, that creates potential opportunities in audience engagement, digital subscriptions, sponsorship integration, and interactive media products.

Upside Take

Formula 1 remains one of the best examples of how engineering, data analytics, human expertise, and technology can work together to improve competitive performance.

For NBA, NFL, NHL, MLS, and other professional sports organizations, there are lessons in how F1 teams organize information, coordinate multidisciplinary staff, and make decisions under pressure.

For sports-tech startups, Formula 1 also reinforces an important principle: collecting large amounts of data is not enough.

The real competitive advantage comes from converting that data into accurate, timely, and actionable information.

The Bigger Picture: Five Trends Connecting These Events

Although the NFL, WNBA, and Formula 1 operate in different markets, their evolution highlights five important trends.

1. Sports are becoming increasingly global. The NFL’s Paris debut and Formula 1’s international calendar demonstrate how leagues use live events to reach new fans, attract sponsors, and expand media opportunities.

2. Women’s sports represent a significant commercial and innovation opportunity. The WNBA’s growth is creating greater demand for specialized performance services, scientific research, and technologies developed and validated with female athletes.

3. Data integration is becoming more important than data collection. Formula 1 illustrates the value of coordinating complex datasets and expert judgment. Professional sports teams face similar challenges when combining information from wearables, biomechanics, medical assessments, and athlete management systems.

4. Athlete health and availability remain central priorities. Whether managing transatlantic travel in the NFL, playoff fatigue in the WNBA, or physical demands in Formula 1, teams need reliable approaches to preparation, monitoring, and recovery.

5. Technology is transforming both competition and the fan experience. Advanced analytics, AI, interactive broadcasts, and digital platforms are creating new opportunities for sports organizations and technology companies.

Conclusion: Three Events, One Important Message for the Sports Technology Industry

This weekend provides an interesting snapshot of where professional sports are heading.

The NFL’s historic game in Paris highlights the opportunities and complexities of international expansion. The WNBA Finals demonstrate the growing economic importance of women’s sports and the need for greater investment in athlete health and performance. Formula 1 illustrates how technology, data, and human expertise can be combined to create a competitive advantage.

For sports technology startups, these events also reinforce an important lesson.

The most promising opportunities are not necessarily about creating more data, more sensors, or more AI-powered dashboards. They are about helping teams solve meaningful problems.

Whether that means improving athlete readiness after international travel, supporting female athlete health, enhancing biomechanics analysis, or making complex information easier to interpret, the objective should remain the same: deliver measurable value to practitioners and athletes.

At Upside, we’ll continue following these developments, connecting with practitioners across professional leagues, and identifying innovations that can make a difference in elite sports.

Which of these three events are you most excited to watch this weekend? And which technologies do you believe will have the biggest impact on the future of professional sports?

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Measuring often, and over several seasons, is what turns movement data into a trend they can act on.

Performance staff in basketball talk about braking – the deceleration phase in which a player slows the body down, and it happens on every drive, closeout and rebound landing.

Dr. Bill Burgos is a former NBA strength and conditioning coach. In an Upside video chat in December 2025, he said: “In basketball, deceleration is arguably more important than acceleration. Anyone can run fast, but not everyone can stop efficiently.” Derek Millender, head strength and conditioning coach of the Cleveland Cavaliers, said in the same chat: “We absolutely train the brakes.”

The lower leg carries much of that load. A 2025 meta-analysis in Sports Medicine found that ankle injuries made up 25.8% of reported basketball injuries. Ankle and knee injuries together made up 41.3%.

One measurement describes one day

Teams track how much work a player does. Minutes are one useful measure of load. They record how long a player was on the court, but they carry no information about how the player moved during that time.

Two players with the same minutes can load the lower leg in different ways. One may land with more knee bend and a longer ground contact. Another may stop on a stiffer leg, or plant off the same foot on most cuts.

A single test shows where a player is on the day it was taken. Several tests, at regular intervals, show the direction and speed of a change. A good measurement taken every few weeks usually tells a team more than a very precise one taken twice a season.

Frequency also sets a standard for the method. It has to be consistent enough that a difference between session four and session nine reflects the player.

Two kinds of measurement

Detailed biomechanical assessment and frequency movement tests answer different questions. A detailed assessment examines technique in depth, under a fixed protocol, with the full set of measures. Optical marker-based motion capture is considered the gold standard method for that work.

A frequency test answers a narrower question. It tells the staff whether anything has changed since the last session, in time for the next training decision. Markerless testing is built for that job, and it does not replace detailed assessment.

A longer history is worth more

Movement data gains value with time. A third season of testing is more useful than a first. The staff can see how a pattern held through heavy load, travel and rehabilitation.

Most professional players arrive from a college program. A department that tests from year one builds several seasons of history on each athlete. It can also baseline a transfer or a freshman in the first week, which matters where players move between programs every year.

Fitting a test into the season

The schedule decides how often a team can test. NBA teams play 82 regular-season games, with back-to-backs and long road trips. The 2026-27 EuroLeague regular season has 38 rounds, including 10 double-round weeks, and most also play in a domestic league.

An in-season test usually has to fit inside the warm-up, in a time slot that is already planned. There’s no time to adhere markers or wearables to the athlete, and the results have to be comparable from session to session, no matter who is operating the test. An individual player should only be compared to his or her own longitudinal data, because an average from a 15-player team mixes very different roles.

How OnTraq runs the test

OnTraq is a markerless movement testing system from Qualisys, which has made motion capture systems for sport science and biomechanics since 1989. Markerless means the system measures 3D movement from video, so players wear no markers or sensors. Eight cameras are set up where the athletes train.

Each player completes 8 movement protocols in about 1 minute 40 seconds. Smart Capture is a patent-pending feature in OnTraq. It detects which movement a player is performing and logs each repetition of that movement automatically.

The movement library includes tasks that match basketball actions.

• Change of direction, or cutting, mimics the common in-game movement, in which a player plants one foot and pushes off in a new direction.

• Lateral leaps reflect defensive slides

• Drop jumps and counter-movement jumps test landing from a height and jumping again, as in rebounding.

Staff can build their own protocol from these tasks to effectively monitor the way the athlete moves compared to their baseline. Combine that with ground reaction force, available via integration with the OnTraq system, and it gives the whole picture of the player’s movement patterns associated with their game.

OnTraq’s trend dashboard is where coaches get direct answers. Each metric card names a movement and a metric, for example peak eccentric velocity in a counter-movement jump. It shows the latest value, the percent change compared with the last 5 sessions and a trend line.

The card shows how a player performs against his or her own baseline. A coach can read it and decide on readiness within moments. Sports scientists and physical therapists can open the web report for more detail, where each movement is split into phases.

An upcoming OnTraq webinar demonstrates the trend dashboards, how teams customize protocols and what the output looks like. Sign up for the webinar by clicking on the button below:

Sign up for the Webinar

Thomas Schneider, Sales Director for OnTraq in Europe, describes the purpose this way: “It’s not there to tell a coach how to coach. It’s there so the question ‘has anything changed since last time?’ has a real answer, fast enough to actually be useful before a decision needs to be made, not after.”

More information about OnTraq is available at ontraqbyqualisys.com.

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Introduction: Universities are becoming AI innovation hubs

Artificial intelligence is rapidly transforming higher education in the United States. Universities are investing in AI research laboratories, computing infrastructure, specialized faculty, and partnerships with major technology companies such as NVIDIA, Microsoft, Google, Amazon Web Services (AWS), IBM, and OpenAI.

These investments are creating a new generation of AI innovation ecosystems where researchers, students, startups, and corporate partners can collaborate to develop and commercialize advanced technologies.

For the sports industry, this represents a potentially significant shift.

College athletic departments generate enormous amounts of data through athlete management systems (AMS), GPS tracking, force plates, motion capture, video analysis, strength and conditioning platforms, medical assessments, and athlete wellness monitoring.

Yet despite the growing sophistication of these technologies, many teams still struggle to turn the data they collect into actionable insights.

AI laboratories could help bridge this gap.

Imagine a university where its AI researchers work directly with the athletic department to develop algorithms that analyze athlete movement, automate performance reporting, identify potentially meaningful changes in injury-risk indicators, optimize training schedules, or improve recruitment and scouting.

The same infrastructure could also support fan engagement, ticketing, commercial operations, and administrative productivity.

More importantly, these university-based innovations could eventually reach professional leagues such as the NFL, NBA, NHL, MLS, MLB, and European soccer.

The opportunity goes beyond using existing AI products. Universities could become creators, testing environments, and commercial partners for the next generation of sports AI technologies.

This analysis examines the emerging U.S. university AI ecosystem, its partnerships with major technology companies, and the opportunities it creates for athletic departments, professional teams, and sports technology startups.

Leading AI research laboratories and university initiatives in the United States

Not all university AI programs operate in the same way. Some focus on foundational AI research, others on supercomputing infrastructure, while a growing number apply machine learning and data science directly to human performance and sports analytics.

The following institutions are particularly relevant to the sports industry.

Additional universities worth monitoring include UC Berkeley (BAIR), the University of Washington (AI research and sports analytics), the University of Southern California (ISI and AI research), and Oregon State University (AI and advanced computing).

It is important to distinguish established sports-specific programs from general AI research laboratories. Not every institution listed currently has a dedicated AI partnership with its athletic department. For some, the sports applications described are opportunities rather than announced programs.

A standout example: University of Florida

Florida’s AI-Powered Athletics program demonstrates how university-scale computing infrastructure can be connected to sports performance data.

Rather than relying exclusively on individual commercial software products, universities with these capabilities can explore their own analytical models, combine data across multiple sources, and conduct research tailored to the needs of their athletic departments.

Another university to watch: Vanderbilt

Vanderbilt officially opened the Vanderbilt Lab for Immersive AI Translation (VALIANT) in 2025 to help translate advanced AI research into practical applications.

Its wider AI ecosystem includes:

• VALIANT: Research in computer vision, machine learning and related AI disciplines.

• Data Science Institute: Applied machine learning, interdisciplinary analytics and data science research.

• Amplify Generative AI Innovation Center: Launched in 2026 to support generative and agentic AI applications across the university.

• Biomechanics and engineering research: Expertise in human movement and rehabilitation that could complement AI-based analysis.

For sports, Vanderbilt’s most interesting opportunity may be connecting these research groups with its athletics department and external technology companies.

For example, AI researchers could collaborate with sports scientists to investigate athlete movement, training data, injury-related factors, or automated performance reporting.

A startup specializing in computer vision or wearable sensors could also collaborate with Vanderbilt researchers to evaluate its technology.

These are potential applications, not confirmed athletics deployments.

Why it matters: Vanderbilt has many of the ingredients required to become an important sports AI innovation hub. Its next opportunity is to connect those capabilities more directly with the needs of sports practitioners.

Partnerships between universities and major AI technology companies

The emergence of university AI ecosystems is being accelerated by partnerships with leading technology companies.

These relationships can provide access to GPU computing, cloud platforms, AI models, engineering expertise, training programs, research funding, and commercialization opportunities.

Key partnerships and strategic relationships

NVIDIA: A particularly important player

NVIDIA’s collaboration with the University of Florida is a notable example of how a technology partnership can help a university develop advanced AI capabilities.

Its HiPerGator infrastructure supports research across multiple disciplines, and NVIDIA has identified university relationships involving Oregon State and North Carolina A&T, as well as broader AI education initiatives.

For athletics, the potential applications are substantial:

• Processing large volumes of biomechanical and video data.

• Developing computer-vision models for markerless motion capture.

• Training sport-specific machine learning models.

• Combining historical performance and workload data.

• Building AI assistants for coaching, medical, and performance departments.

• Creating simulated training environments and digital models of athlete movement.

A critical distinction: access to NVIDIA infrastructure does not automatically mean a university has deployed these applications in its sports programs. The computing capability creates the opportunity; validated use cases and effective collaboration determine the value.

Vanderbilt: Expanding access to generative AI

Vanderbilt has also expanded access to AI technologies through institutional initiatives involving ChatGPT Edu, Amplify, and Google’s educational AI resources.

These initiatives support research, education, and university productivity.

Combined with VALIANT and Vanderbilt’s Data Science Institute, they create opportunities for researchers and university departments to develop practical AI applications.

Potential applications within Vanderbilt Athletics could include automated performance reporting, analysis of authorized athlete datasets, research assistants, and staff productivity tools.

These opportunities should be distinguished from confirmed sports-specific deployments.

My assessment: The most interesting partnerships may ultimately be those that bring together three groups: AI technology companies, university researchers, and athletic departments.

Such collaborations could accelerate innovation while providing researchers with access to meaningful real-world problems and carefully governed datasets.

How AI labs could transform college athletic departments

The most immediate opportunity is to connect academic AI expertise with the practical challenges facing athletic departments.

College teams already invest in sophisticated technologies. However, their performance, medical, coaching, recruiting, and commercial departments often operate with different systems and datasets.

AI could help connect those departments, automate repetitive processes, and produce insights that would otherwise require significant manual analysis.

Seven high-potential applications

Which applications should athletic departments prioritize?

The following is an editorial assessment of implementation opportunities, not a ranking based on proven commercial results.

The most practical initial applications are likely to be those that reduce administrative work and improve access to existing data. They generally offer clearer measures of success than ambitious injury-prediction projects.

How university AI labs could accelerate innovation across elite sports

One of the most interesting developments is the possibility that universities become major research and development partners for professional teams.

We already see examples of this model emerging.

Carnegie Mellon’s Sports Analytics Center has worked on applications using NFL tracking data. In April 2026, the university described how its researchers’ analysis would be integrated into the NFL IQ AI chat tool, supporting questions about draft prospects, team needs, and player evaluation.

Stanford’s Human Performance Laboratory similarly demonstrates the value of connecting researchers, sports medicine, engineering, and athletic programs in one research environment.

Vanderbilt represents another potential opportunity. Its AI researchers, biomechanics expertise, and Data Science Institute could collaborate with sports technology companies and professional organizations on movement analysis, performance analytics, or rehabilitation research.

These examples suggest a broader opportunity.

There are four particularly important implications.

First, universities could reduce the cost of early-stage experimentation. Research groups and graduate students may be able to explore ideas that are too speculative for commercial vendors to prioritize, although research still requires funding, governance, and staff time.

Second, they could strengthen scientific validation. Independent university researchers can help evaluate whether new AI technologies actually improve performance, assessment reliability, or workflow efficiency.

Third, they could accelerate the creation of sport-specific AI models. General-purpose models may struggle with the terminology, data structures, and decision-making processes of professional sports.

Fourth, universities could become startup incubators. Research breakthroughs could lead to new products, university spinouts, licensing agreements, and investment opportunities.

This could become especially relevant to professional organizations that lack the resources to maintain large internal AI research departments.

Potential impact on Athlete Management Systems (AMS) and AI sports technology companies

This may be one of the most commercially significant consequences of the expansion of university AI laboratories.

Today, many teams rely on commercial Athlete Management Systems to consolidate performance, medical, and wellness information.

Companies such as ORRECO, Action Apps, Teamworks, Kitman Labs, Genetrainer, operate across different parts of this ecosystem, including athlete data management, performance monitoring, and/or sports operations.

University AI initiatives could influence how these platforms evolve.

A. A potential challenge to traditional AMS business models

Historically, an important part of an AMS platform’s value has been its ability to collect, centralize, visualize, and report athlete information.

But as AI models become more capable of analyzing structured and unstructured data, customers may increasingly expect their software to do more than display dashboards.

For example, instead of manually reviewing multiple reports, a performance director might ask:

• Which athletes experienced the largest changes in high-speed running exposure this week?

• Which players have incomplete rehabilitation assessments?

• What patterns appear in our previous three seasons of hamstring injuries?

• Which athlete monitoring variables are most strongly associated with performance outcomes in our own data?

This creates pressure for AMS providers to evolve toward more intelligent decision-support platforms.

However, universities building custom AI tools does not automatically eliminate the need for commercial AMS products. Data quality, permissions, interoperability, reliability, support, security, and workflow design remain essential.

B. Opportunity: AMS companies could partner directly with AI laboratories

Instead of treating university AI labs as competitors, AMS providers could use them as research partners.

Potential collaborations include:

1. Joint algorithm development: Building and evaluating models for performance, recovery, and workload analysis.

2. Research validation: Testing whether new AI features are accurate, reliable, and useful to practitioners.

3. Secure data integration: Developing APIs and privacy-preserving methods for analyzing information across multiple platforms.

4. AI assistant development: Creating natural-language interfaces to authorized athlete datasets.

5. Product testing: Running structured pilots with college athletic departments before expanding to professional teams.

Vanderbilt’s Data Science Institute, VALIANT, and applied AI initiatives could potentially provide research expertise for such collaborations, alongside universities such as Florida, Stanford, and Carnegie Mellon.

C. A significant opportunity for sports AI startups

The opportunity extends well beyond AMS providers.

Consider a startup developing markerless motion capture for football quarterbacks.

It could partner with a university’s computer vision researchers, biomechanics department, and football program to study throwing mechanics and develop sport-specific algorithms.

At Vanderbilt, for example, this could involve combining VALIANT’s AI research expertise with biomechanics researchers and, subject to appropriate agreements, athletics practitioners.

The athletic department would gain access to experimental technology, the researchers would gain a meaningful applied research project, and the startup could improve its product while building a stronger evidence base.

This is a potential model, not a claim that such a partnership has been established.

D. Will universities build competing sports AI companies?

Some could.

Universities may develop proprietary algorithms, research software, and intellectual property that can be licensed or commercialized.

However, turning a research prototype into a scalable sports technology business is difficult. Companies must provide customer support, cybersecurity, integrations, continuous product updates, and dependable commercial operations.

Consequently, I expect three models to coexist:

• University-developed tools used internally by athletic departments.

• University–vendor partnerships that jointly develop and validate commercial solutions.

• University spinouts that become independent sports technology startups.

For established vendors, the key is to become a partner in this ecosystem rather than simply another software supplier.

The next competitive advantage: Proprietary sports data and AI expertise

As foundational AI models become increasingly accessible, competitive differentiation may shift toward the quality of proprietary data, domain expertise, validated models, and integration into daily workflows.

This is particularly relevant in elite sports.

A university may have years of information from athlete monitoring, strength and conditioning, medical assessments, and game analysis.

When appropriately governed and analyzed, those datasets can become valuable research resources.

But the value is not simply the number of data points collected.

A large dataset with inconsistent measurements, missing information, or unclear definitions may be less useful than a smaller, carefully curated dataset.

The institutions that could benefit most are those that combine:

High-quality longitudinal data + AI research expertise + practitioner knowledge + robust validation.

Florida’s AI-Powered Athletics initiative provides one example of efforts to connect university AI capabilities with sports datasets.

Vanderbilt’s interdisciplinary AI ecosystem offers another potential foundation, particularly if its research groups and athletic department develop structured collaborations.

There are also important safeguards. Student-athlete privacy, medical confidentiality, consent, intellectual property, NCAA requirements, and commercial data-use restrictions must be addressed before data is used for research or model training.

In particular, medical and performance data should not be made broadly accessible to recruiters, commercial departments, or external vendors simply because a university has built a centralized AI platform.

Recommendations to college teams and professional sports organizations

Based on these developments, I would recommend that athletic departments take a proactive but disciplined approach.

1. Build relationships with your university’s AI researchers

Athletic departments should identify faculty and research groups specializing in machine learning, biomechanics, computer vision, optimization, and data science.

At Vanderbilt, this could involve bringing together VALIANT, the Data Science Institute, biomechanics researchers, and Vanderbilt Athletics to identify opportunities for applied research.

2. Audit existing data and technology infrastructure

Determine what data is available, who controls it, whether vendors support secure exports or APIs, and which datasets can legally and ethically be combined.

3. Launch two or three focused AI pilots

Prioritize applications with measurable outcomes, such as reducing reporting time, improving data retrieval, or increasing the reliability of movement assessments. Avoid beginning with promises of injury prediction.

4. Create partnerships with sports technology vendors

Invite existing AMS, wearable, biomechanics, and analytics providers to participate in collaborative research. Establish clear agreements concerning data ownership, publications, intellectual property, and commercial rights.

5. Establish strong AI governance

Involve medical, legal, IT, compliance, and athlete representatives. Require appropriate consent, access controls, cybersecurity, and human oversight. Evaluate models for accuracy, bias, and performance across athlete populations.

6. Measure outcomes before expanding

Compare AI-assisted workflows with existing practices. Track time saved, practitioner adoption, data quality, decision consistency, and other relevant measures. Expand only when the benefits justify the cost and risk.

A practical 12-month roadmap

For professional teams, a similar approach could involve partnering with nearby universities rather than building a large internal AI research team.

What this means for the sports technology investment ecosystem

The rise of university AI labs also creates an interesting opportunity for sports technology investors.

Traditionally, investors discover startups through founders, accelerators, venture networks, and industry conferences.

University AI laboratories could become an additional source of promising technologies.

Some of the most interesting companies in the coming years may originate from research projects involving computer vision, biomechanics, wearable sensors, sports analytics, or intelligent training systems.

Investors should pay particular attention to three indicators:

Scientific differentiation: Does the startup have meaningful intellectual property, unique data, or a technically defensible advantage?

Real-world validation: Has the technology been evaluated in relevant sporting environments, with evidence supporting its claims?

Commercial readiness: Can the founding team turn research into a reliable product that teams are willing to purchase and use?

Strong university affiliations can increase credibility, but they are not substitutes for independent validation, customer traction, and execution.

One potentially valuable model would be a university sports AI accelerator connecting research laboratories, athletic departments, sports technology founders, professional teams, and investors.

Stanford’s existing HAI Startup Series provides an example of a broader AI commercialization initiative that offers early-stage companies mentorship and exposure to researchers and business leaders.

Vanderbilt’s expanding AI ecosystem, together with Nashville’s healthcare and technology community, could also provide a foundation for exploring sports-focused AI commercialization initiatives.

Conclusion: Could universities become the next major sports AI innovation centers?

The emergence of AI research laboratories across U.S. universities represents more than an academic trend.

It could reshape how sports organizations develop, evaluate, and adopt technology.

Universities have a potentially powerful combination of assets: AI researchers, computing infrastructure, students, interdisciplinary expertise, athletic departments, and relationships with major technology companies.

Institutions such as Florida, Stanford, Carnegie Mellon, Michigan, and Vanderbilt demonstrate different elements of this opportunity.

Florida provides an established example of connecting AI infrastructure with collegiate athletics.

Carnegie Mellon demonstrates how academic research can contribute to professional sports analytics.

Stanford and Michigan offer strong interdisciplinary human performance research environments.

Vanderbilt, through VALIANT, its Data Science Institute, Amplify, and its biomechanics research capabilities, represents another institution with the potential to connect advanced AI research with collegiate athletics and sports technology innovation.

The next step is connecting these resources more systematically to the needs of coaches, sports scientists, medical professionals, scouts, and athletic administrators.

The implications could be significant.

For college teams, AI could improve operational efficiency, performance analysis, recruiting, and the quality of decision support.

For professional teams, university partnerships could provide access to advanced research capabilities without requiring them to build every technology internally.

For AMS providers and sports technology companies, university AI labs could become important collaborators in algorithm development, product validation, and innovation.

For investors, they could become a source of new companies built around defensible research and real-world applications.

However, success will depend on much more than access to powerful AI models or GPUs. It will require high-quality data, rigorous validation, responsible governance, and close collaboration with practitioners.

My prediction is that over the next three to five years, we will see more structured partnerships between university AI laboratories, college athletic departments, professional sports organizations, and sports technology companies.

The universities that successfully connect their AI research capabilities with their athletic programs could become influential innovation hubs for the broader sports industry.

And the sports technology companies that establish these relationships early may gain a meaningful advantage in developing the next generation of performance and analytics solutions.

Selected research sources and further reading

The following official resources provide useful starting points for examining this emerging ecosystem.

• University of Florida — AI-Powered Athletics

• NVIDIA — University of Florida AI case study

• Stanford — Human Performance Laboratory

• Carnegie Mellon — Sports Analytics Research Lab

• University of Michigan — High Performance Athlete Innovation Lab

• Vanderbilt — Opening of VALIANT

• Vanderbilt — VALIANT affiliated AI laboratories

• Vanderbilt — Amplify Generative AI Innovation Center

• Vanderbilt — Data Science Institute

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Dear Colleague,

We are excited to announce that Rezzil is a new sports-tech startup confirmed to present at our upcoming Upside VIP Lunch at the 2026 PSPA Conference in Atlanta.

⚽ Upside VIP Lunch
📅 December 18, 2026, 12 pm - 2.30 pm
📍 Atlanta, Georgia, US Soccer HQ

The event will bring together approximately 200 leading MLS and NWSL practitioners and decision-makers, including Performance Directors, Heads of Athletic Therapy, Directors of Rehabilitation, Sports Scientists and representatives from clubs across the leagues.

Each presenting startup will be able to present for 15 minutes to MLS/NWSL practitioners, have a booth and be part of a speed dating session with the teams.

Due to high demand, we extended the number of presenting startups to ten. Next week we plan to announce some new startups presenting at our VIP Lunch, We have a lot of startups interested in taking the last three spots so please reach out to us ASAP if interested in presenting.

🚀 Meet the New Presenting Startup

👓 Rezzil

Rezzil (www.rezzil.com) is a pioneering Movement Intelligence company transforming how elite sport measures, develops and optimises performance. Founded in Manchester, UK, Rezzil turns movement into actionable insights, helping athletes and sporting organisations unlock performance through innovative technology, data, and immersive training.

At the heart of its performance offering is Rezzil Review that transforms match footage into immersive 3D environments, giving coaches and players new perspectives on game analysis, tactical understanding, and preparation. By revisiting key moments from different viewpoints, teams can uncover insights that traditional video alone cannot provide.

Rezzil Index, compliments this offering, an advanced platform that enables professional teams to assess, benchmark and develop the cognitive and physical capabilities that underpin elite performance. Through sport-specific VR training simulations and data-driven insights, Rezzil helps players sharpen decision-making, spatial awareness, scanning, reaction time, and performance under pressure, while supporting rehabilitation and return-to-play programmes.

Trusted across elite sport, Rezzil works with organisations including Brentford, Burnley FC, Monaco, Red Bull and more to support player development, performance analysis and rehabilitation. By combining technology, research and practical sporting expertise, Rezzil is helping teams better understand their athletes, make more informed decisions and find new ways to unlock their full potential. In 2024, the Premier League entered a four-year strategic partnership and took an equity stake in Rezzil, further strengthening its position in immersive sports technology.

Here is a video of Rezzil’s performance solution for teams

You can watch the video interview we did with Rezzil CEO:

⚠️ Only Three Presentation Spots Remain

Selected sports technology vendors will have the opportunity to:

• Present directly to MLS and NWSL teams and practitioners

• Demonstrate and exhibit their technology

• Receive feedback from experienced sports performance professionals

• Participate in meaningful conversations with key decision-makers

• Explore potential pilots, partnerships and commercial opportunities

• Build relationships in an intimate, highly targeted environment

We already have 7 vendors confirmed to present so if you are Interested in the last 3 spots to present please reach out to us ASAP at julien@upsideglobal.co before the last spots are gone. We have lots of startups who are interested so we won’t be able to accommodate everyone.

Last year’s Upside VIP Dinner welcomed more than 50 practitioners representing over 20 MLS clubs.

You can view the recap and recorded panel discussions and presentations here:

🚀 COMING IN Q1 2027: UPSIDE SPORTS TECH INVESTMENT VIP DINNER — NYC!

We’re excited to announce that Upside is planning an exclusive Sports Tech Investment VIP Dinner in New York City in Q1 2027!

The goal? Bring together leading investors, sports team owners, executives, and innovative startup founders for an evening of investment opportunities, meaningful connections, and networking.

📍 Location: An exclusive private club in NYC
📅 Date: Q1 2027 (TBA)
👥 50 top executives, including Top sports tech VCs, team owners, sports executives, and founders
🚀 8 selected sports tech startups will have the opportunity to pitch directly to investors
🤝 Networking with key decision-makers across sports, technology, and venture capital

Our mission is simple: Connect the next generation of sports tech startups with the investors and industry leaders who can help them grow.

📩 Are you a sports tech startup looking to raise capital?

We’re now welcoming expressions of interest from startups interested in pitching at the event.

Email julien@upsideglobal.co to learn more and express your interest.

More details coming soon!

📅 What’s Next for Upside

🇫🇷 Upside Tech Summit—France
📅 2nd half of 2027
📍 France

We are planning to host this summit at a major stadium, bringing together leading organizations from Ligue 1, the Premier League, LaLiga, international rugby, basketball, the NBA, MLS, the NFL and other elite sports.

We are also developing additional Upside VIP events with major leagues, teams, VCs across the United States and Europe in 2026 and 2027.

Interested in attending, speaking, presenting, exhibiting or sponsoring an upcoming Upside event? Contact me at julien@upsideglobal.co.

Best,

Julien

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Upside Global | October 2026

This weekend, I had the opportunity to visit Vanderbilt University (NCAA), Nashville SC (MLS) and catch up with the Predators (NHL) in Nashville, Tennessee, and attend the Health & Performance Summit at Austin Peay State University (APSU) in Clarksville, presented by Deaconess.

It was a fascinating weekend learning how collegiate athletic programs, professional sports organizations, and the military approach athlete development, training, recovery, injury management, nutrition, and emerging technologies.

I also had the opportunity to meet and interview several sports technology companies exhibiting at the summit, including Myocene, DetectFit, Aris Training, VALD, and QuickBoard.

Four areas particularly stood out:

1. How NCAA athletic departments are adopting advanced performance technologies and AI.

2. How the LA Dodgers evaluate and develop young international baseball players.

3. How NBA performance departments manage training, nutrition, recovery, and player readiness.

4. How the military is applying sports science principles to improve operational readiness and long-term durability.

One theme kept coming up throughout the weekend:

The future of human performance isn’t necessarily about collecting more data. It’s about using technology, science, and practitioner expertise to make better decisions.

Here are my key takeaways.

Inside Vanderbilt University: NCAA Performance Technology Is Catching Up With Professional Sports

During my visit to Vanderbilt University, I learned more about its athletic programs, which support approximately 400 student-athletes across 17 varsity teams, according to the figures discussed during my visit.

The university has invested in a wide range of technologies supporting athlete training, rehabilitation, and recovery.

Some of the technologies I learned about included:

• Force plates: Used to assess strength, power, neuromuscular performance, and movement characteristics.

• Velocity-based training (VBT): Technologies that measure movement velocity during resistance training.

• Ultrasound technologies: Used in sports medicine and rehabilitation.

• Computer vision: Movement analysis technologies that can provide biomechanical insights.

• Athlete Management Systems (AMS): Platforms that centralize athlete health, training, and performance information.

• AI-powered analytics: Emerging tools designed to support athlete monitoring and performance analysis.

What impressed me was how sophisticated some collegiate performance environments have become.

The gap between NCAA and professional sports performance technology is narrowing.

Some NCAA programs now have access to facilities and technologies comparable to those used by professional sports organizations.

The importance of donor funding

Another interesting takeaway was the role of donations in funding athletic facilities and performance technologies.

Private donations can help collegiate programs invest in equipment, training environments, and athlete development resources.

This creates opportunities for sports technology companies, particularly those offering solutions that demonstrate practical value for student-athletes and performance staff.

Investing in the fan experience

Vanderbilt is also investing in its broader athletic infrastructure and fan experience.

Its football stadium accommodates approximately 30,000 fans, and premium hospitality offerings are becoming an important part of the experience.

This reflects a broader trend across collegiate athletics: athletic departments are investing in performance facilities, student-athlete development, and fan experiences to attract athletes, supporters, and donors.

University AI Labs Could Become a Major Competitive Advantage for NCAA Programs

One of the most interesting trends I’m seeing is the growing opportunity for collaboration between university athletic departments and AI research laboratories.

Universities have direct access to researchers, computer scientists, engineers, and academic resources that can support the development of new performance technologies.

Potential applications include:

• Injury risk assessment: Identifying patterns associated with increased injury risk.

• Biomechanics: Using computer vision and AI to analyze movement.

• Athlete monitoring: Integrating training, recovery, and physiological information.

• Performance analytics: Identifying trends that can help individualize training.

• Workload management: Supporting decisions around training intensity, fatigue, and readiness.

Rather than relying exclusively on third-party vendors, NCAA programs may increasingly collaborate with university research departments to develop customized solutions.

However, developing an AI model is only the first step.

The challenge is translating research into scientifically validated tools that coaches, sports scientists, and medical staff can use in their daily workflows.

My takeaway: NCAA athletic departments could become important innovation hubs for the sports technology industry, particularly in AI, biomechanics, and athlete monitoring.

Chris Dunaway, LA Dodgers: Creative Solutions to Improve Performance

One of the highlights of the APSU summit was a presentation by Chris Dunaway, International Director of Athleticism & Performance for the Los Angeles Dodgers (MLB).

His session, “Creative Solutions to Improve Performance,” provided an inside look at how the Dodgers scout, evaluate, and develop young baseball players internationally, particularly in the Dominican Republic.

Chris opened with a quote that captured his philosophy:

Never tell people how to do things. Tell them what to do and they will surprise you with their ingenuity.

The message was clear: give practitioners a problem to solve and empower them to develop creative solutions.

Using portable force plates to evaluate young baseball players

Chris explained how the Dodgers use mini force plates in their international development programs.

These portable systems allow practitioners to assess physical characteristics without requiring sophisticated laboratory environments.

The assessments he discussed included:

• Strength testing using force plates.

• Dynamic Strength Index (DSI).

• Sprint profiling.

• Movement screening.

• Regular monitoring of physical development.

One particularly interesting detail was that the Dodgers focus on approximately five or six key performance metrics, rather than trying to analyze every available data point.

Chris also mentioned that force plate testing is performed on Mondays as part of their monitoring routines.

Understanding the Dynamic Strength Index

The Dynamic Strength Index compares an athlete’s peak force during an explosive movement, commonly a countermovement jump, with maximal force during an isometric strength assessment.

It helps practitioners understand the relationship between maximal strength and explosive force production.

This information can help identify strength and power development priorities.

International scouting and player development

Chris gave us a fascinating look at how the Dodgers scout and evaluate young baseball players in the Dominican Republic.

Portable performance technologies allow practitioners to gather useful physical assessments without requiring extensive laboratory infrastructure.

International recruitment and signing eligibility vary according to the country and applicable MLB rules.

The Dodgers use physical testing, movement assessments, and performance data to better understand young players’ athletic profiles and development potential.

Injury history and training consistency

Chris emphasized that the Dodgers take a cautious approach to managing injury risk.

One of his key points was that previous injury is among the strongest predictors of future injury.

He also raised concerns about the physical demands placed on baseball players.

Many athletes train and compete extensively throughout the year, leaving limited opportunities for recovery.

Another challenge is that some players work with external trainers, potentially creating inconsistencies between their individual training programs and those prescribed by the organization.

Integrating GPS, biomechanics, and performance data

Chris also discussed how the Dodgers use GPS systems, including STATSports, within their development environments.

At the MLB level, technologies such as Hawk-Eye, Kinetrax, and TrackMan generate extensive movement, biomechanics, and performance data.

The challenge is integrating these data sources into centralized systems that support decisions about training, workload, and player development.

My takeaway: Collecting more data is not necessarily the solution. Identifying the most relevant metrics and translating them into actionable decisions is what matters.

Dr. Bill Burgos: Performance Is Not Random — Inside NBA Performance Operations

Another fascinating presentation came from Dr. Bill Burgos, founder of BUCOGROUP, LONU and former Head Strength & Conditioning Coach for the Minnesota Timberwolves, Orlando Magic, and New York Knicks.

His session, “Performance Is Not Random,” provided a behind-the-scenes look at how NBA performance departments manage athletes throughout an 82-game regular season.

Bill emphasized that elite performance requires much more than strength training.

It involves daily workload management, nutrition, recovery, sleep, athlete education, and consistent communication.

NBA teams operate on structured daily schedules

Bill described how teams organize their routines around practice days, game days, and off days.

A typical game-day schedule might include:

• 11:00 AM: Team shootaround.

• 7:30 PM: Game tip-off.

Between these activities, performance staff must coordinate nutrition, recovery, treatment, training, and player preparation.

As Bill explained, NBA players already play an enormous amount of basketball throughout the season.

The challenge is determining how much additional training they need and when to schedule it.

Managing workload and training intensity

One of Bill’s main responsibilities was managing players’ daily training loads.

He discussed the importance of monitoring training intensity, including whether an athlete exceeds a desired threshold during weightlifting.

This reinforces the need to individualize strength training rather than applying identical programs to every player.

The objective is to provide an appropriate training stimulus without unnecessarily increasing fatigue during a demanding competition schedule.

Using QuickBoard and force plates on game day

One particularly interesting insight was how Bill incorporated QuickBoard and force plate assessments into NBA game-day routines to measure player readiness.

QuickBoard was used to assess aspects of reactive movement and neuromuscular performance, including reaction time, coordination, and movement accuracy.

Force plates provided objective measurements of force production, jump performance, and other neuromuscular characteristics.

These assessments helped performance staff monitor players and identify changes relative to their individual baselines.

The practical advantage is that both technologies can provide useful information through relatively short testing sessions.

My takeaway: Game-day readiness assessments can help practitioners make more informed decisions, provided the results are interpreted alongside player feedback, workload, recovery, and injury history.

Blood flow restriction training in the NBA

Bill also discussed using blood flow restriction (BFR) training during his NBA career.

BFR involves using specialized cuffs to partially restrict blood flow during exercise.

It can provide a training stimulus while reducing the need for heavy external loads, making it relevant in certain rehabilitation and strength-training situations.

This is particularly interesting in the NBA, where athletes already accumulate substantial physical demands through practices, games, and travel.

BFR can offer practitioners another option when heavier loading is not appropriate, although it requires suitable screening and supervision.

Creatine supplementation and individualized nutrition

Bill also discussed being particularly careful about creatine use.

His comments highlighted the importance of managing supplementation deliberately rather than assuming every athlete should follow the same approach.

More broadly, nutrition was one of the central themes of his presentation.

He explained that performance staff may estimate athletes’ calorie needs, but knowing what players actually consume can be difficult.

For example, when players order food independently, staff may not know exactly what they have ordered or eaten.

This creates challenges when trying to manage fueling, recovery, and overall nutritional intake.

Educating younger NBA players about nutrition

One of the most interesting observations was the difference between veteran and younger players.

Bill explained that experienced NBA players often have a better understanding of how to eat properly, while younger athletes may need considerably more guidance.

He recalled younger players who wanted to eat chicken tenders before every game.

His approach was not simply to tell athletes what they could or couldn’t eat.

Instead, he focused on education and helping players understand the relationship between nutrition, energy, recovery, and performance.

Working collaboratively with team chefs

Bill also discussed the importance of building relationships with chefs.

Rather than dictating exactly what chefs should prepare, his approach was to involve them in the performance process and educate them about the nutritional needs of NBA players.

This helped align food preparation with the broader performance objectives of the team.

It is a useful reminder that nutrition management requires collaboration between athletes, performance staff, dietitians, and food service personnel.

Building regular touchpoints with players

Another interesting observation concerned the differences in players’ daily routines.

Bill explained that some established players with major contracts had greater flexibility and spent time away from the team’s facilities.

Meanwhile, some younger players spent considerably more time at the training facility.

This made it important to create regular touchpoints with athletes to discuss nutrition, recovery, and preparation.

Rather than relying on occasional formal meetings, performance staff needed ongoing communication to reinforce healthy habits.

Bill also described setting up fueling stations to encourage athletes to make better nutritional choices throughout the day.

The goal was to create an environment that made good decisions easier.

Understanding soreness during the NBA season

Bill also shared interesting observations about muscle soreness.

He explained that soreness was often more noticeable at the beginning of the NBA season, when players were adjusting to the physical demands of training and competition.

As the season progressed, athletes generally adapted to those demands.

However, he emphasized that practitioners should consider whether what players describe as soreness might also reflect inadequate fueling or insufficient recovery.

Not every complaint of fatigue or discomfort should automatically be attributed to excessive training load.

Nutrition, sleep, recovery, and changes in training intensity can all influence how athletes feel.

Sleep disruption affects both players and performance staff

Another major challenge is sleep.

NBA players frequently deal with late games, travel, and changing schedules.

Bill also recalled the additional disruptions caused by COVID-era testing protocols.

But he highlighted another issue that is often overlooked:

NBA performance staff themselves frequently struggle to get enough sleep.

Coaches, trainers, and medical personnel must prepare the next day’s activities, coordinate treatments, organize training, and support athletes.

We often discuss athlete recovery, but the well-being of the practitioners supporting those athletes deserves more attention.

Teaching principles rather than creating dependency

One of my favorite takeaways from Bill’s presentation was his philosophy around athlete education.

He wanted players to take ownership of their preparation, nutrition, training, and recovery.

Rather than telling them what to do every day, he focused on teaching principles they could apply independently throughout the season.

My takeaway: Elite performance is not random. It is built through consistent daily habits, appropriate training loads, objective monitoring, proper nutrition, recovery, and athlete education.

Paul Robbins: The Science Behind Athletic Excellence: Training and Recovery Innovation

One of the interesting sessions at the ASPU Summit was led by Paul Robbins, who discussed how tracking technologies, biomechanics, big data, and artificial intelligence are transforming the way sports organizations approach athlete performance, training, and recovery.

The session highlighted four key areas where technology and data can help practitioners better understand athletes and make more informed decisions.

1. Understanding the True Physical Demands of Athletes Through Game Monitoring

Tracking technologies are providing teams with increasingly detailed insights into the physical demands athletes experience during competition.

By analyzing movement patterns, workloads, accelerations, decelerations, and other performance metrics collected during games, practitioners can develop a more accurate understanding of what athletes experience on the field or court.

Key takeaway: Training programs should be informed by the actual demands of competition, rather than relying exclusively on traditional training metrics or generalized assumptions.

2. Using Biomechanics Data to Improve Post-Game Recovery and Training

Game data can also provide valuable biomechanical insights into how athletes move and respond to physical demands during competition.

These insights can help practitioners better understand movement patterns, mechanical stress, and potential areas of fatigue.

By connecting biomechanics information with training and recovery strategies, teams can work toward more individualized post-game recovery protocols and training programs.

Key takeaway: The integration of game tracking data and biomechanics could help teams move toward more personalized, evidence-informed approaches to recovery and training.

3. Combining Big Data With Secure AI to Accelerate Decision-Making

Professional sports organizations are collecting enormous amounts of information through tracking systems, athlete monitoring platforms, biomechanics tools, and other technologies.

However, the challenge is not simply collecting more data. It is making that information accessible, secure, and useful for coaches and practitioners.

Paul highlighted the opportunity to use secure AI solutions to analyze large datasets, identify meaningful patterns, and help coaches make faster, better-informed decisions.

Key takeaway: AI could become an increasingly valuable tool for transforming complex performance datasets into actionable insights, provided data security, reliability, and practitioner oversight remain priorities.

4. Turning Complex Data Into Clear, Actionable Insights

Perhaps one of the most important messages from the session was that collecting sophisticated data is only part of the equation.

Teams need to determine how to present insights in ways that are simple, clear, and immediately useful to coaches and performance staff.

A dashboard containing hundreds of metrics may be technically impressive, but its practical value is limited if coaches cannot quickly understand what matters and what actions to take.

The challenge for technology companies is therefore not just building better measurement tools, but also developing more intuitive ways to communicate findings.

Key takeaway: The value of sports performance technology increasingly depends on its ability to deliver the right information, to the right person, at the right time.

💡 Upside Take: The Future Is About Better Decisions, Not More Data

Paul Robbins’ session reinforced an important trend across the sports performance industry: the next competitive advantage may come less from collecting additional data and more from making existing data actionable.

Four broader trends stand out:

• Game-informed training: Using real competition data to design more relevant training programs.

• Individualized recovery: Connecting biomechanics and workload information to post-game recovery strategies.

• Secure AI integration: Using AI to analyze complex datasets and support faster practitioner decisions.

• Simplified insights: Moving beyond complex dashboards toward clear, actionable recommendations.

For sports-tech startups, there is an important lesson here.

The companies that succeed may not necessarily be those collecting the most data, but those helping practitioners understand what the data means and what to do next.

As teams continue investing in athlete tracking, biomechanics, and AI-powered analytics, the ability to connect these technologies and translate information into practical decisions could become an increasingly important differentiator.

Sgt. Spencer Posey, Garmin: Athletic Excellence and Military Preparedness

Another particularly interesting presentation came from Sgt. Spencer Posey, Military & Human Performance Lead at Garmin.

His session, “Athletic Excellence and Military Preparedness,” explored how the military is adopting principles from elite sports performance while facing very different operational challenges.

Who is the better athlete: an NFL linebacker or a soldier?

Spencer opened with a thought-provoking question:

Who is the better athlete: an NFL linebacker or a soldier with 14 years of military experience?

An NFL linebacker prepares for competition with a relatively predictable schedule.

The athlete knows when the game will take place, where it will be played, and who the opponent will be.

Military personnel, on the other hand, must operate in unpredictable environments.

They may face unknown threats, extended deployments, limited recovery opportunities, and constantly changing operational demands.

A professional athlete prepares to perform at a specific time.

A soldier must be prepared to perform when the mission requires it, often without knowing when that moment will come.

How the US military is adopting human performance programs

Spencer discussed the evolution of military human performance initiatives.

Historically, military physical training often followed a standardized approach.

For example, personnel might be required to participate in the same physical training drills at 6:30 AM, regardless of their individual needs, physical condition, or occupational requirements.

Over time, military organizations began adopting more comprehensive approaches inspired partly by elite sports performance.

Spencer highlighted several initiatives:

• TFF: Total Force Fitness a framework that came out of the Department of defense in the early 2000’s focused on eight domains of readiness: Physical, medical, nutritional, psychological, social, environmental, spiritual, financial.

• THOR3: Tactical Human Optimization, Rapid Rehabilitation and Reconditioning.

• POTFF: Preservation of the Force and Family.

• H2F: The US Army’s Holistic Health and Fitness initiative, introduced in 2020, which places greater emphasis on physical readiness, nutrition, sleep, and broader human performance.

The objective is to move beyond traditional fitness testing toward a more comprehensive approach to military readiness.

The potential return on investment of military human performance programs

One particularly interesting figure Spencer shared concerned the potential economic benefits of the Army’s H2F initiative.

He referenced an evaluation covering the 2019–2023 period.

According to the figure presented, every $1 invested generated an estimated $8.15 in value.

This was presented as an estimated return on investment rather than a direct financial return.

The broader implication is significant.

Improving physical readiness, reducing injuries, and keeping military personnel available for duty can potentially create substantial operational and economic value.

Being strong in the gym doesn’t necessarily mean being ready for the field

Another important takeaway was the difference between gym performance and occupational capability.

Spencer challenged the assumption that a soldier who performs well in strength testing will necessarily perform well in operational environments.

Being able to lift heavy weights in a gym doesn’t automatically mean someone can carry heavy equipment over difficult terrain, move under fatigue, or perform complex tasks under pressure.

Physical fitness is important, but it is not the same as operational readiness.

The same principle applies to elite sports.

An athlete can produce impressive numbers on force plates or in strength testing without necessarily performing better during competition.

The challenge is identifying assessments that reflect the actual demands of the occupation or sport.

Availability wins: load management as a military readiness intervention

One of Spencer’s strongest messages was:

“Availability wins in the military.”

In professional sports, teams manage athlete workload to support performance and reduce injury risk.

Spencer argued that load management should also be considered a critical military readiness intervention.

The objective is not simply to make soldiers stronger or fitter.

It is to ensure they remain physically capable and available when needed.

He suggested that load management should become a leadership metric, with commanders evaluated partly on how effectively they maintain the readiness of their personnel.

Rather than treating injuries and physical readiness solely as medical responsibilities, military leadership should be directly involved in managing human performance.

Sleep: recovery is preparation

Sleep was another major topic.

Spencer emphasized that recovery is preparation.

However, unlike professional athletes, military personnel cannot always protect their sleep schedules.

Operational requirements, deployments, missions, and unpredictable environments can disrupt recovery.

Human performance teams must therefore develop strategies that improve readiness even when ideal sleep conditions are impossible.

Nutrition in the military: performance under unpredictable conditions

Spencer also discussed the importance of nutrition in military environments.

In professional sports, athletes often have access to team chefs, nutritionists, fueling stations, and carefully planned meals.

Military personnel may face very different conditions:

• Unpredictable meal schedules.

• Restricted access to food and water.

• Limited opportunities for recovery.

• High physical demands.

• Difficult environmental conditions.

Spencer highlighted the importance of practical fueling strategies, including carbohydrate availability and post-operation rehydration.

The challenge is developing nutrition strategies that work under real operational conditions rather than assuming ideal access to food and recovery resources.

Return to play vs. return to duty

Another important distinction concerns rehabilitation.

In professional sports, practitioners frequently discuss Return to Play (RTP).

In the military, the equivalent concept is Return to Duty (RTD).

Returning to duty involves more than recovering from an injury.

A soldier must demonstrate the physical capability required to perform their specific occupation.

Different military roles may require different combinations of strength, endurance, mobility, load carriage, and operational skills.

Rehabilitation and readiness assessments should therefore reflect occupational demands rather than relying exclusively on general fitness benchmarks.

Where the comparison between soldiers and athletes breaks down

Spencer explained that while soldiers are sometimes described as “athletes in a different uniform,” the comparison has limitations.

1. Physical fitness doesn’t automatically translate into operational effectiveness.

Being fit does not necessarily make someone an effective military leader or decision-maker.

2. Military schedules are less predictable.

Professional athletes generally know their competition calendars, while military personnel may face unpredictable missions and extended deployments.

3. Replacing personnel is more difficult.

Professional teams can often rely on a “next man up” approach.

In the military, replacing highly trained personnel can take years.

4. Performance support is organized differently.

Professional teams typically have dedicated performance staff embedded within their organizations.

Military human performance resources may be distributed across units, facilities, and command structures.

5. Injury underreporting is a significant challenge.

Spencer discussed how military personnel may avoid reporting injuries because they fear being removed from duty, losing opportunities, or being perceived as less capable.

This can create pressure to return to duty before they are fully prepared.

He also referenced approximately 2 million annual outpatient visits related to musculoskeletal and other physical health concerns, illustrating the scale of the issue discussed during his presentation.

The exact reporting period and categories behind this figure would need to be confirmed.

Beyond fitness testing: the military’s durability model

One of the most interesting concepts Spencer introduced was a durability model.

Rather than focusing exclusively on traditional fitness testing, the model considers whether military personnel can sustain occupational performance over time.

He described three fundamental questions:

1. Can the soldier do the job?

Does the individual have the physical and operational capabilities required for the occupation?

2. Can the soldier still do the job in year 10?

Can the individual sustain that capability over a long military career?

3. Will the soldier be available on the day that matters?

Is the individual healthy, capable, and ready when the mission requires them?

These questions shift the focus from short-term fitness performance to long-term operational durability.

Connecting performance science with leadership decisions

Spencer also discussed the importance of making performance data useful at different levels of military leadership.

He emphasized several priorities:

• Embedding performance science into operational decision-making.

• Connecting human performance data with commanders’ decisions.

• Measuring capability and availability according to occupational requirements.

• Improving data literacy across military leadership.

• Combining quantitative measurements with qualitative feedback from personnel.

One challenge he identified was that military organizations may collect substantial quantitative data without obtaining equally useful qualitative feedback.

Knowing a soldier’s fitness score doesn’t necessarily explain whether that individual is ready for a specific mission.

The real value comes from combining objective measurements with operational context.

My takeaway: The military has a tremendous opportunity to leverage technologies and methodologies developed in elite sports, including wearables, athlete monitoring, biomechanics, recovery technologies, and AI.

However, these solutions cannot simply be transferred from professional sports into military environments without adaptation.

The objective is not to produce the strongest or fastest soldier. It is to develop personnel who can perform their occupational duties effectively, remain available, and sustain that capability over time.

Dr. Seth Haselhuhn: Mental Performance in Action — Strategies for Training, Competition, and Rehabilitation

Another fascinating presentation at the APSU Health & Performance Summit came from Dr. Seth Haselhuhn, a mental performance specialist working in the military’s Special Operations community and owner of Caliber Development Group.

His session, “Mental Performance in Action: Strategies for Training, Competition, and Rehabilitation,” explored how athletes and tactical professionals can develop the psychological skills needed to perform under pressure, maintain motivation, manage stress, and navigate injury rehabilitation.

One of the most interesting aspects of his presentation was the emphasis on making mental performance training practical and integrating it into everyday coaching.

Rather than treating mental skills as something athletes work on only when they experience difficulties, Seth advocated developing these skills as part of regular training and preparation.

1. Understanding Motivation: Autonomy, Competence, and Relatedness

Seth explained that motivation involves three important psychological components.

Autonomy — Taking Ownership

Autonomy isn’t simply about giving athletes choices. It’s about helping them take ownership of the decisions they make.

Athletes who understand why they are following a particular training program and accept responsibility for their choices may be more engaged in their development.

Competence — Focusing on Execution Rather Than Outcomes

Competence involves developing the skills, techniques, and strategies required to perform effectively.

Instead of focusing exclusively on winning or losing, athletes should direct their attention toward executing the right actions.

Relatedness — Working Toward a Common Goal

Relatedness involves individuals working together toward shared objectives.

This requires a common understanding of goals, consistent communication, and a shared language between athletes, coaches, and performance staff.

My takeaway: Sustainable motivation isn’t simply about encouraging athletes to work harder. It’s about creating an environment where they feel ownership, develop competence, and understand how their efforts contribute to a common objective.

2. Understanding Confidence: Preparation Matters More Than Feelings

One of Seth’s most interesting observations concerned confidence.

He challenged the common belief that athletes must feel confident before they can perform successfully.

Instead, he described confidence as being closely related to our ability to predict future performance based on preparation and competence.

In other words, confidence isn’t simply a feeling. It develops through knowing what needs to be done and having the capabilities to execute it.

Seth discussed several important aspects of preparation.

Physical preparation

• Are you physically capable of completing the task?

• Do you have the right equipment?

• Do you understand how to use that equipment?

• Can you adapt or troubleshoot if something goes wrong?

Social preparation

• Do you understand who you are working with?

• Do you know who or what you are competing against?

• Do you understand who is observing your performance?

• What do these relationships and circumstances mean to you?

He also discussed three components of competence.

Skill: Do you possess the appropriate skill, or do you have time to develop it?

Technique: Can you combine existing skills or adapt techniques to meet the demands of a situation?

Strategy: Do you have alternative approaches when your initial plan doesn’t work?

Seth recommended having more than one strategy available, but generally no more than three.

My takeaway: Confidence is built through preparation, competence, and adaptability rather than relying exclusively on positive thinking.

3. Stress Management: Understanding What We Can Control

Seth described stress as an imbalance between perceived environmental demands and perceived capabilities to respond, particularly when the outcome matters to the individual.

An athlete may experience pressure when they believe the demands of a situation exceed their ability to manage them.

He also discussed how closely individuals connect their personal identity to their goals.

When athletes define themselves exclusively through performance outcomes, setbacks can become more psychologically challenging.

One concept Seth emphasized was the Trichotomy of Control.

The principle is to recognize the difference between what we can control, what we can influence, and what lies outside our control.

Athletes should focus on actions they can control to improve their ability to influence outcomes they cannot fully control.

For example, a basketball player cannot control whether every shot goes in.

However, the player can control preparation, shot selection, technique, and attention during execution.

This shifts the focus away from worrying about outcomes and toward performing the actions that improve the likelihood of success.

4. Self-Regulation: More Than Breathing and Heart Rate Variability

Another interesting topic was self-regulation.

Seth explained that self-regulation can range from relatively simple physiological techniques to more advanced cognitive skills.

At the basic level, athletes can use breathing exercises and heart rate variability (HRV) awareness to support physiological regulation.

However, he emphasized that more advanced self-regulation involves situational awareness.

Athletes need to understand their environment, recognize what is happening, connect that information to their objectives, and select appropriate actions.

This requires combining attention, decision-making, and an understanding of the task.

The goal isn’t simply to become calmer.

It’s to remain capable of recognizing situations and making effective decisions under pressure.

5. Integrating Mental Skills Into Daily Coaching

One of the most practical aspects of Seth’s presentation was his discussion of how coaches can integrate mental performance into daily training.

He connected coaching objectives with three stages of learning.

Cognitive Phase — Process Goals

During the initial learning stage, athletes focus on understanding how individual skills work and how they fit together.

The central questions are:

• How do I perform this movement or skill?

• What are the individual components?

• How do they work together?

The emphasis is on learning and executing the correct process.

Associative Phase — Performance Goals

As athletes become more proficient, they learn when and how to apply different skills.

The key questions become:

• Which process should I use in this situation?

• Can I recognize the situation accurately?

• Can I execute the appropriate response?

This stage involves adapting learned skills to changing circumstances.

Autonomous Phase — Outcome Goals

At the advanced stage, skills become increasingly automatic.

Athletes can execute familiar actions with less conscious attention, allowing them to focus more on tactical decisions and performance outcomes.

Seth also discussed the importance of testing athletes under pressure to understand what breaks down first.

Does the athlete lose tactical awareness, or does psychological regulation deteriorate?

This can reveal information about both athlete development and coaching effectiveness.

6. Coaching Feedback Shapes Athletes’ Beliefs About Pressure

Seth emphasized that perceptions of pressure are often connected to athletes’ belief systems.

Coaches can influence those beliefs through their feedback and communication.

He outlined several practical coaching principles.

Be optimistic, but practical.

Rather than debating whether a glass is half full or half empty, recognize that it is a glass — and refill it.

The message is to focus on constructive action instead of getting stuck in positive or negative interpretations.

Be realistic and objective.

Avoid automatically labeling events as good or bad.

Instead, help athletes recognize what happened and identify the appropriate response.

Stay in the present.

Seth highlighted two useful reminders:

• Be where your feet are.

• W.I.N. — What’s Important Now?

These encourage athletes to focus on the immediate task rather than past mistakes or future outcomes.

Focus on execution.

Reinforce the processes and actions athletes can perform rather than concentrating exclusively on results.

Focus on controllables.

Use what you can control to influence what you cannot.

Separate identity from performance.

Athletes should understand that their personal worth is not defined by individual outcomes.

They can pursue ambitious goals while recognizing that mistakes are part of development.

My takeaway: Mental performance isn’t just about what athletes think. It’s also about how coaches communicate, provide feedback, and structure the learning environment.

7. Mental Toughness Is Primarily About Controlling Attention

Another interesting insight concerned the concept of mental toughness.

Seth discussed 12 attributes associated with an ideal mentally tough performer.

According to the framework he presented:

• Two attributes relate primarily to confidence.

• Two relate primarily to motivation.

• Eight relate primarily to attention control and focus.

This was particularly interesting because mental toughness is often associated with confidence, determination, or the ability to tolerate discomfort.

Seth’s framework places much greater emphasis on the ability to direct and maintain attention.

In practice, this means helping athletes recognize relevant information, ignore distractions, and focus on the appropriate task under pressure.

My takeaway: Mental toughness is not simply about pushing harder. It is largely about maintaining attention and making effective decisions when circumstances become challenging.

8. The Psychology of Injury: Supporting Athletes Before and After Injury

The final major topic was the psychological impact of injuries.

Seth emphasized that injuries can represent a significant turning point in an athlete’s career.

For some athletes, this may be the first time they face a serious disruption to their identity, confidence, and ability to participate in their sport.

This makes the behavior of coaches, medical professionals, and rehabilitation staff particularly important.

Before Injury — Managing Stress, Fatigue, and Attention

Seth discussed how high stress, physical fatigue, and difficulties controlling attention may contribute to increased injury risk.

He emphasized the importance of:

• Developing life skills.

• Managing physical and psychological energy expenditure.

• Controlling the complexity of training.

• Teaching athletes to direct their attention effectively.

The broader message was that injury prevention should consider psychological demands alongside physical preparation.

After Injury — Managing Emotional Responses and Rehabilitation

Seth discussed how injured athletes may experience grief-like emotional responses.

Rather than dismissing those emotions, coaches and medical staff should recognize that they are part of the athlete’s experience.

He emphasized the importance of establishing realistic, constructive rehabilitation goals that allow athletes to experience progress and maintain a sense of achievement.

Anxiety and a lack of trust can also complicate rehabilitation.

This makes communication between athletes, coaches, and medical professionals essential.

Rehabilitation should therefore address not only physical recovery but also the athlete’s confidence, expectations, and psychological readiness to return.

💡 My Biggest Takeaways From Dr. Haselhuhn’s Presentation

1. Mental performance should be trained every day. Psychological skills should be integrated into coaching and practice rather than treated as separate interventions.

2. Motivation depends on ownership, competence, and shared purpose. Athletes need to understand their choices, develop the appropriate skills, and feel connected to common goals.

3. Confidence is built through preparation. Competence, experience, and adaptability matter more than simply trying to feel confident.

4. Stress management is about controlling attention and responses. Athletes should focus on what they can control and influence.

5. Coaching feedback has a significant psychological impact. The language coaches use can influence athletes’ beliefs, attention, and responses to pressure.

6. Mental toughness is closely connected to focus. The ability to direct attention toward relevant information is critical during competition.

7. Injury rehabilitation must address psychological as well as physical recovery. Anxiety, trust, identity, and motivation can influence how athletes engage with rehabilitation.

My overall takeaway: Sports performance departments invest heavily in technologies that measure strength, power, movement, workload, and physiological readiness.

However, athletes must also develop the psychological skills required to interpret situations, manage pressure, make decisions, and execute effectively.

The next evolution in human performance may come from integrating physical performance, cognitive skills, mental preparation, and psychological well-being into a more comprehensive approach to athlete development.

🎤 Fireside Chat with Gunnar Peterson: From Hollywood to the NBA

One of the highlights of the ASPU Summit in Nashville was a fireside chat featuring Gunnar Peterson, one of the most recognized strength and conditioning coaches in the fitness industry.

With more than 30 years of experience, Peterson has built a career working with elite professional athletes, Hollywood celebrities, and leading sports organizations.

Who Is Gunnar Peterson?

A graduate of Duke University and a Certified Strength and Conditioning Specialist (CSCS), Peterson is widely known for his expertise in functional training, strength development, and individualized conditioning programs.

Throughout his career, he has worked with athletes across the NBA, NFL, NHL, MLB, professional boxing, tennis, and collegiate sports.

His celebrity clientele has also included some of Hollywood’s biggest names, notably Dwayne “The Rock” Johnson, as well as the Kardashian family and other high-profile entertainers.

His ability to work with both elite athletes and entertainment personalities has given him a distinctive perspective on training, physical preparation, consistency, and long-term performance.

His Role With the Los Angeles Lakers

In 2017, Peterson was appointed Director of Strength and Endurance Training for the Los Angeles Lakers (NBA).

In this position, he was responsible for designing and implementing strength and conditioning programs to help players maintain elite physical performance throughout the demanding 82-game NBA regular season.

His responsibilities included individualized strength programs, conditioning, physical preparation, and collaboration with the team’s performance staff.

His experience with the Lakers offered a firsthand perspective on the physical and mental demands of professional basketball, including the challenges of balancing training, recovery, travel, and competition.

Why His Perspective Matters

Peterson’s career illustrates the importance of combining scientific principles with practical coaching experience.

Whether preparing an NBA player for a long competitive season or helping an actor meet the physical demands of a film role, effective training requires understanding the individual’s objectives, physical capabilities, schedule, and recovery needs.

His background also highlights the importance of communication, consistency, athlete engagement, and adapting training programs to individual circumstances.

🎥 Upside Video Interviews: Sports Technology Companies Exhibiting at the Summit

Beyond the presentations, another highlight of the APSU Health & Performance Summit was the opportunity to meet with sports technology companies developing solutions for athlete performance, training, rehabilitation, and recovery.

At Upside, one of our goals is to connect innovative technology companies with practitioners across professional sports, collegiate athletics, and military human performance.

During the summit, we interviewed several exhibiting companies to learn more about their technologies, product developments, and how their solutions can help performance and medical staff.

Watch our YouTube interviews with the exhibiting companies below.

🔬 Myocene — Measuring Muscle Fatigue to Optimize Performance

Website: Myocene

Myocene develops muscle fatigue assessment technology designed to help practitioners better understand athletes’ muscular fatigue and recovery status.

Its technology aims to support more informed decisions about training loads, recovery strategies, and rehabilitation.

🎥 YouTube Interview: Myocene

💪 DetecFit — Portable Strength Assessment and Velocity-Based Training

Website: DetecFit

DetecFit develops portable technologies for strength assessment and velocity-based training (VBT).

Its solutions aim to help strength coaches, sports scientists, and rehabilitation specialists assess athletes’ physical capabilities and monitor training performance.

🎥 YouTube Interview: DetectFit

🏋️ Aris Training — Innovation in Strength and Performance Training

Website: Aris Training

Aris Training develops innovative strength and performance training solutions designed to support athlete development.

The company focuses on helping practitioners optimize training and improve the way athletes develop physical capabilities.

🎥 YouTube Interview: Aris Training

📊 VALD — Performance Assessment and Athlete Monitoring

Website: VALD

VALD offers a range of performance assessment technologies used by sports organizations, rehabilitation professionals, and performance specialists.

Its portfolio includes force plates, dynamometers, and athlete monitoring tools designed to provide objective information about strength, movement, and physical performance.

🎥 YouTube Interview: VALD

⚡ QuickBoard — Reaction Time, Agility, and Motor Learning

Website: QuickBoard

QuickBoard develops sensor-based technology designed to assess and train reaction time, agility, coordination, and motor learning.

Its solutions are used in performance training and rehabilitation environments to help practitioners measure physical responsiveness and incorporate cognitive challenges into movement exercises.

QuickBoard was particularly relevant to the summit because Dr. Bill Burgos discussed using QuickBoard during NBA game-day routines to help assess player readiness.

🎥 YouTube Interview: QuickBoard

Upside Take: Technology Must Solve Real Problems

One of the most interesting aspects of meeting these companies was seeing their different approaches to supporting athlete performance.

Some focus on muscle fatigue and recovery. Others specialize in strength assessment, velocity-based training, reaction time, motor learning, or objective performance monitoring.

Despite their different technologies, they share a common challenge:

How do you translate measurements into actionable insights that help practitioners make better decisions?

Throughout the weekend, that question came up repeatedly.

Whether it was Chris Dunaway discussing force plate assessments with young Dodgers prospects, Bill Burgos explaining game-day readiness testing in the NBA, or Spencer Posey discussing operational readiness in the military, the message was consistent.

The value of performance technology is not simply in what it measures, but in how those measurements improve training, recovery, rehabilitation, and readiness.

A big thank you to the teams behind Myocene, DetectFit, Aris Training, VALD, and QuickBoard for taking the time to speak with Upside and share their innovations.

Sports Psychology Is Becoming Essential in Collegiate Athletics

Another important theme from the weekend was the growing role of sports psychology.

Student-athletes face considerable demands related to academics, competition, injuries, performance expectations, and personal well-being.

Mental performance specialists and sports psychologists can support:

• Confidence and resilience.

• Stress management.

• Injury rehabilitation.

• Performance under pressure.

• Emotional well-being.

• Athlete development.

I expect mental performance support to become increasingly integrated into collegiate and professional sports performance departments.

The industry is gradually moving toward a more comprehensive approach to athlete health that considers both physical and psychological factors.

8. Three Broader Trends Across Elite Sports

My visit to Vanderbilt and the APSU summit reinforced several trends I’ve been observing through conversations with practitioners across the NBA, NFL, MLB, NHL, MLS, NCAA, European professional sports, and military human performance.

Teams want technologies that save time

Practitioners already have access to enormous amounts of data.

They don’t necessarily need another dashboard.

They need technologies that:

• Automate repetitive tasks.

• Integrate with existing systems.

• Reduce administrative workload.

• Provide actionable insights.

• Help them make better decisions.

Saving practitioners time is becoming an important competitive advantage for sports technology companies.

Technology vendors need to solve real problems

One of the biggest mistakes sports-tech startups make is focusing too heavily on product features.

Teams want to understand what problem a technology solves and whether it improves their existing workflows.

The most successful vendors begin by understanding practitioners’ needs rather than immediately pitching their products.

MLS remains one of the most technology-friendly leagues I’ve encountered

From my experience working with MLS clubs, many organizations are particularly open to evaluating emerging technologies and collaborating with startups.

This creates opportunities for innovation across athlete monitoring, biomechanics, rehabilitation, recovery, and performance analytics.

My Biggest Takeaways From the Weekend

1. NCAA performance facilities are becoming increasingly sophisticated.

Some collegiate programs have access to technologies comparable to those used by professional sports organizations.

2. University AI labs could become major innovation hubs.

Collaboration between athletic departments and academic researchers could accelerate new applications in biomechanics, athlete monitoring, and performance analysis.

3. More data doesn’t necessarily mean better decisions.

The Dodgers’ focus on a small number of meaningful performance metrics is an important lesson.

4. Game-day readiness monitoring can be practical and efficient.

Bill Burgos’s use of QuickBoard and force plates illustrates how objective assessments can fit into NBA performance routines.

5. Nutrition education is just as important as nutrition planning.

Helping athletes understand how to fuel themselves is essential, especially for younger players.

6. Training must reflect the demands of competition or occupation.

NBA athletes already accumulate substantial physical loads, while military personnel face unpredictable operational demands.

7. Availability is a critical performance outcome.

Spencer Posey’s presentation reinforced the importance of keeping personnel healthy, capable, and ready when needed.

8. Long-term durability deserves more attention.

The objective should not simply be maximizing performance today, but sustaining physical capability throughout a career.

9. Sports psychology and staff well-being are increasingly important.

Supporting both athletes and practitioners is essential for sustainable performance.

10. Sports technology must deliver actionable insights.

The exhibiting companies demonstrated different approaches to performance assessment, training, and recovery. Their long-term value will depend on how effectively those measurements support practitioners’ decisions.

Final Thoughts

One of the biggest lessons from this weekend is that elite sports organizations and military human performance programs don’t necessarily need more technology. They need better ways to use the technologies and data they already have.

Chris Dunaway demonstrated how the LA Dodgers use portable force plates, physical assessments, and advanced data systems to evaluate and develop baseball players.

Dr. Bill Burgos showed how NBA performance departments combine game-day readiness testing, individualized training, nutrition, recovery, and athlete education to support players throughout a demanding season.

Sgt. Spencer Posey highlighted how military organizations are adopting sports science principles while focusing on operational readiness, availability, and long-term durability.

Vanderbilt illustrated how NCAA athletic departments are investing in sophisticated performance facilities and exploring the potential of AI and academic research.

And the exhibiting companies — Myocene, DetectFit, Aris Training, VALD, Teambuildr, and QuickBoard — offered an opportunity to see technologies addressing different aspects of performance assessment, training, and recovery.

Despite the differences between professional sports, collegiate athletics, and military operations, the same principle applies:

The next competitive advantage in human performance will come from combining technology, scientific research, data, and practitioner expertise to make better decisions, not simply collecting more information.

A fascinating weekend of learning, exchanging ideas, and discovering new technologies with practitioners and innovators across professional sports, collegiate athletics, and military human performance.

Until next year.

Best,

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Upside Global | Sports Performance & Technology Analysis | October 2026

Introduction: Performance Centers Are Becoming Strategic Assets

As professional sports become increasingly global, access to high-quality training facilities away from home is becoming an important operational advantage.

From the Red Bull Athlete Performance Center in Los Angeles to the New Zealand Campus of Innovation and Sport (NZCIS), leading performance centers combine strength and conditioning, sports science, rehabilitation, recovery, nutrition and athlete monitoring under one roof.

For decades, professional sports teams have invested heavily in their own training facilities, performance laboratories, recovery centers and medical infrastructure.

Today, many elite organizations operate integrated performance environments where coaches, sports scientists, physiotherapists, nutritionists and medical staff work together to optimize athlete performance.

However, when teams travel domestically or internationally, maintaining access to the same level of infrastructure can become challenging.

An NBA team traveling to Los Angeles, an NHL team playing several consecutive road games, an MLS club visiting New York, or an international rugby team preparing for a competition in Europe may need access to specialized training equipment, rehabilitation facilities, recovery technologies and appropriate training spaces.

Finding these facilities is often a manual, time-consuming process involving calls, emails and personal introductions.

This creates an opportunity to build a more connected global ecosystem of sports performance centers, making it easier for professional teams to discover, evaluate and access the facilities they need wherever they compete.

Importantly, not all leading performance centers are commercially accessible. Some are privately operated by professional clubs or sports organizations, while others actively welcome visiting teams and athletes.

This analysis explores the world’s leading performance centers, why they matter, the technologies shaping their evolution, and how teams can make better decisions when selecting facilities while traveling.

Why Professional Teams Need Access to Performance Centers When Traveling

Professional sports organizations increasingly operate across multiple cities, countries and continents.

Whether competing in domestic leagues, international tournaments, preseason tours or training camps, teams must maintain consistent approaches to physical preparation, rehabilitation and recovery.

Several factors explain why access to high-quality performance centers is becoming increasingly important.

Maintaining training continuity

Professional athletes follow carefully designed training programs throughout the season.

However, hotel gyms rarely provide the space, equipment or specialized technologies required by professional sports teams.

Access to a nearby performance center allows practitioners to maintain strength and conditioning programs, conduct training sessions and manage individual athlete workloads.

For example, an NBA team on a five-game road trip may need a facility equipped with squat racks, free weights, resistance machines and force plates to maintain its normal training protocols.

Supporting rehabilitation and return to play

Injured athletes often require specialized rehabilitation equipment, treatment rooms and assessment technologies.

When traveling, teams may need access to facilities that support rehabilitation without disrupting the athlete’s recovery program.

This can include isometric strength assessment, movement analysis, neuromuscular testing and progressive loading.

Optimizing recovery between games

Teams competing in congested schedules need appropriate recovery infrastructure.

Hydrotherapy pools, cold-water immersion, compression systems, physiotherapy areas and dedicated recovery spaces can support established recovery routines.

This is particularly relevant for NBA, NHL, MLS and rugby teams managing frequent travel and limited recovery time.

Reducing logistical complexity

Travel time is an important consideration.

A performance center located 15 minutes from a team’s hotel or stadium may be considerably more practical than one located an hour away.

Reducing transportation time can create additional opportunities for treatment, recovery, meetings and rest.

Accessing specialized technologies

Some performance centers provide access to technologies that may not be available in hotels or temporary training facilities.

These include force plates, GPS systems, biomechanics laboratories, velocity-based training devices and recovery technologies.

Supporting international training camps

National teams and professional clubs traveling overseas may require integrated facilities for several days or weeks.

A center combining training fields, gyms, accommodation, nutrition, medical services and recovery infrastructure can significantly simplify camp logistics.

Main Use Cases for Teams Using Performance Centers

Performance centers can support a wide range of operational and performance requirements.

The requirements vary considerably depending on the sport.

An MLS team may prioritize access to training pitches, an NBA team may need a regulation basketball court, while an NHL team may require ice time in addition to strength and conditioning facilities.

Therefore, selecting the right performance center requires understanding both the team’s sporting needs and the facility’s capabilities.

Leading Sports Performance Centers Around the World

The following facilities represent notable examples of elite sports performance infrastructure.

They have been selected based on their facilities, sports-science capabilities, reputation, integrated services and relevance to professional teams.

This is an editorial selection rather than a definitive ranking. Access, pricing and availability should be confirmed directly.

1. Red Bull Athlete Performance Center — Los Angeles, USA

Website: Red Bull Performance

Red Bull’s Athlete Performance Center in the Los Angeles area is an example of an integrated elite-performance environment.

The facility brings together strength and conditioning, sports medicine, physiotherapy, performance profiling, nutrition, mental performance and recovery services.

Its multidisciplinary approach emphasizes individualized athlete development and collaboration between performance specialists.

Red Bull also operates a wider high-performance ecosystem, including facilities and expertise in Europe.

Key capabilities:

• Strength and conditioning

• Sports medicine and physiotherapy

• Performance assessments

• Nutrition and recovery support

• Mental performance

• Individualized athlete development

Best suited for: Elite athletes requiring integrated performance services.

Access: Primarily serves Red Bull-affiliated athletes and teams. External commercial access should not be assumed.

2. New Zealand Campus of Innovation and Sport (NZCIS) — Upper Hutt, New Zealand

Website: NZCIS

NZCIS is one of the most relevant examples of a modern performance campus designed to support professional teams, international training camps and athlete development.

Located near Wellington, the campus combines extensive training infrastructure with accommodation, nutrition, sports science and recovery facilities.

Its integrated approach makes it attractive for professional rugby teams, football clubs, national teams and other elite sporting organizations.

NZCIS has worked with leading sports organizations, including New Zealand Rugby.

Key capabilities:

• High-performance strength and conditioning facilities

• Outdoor training fields

• Recovery and rehabilitation areas

• Hydrotherapy and other recovery technologies

• Performance analysis and sports-science infrastructure

• Accommodation and dining

• Meeting and conference facilities

Best suited for: International rugby teams, football clubs, AFL teams and organizations planning extended training camps.

Access: NZCIS welcomes visiting teams and offers integrated training arrangements.

3. St. George’s Park — England

Website: England Football – St. George’s Park

St. George’s Park is the home of England’s national football teams and one of Europe’s leading football performance campuses.

Located in Staffordshire, the facility combines football pitches, indoor training areas, sports science, rehabilitation, strength and conditioning and accommodation.

The campus has also hosted professional football clubs preparing for domestic and international competitions.

Key capabilities:

• Outdoor and indoor football pitches

• Strength and conditioning

• Sports medicine

• Rehabilitation and recovery

• Performance analysis

• Accommodation and catering

• Team meeting facilities

Best suited for: Professional football clubs, national teams and preseason training camps.

Access: Offers training packages for visiting teams, subject to availability.

4. Aspire Zone and Aspetar — Doha, Qatar

Websites: Aspire Zone | Aspetar

Aspire Zone is an extensive sports performance ecosystem combining training facilities, sports science, education and specialized medical services.

Aspire Academy provides elite training infrastructure across multiple sports, while Aspetar is internationally recognized for its focus on sports medicine, rehabilitation and athlete performance.

The wider campus has supported international teams and major sporting events.

Key capabilities:

• Strength and conditioning

• Football training facilities

• Biomechanics and performance assessment

• Sports medicine and rehabilitation

• Recovery services

• Training camps

• Sports-science expertise

Best suited for: International teams, elite athletes, rehabilitation programs and major-event preparation.

Access: Training camp and international athlete services are available through relevant operators, subject to eligibility and arrangements.

5. IMG Academy — Bradenton, Florida, USA

Website: IMG Academy

IMG Academy is a major multisport training campus supporting athlete development across basketball, football, soccer, tennis, baseball and other sports.

Its facilities include sport-specific training environments, strength and conditioning spaces, performance services and accommodation.

IMG Academy has also hosted professional teams and training camps.

Key capabilities:

• Multisport training facilities

• Strength and conditioning

• Sports performance services

• Athlete development

• Accommodation

• Team training camps

Best suited for: Professional and collegiate teams, preseason preparation and individual athlete development.

Access: Team training and camp opportunities are available, depending on scheduling and requirements.

6. Australian Institute of Sport (AIS) — Canberra, Australia

Website: Australian Institute of Sport

The Australian Institute of Sport is a major component of Australia’s elite sports performance ecosystem.

Its Canberra campus combines training facilities, athlete services, sports science and recovery infrastructure.

The institute supports national sporting organizations and Olympic and Paralympic performance programs.

Key capabilities:

• High-performance training

• Sports science

• Strength and conditioning

• Recovery and rehabilitation

• Multisport infrastructure

• Athlete accommodation

Best suited for: National teams, Olympic sports and multisport training camps.

Access: Selected sporting groups can access facilities through appropriate booking arrangements.

7. INSEP — Paris, France

Website: INSEP

France’s National Institute of Sport, Expertise and Performance is one of Europe’s leading elite-sport institutions.

Located in Paris, INSEP integrates athlete development, performance science, sports medicine, research and specialized training infrastructure.

The institute plays an important role in preparing French athletes for major international competitions.

Key capabilities:

• Elite athlete development

• Sports science and research

• Strength and conditioning

• Rehabilitation

• Biomechanics

• Olympic and Paralympic preparation

Best suited for: National federations, Olympic programs and specialized athlete development.

Access: Primarily supports elite-sport programs. Visiting-team access requires direct coordination.

8. EXOS — Phoenix, Arizona, USA

Website: EXOS

EXOS is known for its integrated approach to human performance, combining strength and conditioning, movement development, physical therapy, nutrition and performance coaching.

Its facilities and services have supported professional athletes across multiple sports.

Key capabilities:

• Strength and conditioning

• Movement assessment

• Physical preparation

• Rehabilitation

• Nutrition

• Individualized performance programs

Best suited for: Individual athletes, offseason preparation and specialized training programs.

Access: Team and athlete arrangements should be confirmed directly.

9. Paris Saint-Germain Campus — Poissy, France

Website: PSG Campus

Paris Saint-Germain’s training campus demonstrates how major professional clubs are investing in integrated performance infrastructure.

The campus brings together football training, sports medicine, recovery, strength and conditioning and player development.

Its design supports collaboration between coaching, medical and performance departments.

Key capabilities:

• Football training pitches

• Strength and conditioning

• Medical and rehabilitation facilities

• Recovery infrastructure

• Player development

• Integrated performance services

Best suited for: Benchmarking elite club infrastructure and multidisciplinary performance environments.

Access: Primarily a private club facility rather than a publicly advertised rental center.

Comparing the Leading Performance Centers

The Growing Importance of Technology in Elite Sports Performance Centers

One of the biggest transformations in elite sports performance centers over the past decade has been the integration of advanced technologies into training, rehabilitation, recovery and athlete monitoring.

Today, the best performance centers are no longer simply facilities equipped with weights, training fields and treatment rooms.

They are increasingly becoming technology-driven performance hubs, where coaches, sports scientists, physiotherapists and medical teams collect objective data, evaluate athletes and make more informed decisions.

For professional teams traveling domestically or internationally, access to these technologies can be particularly valuable.

Rather than interrupting their normal assessment and monitoring routines, visiting teams can potentially maintain continuity by using compatible equipment available at local performance centers.

5.1 Force Plates and Strength Assessment Technologies

Solutions from companies such as VALD, Hawkin Dynamics and Kistler allow practitioners to assess force production, asymmetries, jump performance and other neuromuscular characteristics.

These technologies can help teams monitor physical capabilities, evaluate rehabilitation progress and support training decisions.

Example: An NBA team traveling for several consecutive games could use compatible force plates at a local performance center to conduct its established jump-testing protocol.

This could help practitioners maintain consistency in their monitoring processes without transporting additional equipment.

5.2 GPS Tracking and Athlete Monitoring Systems

Wearable technologies from companies such as Catapult and STATSports help practitioners monitor external training loads, movement demands and physical performance.

Access to appropriate training spaces and compatible monitoring infrastructure can help visiting teams continue collecting performance data.

For example, a professional rugby team training overseas may need access to outdoor fields where its GPS tracking systems can operate effectively.

5.3 Velocity-Based Training (VBT) and Strength Monitoring

VBT solutions from companies such as Perch, Vitruve and DetecFit allow coaches to monitor movement velocity during resistance training.

These technologies can support individualized training prescriptions, track performance changes and provide immediate feedback during strength sessions.

Portable VBT devices are especially relevant for traveling teams because they can be used in different training environments.

Example: An NHL team on a road trip could use a portable VBT device at a local performance center to monitor selected strength exercises without requiring permanent installation.

5.4 Biomechanics and Motion Capture Technologies

Technologies from companies such as Qualisys, Vicon and Theia Markerless support detailed movement assessments.

Applications include:

• Running mechanics and gait analysis

• Movement screening

• Rehabilitation assessments

• Return-to-play evaluations

• Sport-specific skill development

• Movement efficiency and technique analysis

Some advanced performance centers operate dedicated biomechanics laboratories, while others use portable or markerless motion capture systems.

For visiting teams, access to these technologies may be particularly useful when evaluating injured athletes or conducting specialized assessments.

5.5 Recovery and Rehabilitation Technologies

Recovery is another area where technology is playing an increasingly important role.

Performance centers may provide access to hydrotherapy, compression systems, cryotherapy, neuromuscular stimulation and specialized rehabilitation equipment.

Technologies from companies such as Normatec and Game Ready are examples of solutions used in recovery and rehabilitation settings.

For teams managing congested schedules, access to appropriate recovery infrastructure can help maintain established post-game routines.

However, teams should distinguish between the availability of a recovery technology and the scientific evidence supporting its use for a specific outcome.

5.6 Athlete Management Systems (AMS) and AI-Powered Analytics

Platforms such as Smartabase, Kitman Labs and TeamBuildr help organizations manage training information, athlete monitoring, performance assessments and strength programs.

As performance centers become more digitally connected, an important opportunity is to facilitate secure data exchange between facilities and visiting teams.

For example, a visiting team could conduct a strength assessment at an external facility and integrate the results into its existing athlete monitoring workflow, provided the equipment, software and data-sharing arrangements are compatible.

AI could further support practitioners by helping analyze performance trends, organize assessment results and identify information requiring closer review.

5.7 Why Technology Matters When Selecting a Performance Center

For professional teams, the availability of advanced technologies can influence which performance center they choose when traveling.

Consider two facilities located 15 minutes from a team’s hotel.

The first offers a traditional gym with free weights, resistance machines and basic recovery equipment.

The second provides similar equipment but also offers force plates, VBT systems, rehabilitation technology, movement assessment tools and dedicated sports-science support.

Depending on the team’s objectives, the second facility could offer significantly more value, particularly if players require physical assessments, individualized rehabilitation or monitoring during a road trip.

However, having more technology does not automatically make a facility better.

The equipment must be appropriate for the team’s needs, properly maintained and supported by qualified personnel.

Measurement consistency, calibration, data security and compatibility with the team’s existing systems are equally important.

5.8 Technology as a New Selection Criterion for Traveling Teams

As part of the global performance-center database we are exploring for the Upside AI Assistant, we believe technology availability should become a major searchable category.

In addition to location, pricing, facility size and amenities, teams could search for centers based on specific technologies.

For example:

• “We’re playing in Los Angeles this weekend. Which performance centers near LAX have VALD force plates and recovery facilities?”

• “Our rugby team is traveling to Paris. Which facilities offer indoor training areas, GPS-compatible training spaces and hydrotherapy?”

• “We’re visiting Melbourne next month. Can you recommend a performance center with VBT equipment, a biomechanics lab and rehabilitation facilities?”

• “Our NHL team needs a strength and conditioning facility near our hotel with sufficient equipment for 25 players. Which facilities can accommodate us?”

The AI Assistant could identify relevant centers, compare their capabilities and connect the visiting team directly with the facility’s management to discuss availability, pricing and booking arrangements.

To support this capability, a useful database should capture not only the technology category but also the equipment manufacturer, model, available quantity, calibration status, software compatibility and whether visiting teams can use the equipment independently or require on-site staff.

5.9 A New Opportunity for Performance Centers and Technology Vendors

This evolution also creates potential opportunities for sports-tech companies.

Performance centers can become demonstration and testing environments where practitioners experience new technologies firsthand.

For example, a visiting professional team could use a force plate system, portable VBT device or biomechanics solution during a training session and subsequently explore whether that technology would be useful at its own facility.

For technology vendors, partnerships with performance centers could provide additional opportunities for product exposure, practitioner feedback and commercial introductions.

For facility operators, investing in the right technologies could help differentiate their services and attract more professional teams, provided the investment aligns with customer demand and operating costs.

The next generation of performance centers will not be defined simply by how much equipment they own, but by how effectively they combine technology, expertise and actionable data to support athlete performance.

Future Trends Shaping Sports Performance Centers

Several trends are likely to influence the development of performance centers over the coming years.

Trend 1: Greater Integration of Sports Science and Technology

Performance centers will increasingly combine strength and conditioning equipment with advanced assessment technologies.

Force plates, VBT systems, motion capture, wearable sensors and AI-powered analytics could become more common components of high-performance facilities.

The objective will be to generate more actionable insights rather than simply collect additional data.

Trend 2: Training, Rehabilitation and Recovery Under One Roof

Facilities such as NZCIS and Aspire demonstrate the benefits of integrating multiple services.

Teams increasingly value environments where athletes can train, recover, receive treatment and access performance expertise without traveling between multiple locations.

This approach can improve operational efficiency and simplify coordination between departments.

Trend 3: AI-Powered Facility Discovery and Matching

Finding an appropriate performance center remains a fragmented process.

Teams often rely on personal networks, online searches and direct introductions.

AI-powered discovery platforms could simplify this process by matching teams with facilities based on location, sport, equipment, services, availability and pricing.

Trend 4: More Flexible Access for Visiting Teams

Performance centers may increasingly offer short-term rentals, team packages and specialized services for visiting professional organizations.

This could create additional revenue opportunities for facility operators while giving traveling teams more flexibility.

Trend 5: Greater Collaboration Between Facilities and Sports-Tech Vendors

Performance centers could become important partners for technology vendors seeking to demonstrate their products to professional practitioners.

These partnerships may include product testing, research collaborations, equipment demonstrations and commercial introductions.

Trend 6: More Connected Performance Data

As athletes train across multiple locations, interoperability between technologies and athlete management systems will become increasingly important.

Teams may place greater emphasis on facilities that support standardized testing protocols, secure data transfer and integration with existing monitoring platforms.

Upside AI Assistant: Helping Teams Find and Connect with Performance Centers Worldwide

At Upside, we plan to soon launch a new capability for our Upside AI Assistant designed to help professional and collegiate teams discover, compare and connect with leading performance centers worldwide.

The concept is to build a global database of facilities, including information about their locations, amenities, equipment, technologies, pricing and availability.

The goal is to make it easier for teams to find suitable training environments when traveling for games, tournaments and training camps.

How It Would Work

Imagine an MLS team traveling to Los Angeles for a weekend game.

A performance director could ask:

“We’re playing in Los Angeles this weekend and need a performance center near LAX with strength-training equipment, recovery facilities and enough space for 25 players. Which facilities would you recommend?”

The AI Assistant could then:

1. Identify suitable performance centers based on the team’s requirements.

2. Compare available facilities based on location, travel time, amenities, technology and pricing.

3. Provide relevant facility information, including websites, equipment and booking contacts.

4. Connect the team directly with the selected performance center to discuss availability and arrange access.

This would move the experience beyond searching for facilities and toward helping teams coordinate their actual training needs.

Building a Global Performance Center Database

We envision including the following parameters:

Potential Benefits for Teams

• Reduce the time spent searching for training facilities.

• Identify centers that match sport-specific requirements.

• Compare amenities and technologies before booking.

• Maintain training and rehabilitation routines while traveling.

• Access appropriate facilities in unfamiliar cities.

• Connect directly with facility operators.

Potential Benefits for Performance Centers

• Increase visibility among professional and collegiate teams.

• Generate introductions to visiting organizations.

• Promote specialized technologies and services.

• Attract potential new customers.

• Build relationships with practitioners and performance departments worldwide.

This represents a potential new direction for the Upside AI Assistant, extending its existing focus on sports technology scouting into performance infrastructure discovery.

Recommendations for Professional Teams

Based on the facilities examined and the operational requirements of traveling teams, several recommendations emerge.

1. Build a Database of Trusted Performance Centers

Teams should maintain a shortlist of reliable training facilities in cities they visit regularly.

This database should include locations, contacts, amenities, technologies, pricing and access requirements.

2. Prioritize Travel Time and Logistics

Distance alone is not enough.

Teams should consider traffic, proximity to hotels and stadiums, transportation arrangements and available training windows.

3. Evaluate Technology Availability

Before booking, teams should verify whether the facility offers the specific technologies required for their training and assessment protocols.

This may include force plates, VBT devices, GPS systems, biomechanics equipment and rehabilitation technologies.

4. Confirm Equipment Compatibility

Not all systems produce directly comparable measurements.

Teams should verify equipment models, testing protocols, software compatibility and data-export capabilities before relying on an external facility for performance monitoring.

5. Consider the Entire Performance Environment

A facility with excellent strength equipment may lack treatment rooms, recovery areas or sufficient space for a full team.

Teams should evaluate the complete range of services rather than focusing on one feature.

6. Verify Pricing and Availability

Teams should confirm rental rates, staffing requirements, exclusive-use options, cancellation policies and additional service charges.

7. Establish Relationships with Facility Operators

Building relationships with local performance centers can simplify future travel arrangements and provide access to trusted contacts when unexpected needs arise.

8. Prioritize Data Security and Athlete Privacy

When using external technologies, teams should establish clear procedures for collecting, storing, accessing and transferring athlete data.

Confidentiality and control over sensitive performance information should be considered during facility selection.

9. Consider Integrated Training Camp Facilities

For longer stays, facilities combining training, accommodation, nutrition, recovery and medical services may offer logistical advantages.

10. Use a Structured Facility Evaluation Framework

Conclusion: Toward a More Connected Global Performance Ecosystem

The world’s leading sports performance centers demonstrate how much elite training infrastructure has evolved.

Facilities such as Red Bull’s Athlete Performance Center, NZCIS, St. George’s Park, Aspire Zone, IMG Academy and the Australian Institute of Sport illustrate different approaches to integrating physical preparation, sports science, rehabilitation, recovery and athlete development.

Technology is becoming an increasingly important part of this evolution.

Force plates, wearable sensors, VBT systems, biomechanics technologies, athlete management platforms and AI-powered analytics are helping practitioners collect objective data and make more informed decisions.

However, the next major opportunity may not be building larger or more technologically advanced facilities. It may be making existing performance infrastructure easier for professional teams to discover, evaluate and access.

For an MLS team visiting another city, an NHL club on a road trip, an international rugby squad preparing for a test match, or an NBA team organizing offseason training, quickly identifying a suitable performance center could reduce logistical complexity and help maintain training continuity.

Looking ahead, a connected global ecosystem of performance centers, supported by better facility data, technology integration, AI-powered discovery and direct introductions, could transform how teams organize training and recovery away from home.

At Upside, we believe there is an opportunity to help build that ecosystem through our AI Assistant, connecting professional teams with the right performance centers, technologies and people wherever they compete.

Ultimately, the future of elite sports performance will depend not only on the technologies and facilities teams own, but also on their ability to access the right expertise and infrastructure anywhere in the world.

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October 19–25, 2026

Another exciting week ahead at the intersection of sports, technology, AI, investment, and business!

This week, we’ll be following major developments across professional sports, artificial intelligence, healthcare technology, and the broader investment landscape.

From the start of the NBA regular season and major technology earnings to new opportunities in AI-powered athlete monitoring, there will be plenty to watch.

On the business side, companies including Netflix, Meta, Tesla, IBM, and major semiconductor manufacturers are scheduled to report earnings. Their results could provide valuable insights into AI investment, digital infrastructure, and the broader technology market.

And at Upside, we have two exciting podcasts coming up:

🎙️ An NBA Group Podcast bringing together leading NBA practitioners to discuss best practices, player performance, sports science, rehabilitation, and emerging technologies.

🎙️ An interview with Dr. Meshari Alwashmi, CEO of AmplifAI Health, to explore the company’s AI-powered thermography technology and its potential applications in sports medicine, athlete monitoring, and healthcare.

🏟️ Special Nashville Trip & ASPU Summit Recap: We’ll share key takeaways from our recent visits with Nashville SC (MLS), the Nashville Predators (NHL), and Vanderbilt University (NCAA), as well as insights from the ASPU Summit.

Our goal with this recap is not to disclose confidential information or reveal team-specific strategies, but rather to identify emerging industry trends, best practices, common challenges, and promising innovations across professional and collegiate sports.

By connecting with practitioners across different leagues and organizations, we aim to highlight valuable lessons and opportunities that can benefit the broader sports performance community.

🚀 Upside VIP Lunch in Atlanta: We’ll also announce additional sports-tech companies selected to present at our upcoming VIP Lunch with MLS and NWSL practitioners on December 18 at the U.S. Soccer Headquarters in Atlanta.

Here’s what we’ll be following next week.

🏟️ SPORTS + TECHNOLOGY CONFERENCES

📺 SPORTEL Monaco 2026 — Monaco | October 19–21

SPORTEL Monaco brings together leading organizations across sports broadcasting, media rights, technology, and digital content.

The event attracts sports leagues, broadcasters, technology companies, investors, and media organizations looking to explore the future of sports content and distribution.

Key themes include artificial intelligence in broadcasting, digital platforms, sports media rights, and emerging technologies.

Upside Take: The sports technology market extends well beyond athlete performance.

AI-powered video analysis, computer vision, automated content production, and real-time data processing are creating opportunities across both sports performance and sports media.

Interestingly, some of the same technologies used to analyze athletes’ movements can also be applied to broadcasting, officiating, and fan engagement.

What to watch: AI-powered broadcasting, computer vision, sports media investment, digital platforms, and emerging technology partnerships.

🏀 PROFESSIONAL SPORTS: NBA SEASON BEGINS

🏀 NBA Regular Season Opening Week | October 20–25

The start of the NBA regular season represents an important moment for teams, players, and performance departments.

After months of offseason training, rehabilitation, preseason preparation, and roster adjustments, teams transition into the demands of an 82-game regular season.

For performance practitioners, this means shifting priorities toward maintaining player health, managing training loads, optimizing recovery, and minimizing injury risk.

Some of the questions worth exploring include:

• How are NBA teams individualizing recovery strategies?

• Which technologies are being used to monitor fatigue and readiness?

• How are strength and conditioning programs adapted during the regular season?

• What role does AI play in athlete monitoring and performance analysis?

• How do teams balance player development with the demands of competition?

Upside Take: The NBA continues to be one of the most interesting environments for sports technology innovation.

With demanding travel schedules, frequent games, and significant financial investments in players, even incremental improvements in athlete availability and performance can deliver substantial value.

What to watch: Athlete monitoring, player availability, workload management, recovery technologies, biomechanics, and AI-powered performance analytics.

📈 MAJOR EARNINGS TO WATCH

Next week is shaping up to be an important period for technology and financial markets, with several major companies scheduled to report quarterly results.

For sports-tech startups, these announcements are relevant because they provide signals about investment conditions, AI infrastructure, digital health, and the broader technology economy.

📺 Netflix — October 20

Netflix is scheduled to report quarterly earnings as the company continues expanding its entertainment, advertising, and live content businesses.

Its growing interest in live sports represents an important development for the sports media industry.

Upside Take: Streaming platforms are becoming increasingly important players in the sports ecosystem.

Their investment in live sports could create new opportunities for leagues, teams, content creators, and technology companies specializing in data analytics, broadcasting, and fan engagement.

What to watch: Live sports strategy, subscriber engagement, advertising revenue, streaming technology, and content investment.

🤖 Tesla — October 21

Tesla is scheduled to report quarterly earnings, with investors closely monitoring developments across autonomous driving, robotics, AI, and manufacturing.

Beyond electric vehicles, Tesla continues investing in technologies with potential applications across multiple industries.

Upside Take: Robotics, AI, and advanced sensors could eventually have important applications in sports performance and rehabilitation.

The development of more sophisticated robotics and computer vision technologies may open opportunities for automated movement analysis, physical assessment, and training systems.

What to watch: AI investment, robotics, autonomous systems, sensor technology, and product development.

🧠 Meta Platforms — October 21

Meta is expected to report earnings, with particular attention on its investments in artificial intelligence, computing infrastructure, and wearable technologies.

Meta’s broader strategy includes AI assistants, smart glasses, and immersive computing experiences.

Upside Take: Smart glasses and AI-powered wearables could become increasingly relevant to sports organizations.

Potential applications include hands-free data collection, athlete feedback, training assistance, and immersive learning experiences.

What to watch: AI infrastructure spending, smart glasses, wearable computing, AI assistants, and augmented reality.

💻 IBM — October 21

IBM is scheduled to report quarterly earnings, providing insight into enterprise AI adoption, software, and digital transformation.

Upside Take: One of the biggest opportunities for AI in professional sports is not necessarily building more sophisticated algorithms.

It is helping teams connect their existing data sources and make better decisions.

Enterprise AI solutions could support the integration of athlete management systems, medical records, training data, and performance analytics.

What to watch: Enterprise AI adoption, data integration, automation, and AI-powered decision support.

🔬 Lam Research & Texas Instruments — October 21

Both companies are scheduled to report earnings, offering insights into the semiconductor industry and demand for advanced computing technologies.

Lam Research provides equipment used in semiconductor manufacturing, while Texas Instruments develops analog and embedded processing technologies.

Upside Take: Many innovations in sports technology depend on advancements in semiconductor technology.

Smaller, more efficient processors and sensors enable the development of next-generation wearables, portable monitoring systems, and connected training devices.

What to watch: Semiconductor demand, AI infrastructure, sensor technology, embedded computing, and hardware innovation.

🏥 Abbott Laboratories & Thermo Fisher Scientific — October 21

These healthcare technology companies are also scheduled to report quarterly results.

Abbott operates across medical devices and diagnostics, while Thermo Fisher Scientific provides scientific instruments, laboratory technologies, and research solutions.

Upside Take: The convergence between healthcare and elite sports continues to create opportunities for innovation.

Technologies initially developed for medical applications are increasingly being explored for athlete monitoring, rehabilitation, physiological assessment, and recovery.

What to watch: Medical devices, diagnostics, biosensors, health monitoring, and healthcare innovation.

🚀 PRODUCT & TECHNOLOGY DEVELOPMENTS TO WATCH

⌚ Wearable Technology: The Next Generation of Athlete Monitoring

The wearable technology industry continues evolving beyond traditional metrics such as heart rate, steps, and sleep duration.

Companies are increasingly exploring technologies capable of measuring physiological responses, muscle function, metabolic activity, and recovery.

The next major opportunity may be integrating multiple physiological signals into more comprehensive athlete health and performance assessments.

Upside Take: The biggest challenge for wearable technology companies is demonstrating that their measurements are accurate, reliable, and actionable.

Sports organizations are becoming increasingly sophisticated in their technology evaluations.

For startups, scientific validation and evidence of practical value are essential.

What to watch: Sensor accuracy, continuous physiological monitoring, metabolic sensors, recovery metrics, and scientific validation.

🤖 AI in Sports Medicine & Athlete Health

Artificial intelligence is creating opportunities to improve how practitioners analyze data, identify trends, and support decisions.

Potential applications include injury risk assessment, rehabilitation monitoring, medical imaging, biomechanics, and physiological analysis.

However, AI solutions must demonstrate clinical and scientific validity before they can be relied upon in high-stakes environments.

Upside Take: The future of AI in sports medicine will depend on its ability to complement practitioner expertise rather than replace it.

The most valuable solutions will be those that integrate seamlessly into existing workflows and provide meaningful, interpretable insights.

What to watch: AI-powered diagnostics, medical imaging, thermography, injury monitoring, and clinical validation.

📊 The Convergence of Performance Technologies

The sports performance technology market is undergoing an important transformation.

Companies are increasingly looking to combine different capabilities, including wearable sensors, biomechanics, video analysis, strength training data, and athlete management systems.

This reflects a broader industry trend toward integrated technology ecosystems.

Upside Take: Teams increasingly want solutions that help them connect data across departments rather than operate multiple disconnected platforms.

For technology vendors, interoperability, data quality, and ease of integration could become important competitive advantages.

What to watch: Platform integration, acquisitions, AI-powered analytics, and connected performance ecosystems.

🚀 AT UPSIDE NEXT WEEK

🎙️ Upside NBA Group Podcast — Best Practices, Performance & Innovation Across the NBA

Next week, we’re excited to host a new Upside NBA Group Podcast, bringing together leading NBA practitioners to discuss the latest developments in sports science, strength and conditioning, athlete monitoring, rehabilitation, and performance technology.

With the NBA regular season beginning, this is an ideal opportunity to hear directly from practitioners working in one of the most demanding professional sports environments.

Our conversation will explore:

• Player health and availability: How NBA teams manage the physical demands of an 82-game season.

• Strength and conditioning: Best practices for maintaining strength, power, and physical readiness throughout the season.

• Recovery and fatigue management: How teams approach recovery during congested schedules and frequent travel.

• Technology and data: Which tools and performance metrics are proving most useful in daily practice.

• The future of NBA performance: Emerging technologies, AI applications, and opportunities for innovation.

We look forward to discussing what is working, what challenges remain, and how NBA teams are adapting their approaches to athlete performance.

🎙️ Upside Podcast — Interview With Dr. Meshari Alwashmi, CEO of AmplifAI Health

Next week, we will also interview Dr. Meshari Alwashmi, CEO of AmplifAI Health, to learn more about the company, its thermography technology, and its vision for the future of AI-powered health assessment.

AmplifAI Health is developing technology that combines artificial intelligence and thermographic imaging to analyze thermal patterns and support health-related assessments.

Thermography is particularly interesting because it offers a non-invasive way to visualize temperature patterns across the body.

For sports organizations, potential applications worth investigating include monitoring physiological responses, supporting rehabilitation assessments, and identifying changes that may warrant further evaluation.

During the interview, we’ll explore:

• The company’s origins: Why Dr. Alwashmi founded AmplifAI Health and the problem the company is seeking to solve.

• How the technology works: How AI and thermographic imaging are combined to analyze thermal data.

• Applications in elite sports: Potential use cases in athlete monitoring, rehabilitation, and sports medicine.

• Scientific validation: What evidence is needed to establish the accuracy, reliability, and practical usefulness of AI-powered thermography.

• Commercialization and fundraising: The challenges of building, validating, and scaling a healthcare technology startup.

• Future opportunities: How AI-powered imaging could evolve across healthcare, sports performance, and other industries.

Upside Take: AI-powered thermography is an interesting emerging area, but its potential value for professional sports will depend on robust scientific validation and clearly defined use cases.

We look forward to learning more about AmplifAI Health’s approach and discussing where the technology could deliver meaningful value for practitioners.

🏟️ New Startup Announcement — Upside VIP Lunch in Atlanta

Next week, we will announce two additional sports-tech companies selected to present at our upcoming Upside VIP Lunch.

📍 U.S. Soccer Headquarters — Atlanta, Georgia

📅 December 18, 2026

👥 Approximately 200 MLS/NWSL practitioners and decision-makers expected.

The selected company will have the opportunity to present its technology to performance directors, sports scientists, rehabilitation specialists and other professionals from elite soccer organizations.

Upside Take: One of the biggest challenges for sports-tech startups is getting access to the right decision-makers.

Our goal is to bring innovative companies and professional sports organizations together, facilitate meaningful conversations and accelerate technology adoption.

🔮 THE BIG PICTURE

Several important themes stand out heading into next week.

1. AI investment is entering a more demanding phase.

Investors increasingly want to understand how large investments in AI infrastructure translate into revenue, productivity, and profitability.

For sports-tech startups, demonstrating a clear return on investment will become increasingly important.

2. Athlete health remains a major innovation opportunity.

Technologies focused on monitoring fatigue, supporting rehabilitation, and improving athlete availability continue attracting interest.

However, accuracy, scientific evidence, and practical usefulness remain critical.

3. Wearables and healthcare technologies are converging.

The boundaries between consumer health, medical devices, and professional sports performance technologies continue to blur.

This convergence could create new opportunities for startups, investors, and sports organizations.

4. Sports technology companies need more than great products.

Developing innovative technology is only the first step.

Successful startups must demonstrate credibility, build relationships with practitioners, validate their solutions, and establish sustainable commercial traction.

5. Practitioners remain at the center of innovation.

At Upside, we believe the most successful technologies are developed through close collaboration with the people who use them every day.

That’s why our upcoming NBA podcast and conversation with AmplifAI Health are particularly exciting.

We’ll continue connecting practitioners, technology companies, researchers, and investors while sharing insights from across the global sports performance industry.

Stay tuned for another exciting week!

Best,

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October 17, 2026 | Austin Peay State University (APSU), Clarksville, Tennessee

Today, we’re excited to be attending the Health & Performance Summit at Austin Peay State University (APSU), an event bringing together leading practitioners, sports scientists, military human performance specialists, researchers, and innovative sports technology companies.

Presented by Deaconess, the summit aims to advance the conversation around athlete health, human performance, strength and conditioning, injury prevention, and the growing role of technology in optimizing performance.

The event also serves an important mission: raising funds to support student programs at APSU, helping develop the next generation of sports scientists, strength and conditioning coaches, and human performance professionals.

At Upside, we strongly believe that innovation happens when practitioners, researchers, and technology companies collaborate, share experiences, and challenge existing approaches.

This summit represents a great opportunity to do exactly that.

🎯 Summit Agenda: Key Themes and Objectives

Throughout the day, attendees will have the opportunity to hear from experts working across professional sports, collegiate athletics, and the military, while discovering some of the latest technologies being developed for the sports performance industry.

The discussions will explore several important themes:

1. Strength & Conditioning: Best Practices Across Elite Sports

How are leading professional sports organizations designing their strength and conditioning programs?

What can collegiate programs learn from the approaches used in the NBA, MLB, and other elite sports environments?

Speakers will share practical insights into performance programming, athlete development, workload management, and the integration of technology into daily training.

2. Athlete Monitoring, Data Analytics & Performance Optimization

With the growing adoption of wearable technologies, force-sensing systems, and athlete monitoring platforms, teams have access to more data than ever before.

However, collecting data is only part of the equation.

The real challenge is translating that information into actionable insights that help practitioners make better decisions about training, recovery, and athlete readiness.

3. Injury Prevention, Rehabilitation & Return to Play

Managing injury risk and helping athletes return to competition safely remain priorities across professional and collegiate sports.

The summit provides an opportunity to explore how evidence-based programming, monitoring technologies, and interdisciplinary collaboration can support these objectives.

4. Military Human Performance: Lessons for Elite Sports

One of the particularly interesting aspects of this summit is the participation of military human performance specialists.

Military personnel and elite athletes face many similar challenges, including physical fatigue, cognitive demands, stress, recovery, and decision-making under pressure.

There is a significant opportunity for knowledge transfer between these two environments, particularly in areas such as readiness assessment, mental resilience, wearable technologies, and human performance optimization.

5. Emerging Sports Technologies & Innovation

Attendees will also have the opportunity to meet sports technology companies developing solutions across strength and conditioning, athlete monitoring, velocity-based training, reactive agility, muscle fatigue assessment, and performance analytics.

These demonstrations should provide valuable opportunities for practitioners to evaluate new technologies and discuss their potential applications.

🎤 Meet the Speakers: Experience Across MLB, NBA, Collegiate Sports & Military Performance

The summit features an impressive lineup of speakers with extensive experience across professional sports, collegiate athletics, and military human performance.

Chris Dunaway — Los Angeles Dodgers (MLB)

Chris Dunaway is the International Director of Athleticism & Performance for the Los Angeles Dodgers.

He previously held strength and conditioning roles across the Baltimore Orioles, Pittsburgh Pirates, and Dodgers organizations.

His expertise includes evidence-based performance programming, sports nutrition, and performance scouting.

His experience across professional baseball provides an interesting perspective on how organizations approach athlete development, physical preparation, and long-term performance.

Dr. Bill Burgos — Founder, BUCOGROUP | Former NBA Strength & Conditioning Coach

Dr. Bill Burgos brings more than 20 years of experience across the NBA and sports performance industry.

He previously served as Head Strength and Conditioning Coach with the Minnesota Timberwolves, Orlando Magic, and New York Knicks.

His areas of expertise include player health and performance strategy, return-to-play protocols, and injury risk mitigation.

His extensive NBA experience offers valuable insights into the demands of managing athlete performance throughout a long competitive season.

Paul Robbins — Founder, VIP Data | NBA Performance Data Specialist

Paul Robbins has spent 16 seasons working as an NBA performance data specialist.

He is the founder of VIP Data and has extensive experience in metabolic testing, sports biometrics, and applied sports technology.

His background spans the NBA, NFL, NHL, USTA, and Navy SEALs.

Paul brings a unique perspective on the application of data analytics and physiological testing to improve human performance across different environments.

Ryan Metzger — Founder, AXIS Strength and Conditioning

Ryan Metzger is a collegiate strength and conditioning coach and founder of AXIS Strength and Conditioning.

Her expertise includes performance programming, athlete monitoring, and sports science, with experience across Power Five collegiate athletics and competitive Olympic weightlifting.

She brings an important collegiate perspective on athlete development and the practical application of performance science.

Sgt. Spencer Posey — Military & Human Performance Lead, Garmin Health

Sgt. Spencer Posey is the Military & Human Performance Lead for Garmin Health and founder and CEO of Denali Fitness and Nutrition.

His expertise includes wearable analytics, readiness metrics, and human performance optimization.

With experience across military, healthcare, and private-sector environments, Spencer brings a valuable perspective on how wearable technologies and physiological data can support human performance and readiness.

Dr. Seth Haselhuhn — SOCOM Mental Performance Specialist

Dr. Seth Haselhuhn is a SOCOM Mental Performance Specialist and owner of Caliber Development Group.

He holds a Ph.D. and specializes in mental performance, decision-making under pressure, and applied sports psychology.

His experience working with military and tactical populations offers valuable insights into the psychological aspects of performance, particularly in high-pressure environments.

🚀 Sports Technology Showcase: Six Companies to Watch

One of the highlights of today’s summit is the opportunity to discover innovative technologies being developed for professional sports, collegiate athletics, and human performance.

Six companies are exhibiting at the event, including Upside.

1. TeamBuildr — Strength & Conditioning Software

Website: https://www.teambuildr.com

TeamBuildr provides strength and conditioning software designed to help coaches create, deliver, and monitor training programs.

According to the company, its platform is trusted by more than 5,500 teams worldwide.

Its technology helps practitioners streamline programming, track athlete progress, and manage training data across large groups of athletes.

As teams increasingly seek integrated solutions for managing athlete performance, software platforms like TeamBuildr play an important role in modern strength and conditioning operations.

2. Upside — Connecting Elite Sports Teams With Innovation

Website: https://www.upsideglobal.co

At Upside, our mission is to help professional sports organizations discover, evaluate, and adopt innovative technologies that can improve athlete health, performance, recovery, and rehabilitation.

Today, our network connects more than 10,000 sports executives and practitioners across the NBA, NFL, MLB, NHL, MLS, NCAA, and leading European sports organizations.

Through our technology scouting platform, AI Assistant, research, interviews, and events, we help teams navigate a rapidly evolving sports technology landscape.

Our platform provides access to information about hundreds of sports technology companies, including their products, capabilities, pricing, scientific research, and existing customers.

We are excited to connect with practitioners and students at APSU and introduce them to some of the innovations shaping the future of sports performance.

3. DetecFit — Affordable Velocity-Based Training & Force Sensing

Website: https://www.detecfit.com

DetecFit is developing a portable technology designed to make velocity-based training and force measurement more accessible.

Its solution enables practitioners to capture strength training data and assess performance without relying on expensive or complex equipment.

By combining velocity-based tracking and force-sensing capabilities, DetecFit aims to provide coaches with actionable information to better monitor strength development and training intensity.

The growing adoption of velocity-based training across elite sports reflects a broader shift toward more objective and individualized strength programming.

4. QuickBoard — Reactive Agility & Cognitive-Motor Training

Website: https://www.quickboard.com

QuickBoard develops a reactive agility and cognitive-motor training system designed to help athletes improve reaction time, coordination, and movement performance.

The technology combines a sensor-based board with interactive training exercises, allowing practitioners to assess and train athletes under different physical and cognitive demands.

QuickBoard’s approach is supported by published research and is relevant to performance training, rehabilitation, and return-to-play programs.

The company is also exploring new force-sensing capabilities that could further expand its applications in athlete assessment.

5. Aris Training — Data-Driven Performance Testing & Resistance Training

Website: https://aristraining.com

Aris Training develops sports performance technology combining data-driven performance testing with digital resistance training systems.

Its solutions are designed to help practitioners measure physical capabilities, monitor progress, and individualize training programs.

Technologies that integrate performance assessment and training are becoming increasingly relevant as teams seek more efficient ways to connect testing data with daily programming.

6. Myocene — Muscle Fatigue Assessment

Website: https://www.myocene.com

Myocene develops portable technology designed to assess muscle fatigue in athletes.

Its approach combines electrical muscle stimulation with force sensing to provide objective measurements of muscle function and fatigue.

Muscle fatigue assessment is an increasingly interesting area of sports science, particularly for teams seeking better tools to evaluate readiness, recovery, and the physiological impact of training.

Solutions like Myocene could help practitioners complement traditional athlete monitoring methods with more direct measures of neuromuscular function.

🔍 Why Events Like This Matter for the Sports Performance Industry

The sports performance technology market continues to evolve rapidly.

New technologies are emerging across athlete monitoring, biomechanics, artificial intelligence, recovery, injury prevention, and strength and conditioning.

However, the availability of more technology does not automatically translate into better athlete outcomes.

Successful adoption requires collaboration between technology developers, researchers, and practitioners who understand the realities of elite sports environments.

Events such as the APSU Health & Performance Summit create opportunities to address several important questions:

• How can practitioners distinguish between useful innovations and technologies that lack sufficient scientific validation?

• Which performance metrics provide the most actionable insights?

• How can teams integrate multiple technologies without overwhelming practitioners with data?

• What can professional sports organizations learn from military human performance programs, and vice versa?

• How can universities better prepare students for careers in an increasingly technology-driven sports performance industry?

These are some of the questions we look forward to exploring throughout the day.

🎓 Supporting the Next Generation of Sports Performance Professionals

Beyond the presentations and technology demonstrations, the summit’s fundraising mission deserves special recognition.

By supporting student programs at Austin Peay State University, the event helps create opportunities for aspiring strength and conditioning coaches, sports scientists, researchers, and performance professionals.

Giving students access to experienced practitioners and emerging technologies can play an important role in bridging the gap between academic education and the practical demands of working in elite sports.

At Upside, we believe the future of sports performance depends not only on developing better technologies but also on investing in the people who will use them.

📅 Coming Next Week: Our Key Takeaways From the Summit

Following today’s event, we’ll publish a dedicated Upside analysis highlighting:

• The most interesting insights shared by the speakers.

• Emerging trends in sports science, athlete monitoring, and human performance.

• Lessons from military performance programs that could be applied to elite sports.

• Innovative technologies showcased during the event.

• Practical takeaways for teams, practitioners, and sports technology startups.

A special thank you to Austin Peay State University, presenting sponsor Deaconess, the speakers, exhibitors, and organizers for bringing the sports performance community together.

We look forward to an exciting day of learning, exchanging ideas, and supporting the next generation of performance professionals.

Looking forward to seeing many of you today at the Summit.

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DetecFit is a Chicago-based sports technology startup founded by brothers Isaiah Anderson (CEO) and Tyler Sauter (Founder & CTO), developing an innovative, portable solution for strength assessment and velocity-based training (VBT). Its flagship device, Arrow, combines isometric strength testing and movement velocity tracking in a single device, enabling athletes, coaches and sports performance practitioners to measure strength, movement speed, range of motion and time under tension. One of its key differentiators is its interactive 3D movement replay, which captures detailed movement data at 300 data points per second, allowing coaches to analyze exercises, monitor progress and provide actionable feedback.

The technology supports strength and conditioning, remote coaching, athlete monitoring and return-to-play assessments following injury. Unlike traditional VBT solutions, DetecFit aims to offer a more affordable, versatile and portable platform suitable for professional teams, individual trainers, gyms and athletes. The company is currently testing its technology while developing a smaller wearable device, expanded sensor integrations and a centralized team dashboard. DetecFit is also preparing to raise $2 million to support its next phase of growth.

You can watch the video interview below by clicking on the Youtube link. You can also listen to the audio interview by clicking on the link at the top of the page:

Here is a look at the DetecFit’s VBT device and 3D rep replay mobile app:

Here is a short video of the DetecFit team going over Arrow for their Pilot release.

📝Show Notes: During the interview with Isaiah and Tyler, we discussed their backgrounds, the inspiration behind launching the company, and how their innovative Arrow device combines velocity-based training (VBT) and isometric strength testing into a single portable solution. We explored the technology’s main applications in strength and conditioning, athlete monitoring, remote coaching and return-to-play assessments, as well as its unique capabilities, including interactive 3D movement replay and real-time performance data.

We also discussed the current state of the VBT market, DetecFit’s competitive advantages, the benefits for teams and practitioners, and the importance of making advanced performance technology more accessible and affordable. Finally, Isaiah and Tyler shared insights into their business model, feedback from trainers, their plans to develop a smaller wearable device and team dashboard, and their upcoming $2 million fundraising round to support the company’s next phase of growth.

Here are the best quotes from the interview with Isaiah and Tyler:

1. Your Background

What experiences led you to create DetecFit?

Isaiah Anderson, CEO:

“We both are lifelong athletes, both played multiple sports growing up. [...] Every day we go to the gym, there was no great tangible way to show what we do.”

“Wearables today really miss out on the strength training portion.”

Tyler Sauter, Founder & CTO:

“I’ve been a software engineer my whole career, which is about 10 years of experience now doing a lot of workflow automation and building backend data pipeline solutions.”

“We were just thinking, what is the way to track this that isn’t a video, and isn’t just a notebook?”

2. Your Company & Product

What does DetecFit do, and what problem does it solve?

Isaiah Anderson:

“We use a lot of VBT calculations to kind of give that progress. But one thing that we do also have is a 3D set replay.”

“You can really replay that entire set and see the time under tension, see the range of motion, see how fast it was moving, kind of in a very interactive, viewable dashboard.”

Tyler Sauter:

“Instead of doing the calculations on device and then wirelessly sending only [...] the average speed [...] we’re sending 300 data points a second of exactly what that accelerometer is reading.”

3. Main Use Cases

How can teams, coaches and athletes use DetecFit?

Tyler Sauter:

“Training is really where we started and built it [...] You actually called out a great use case as well, which is that remote coaching capability.”

“Return to play. That’s huge. It’s even better if you have the baseline before the injury, and then the injury happens, and then you can measure as you’re returning.”

“We do have real-time alerts that are all configurable to thresholds.”

Isaiah Anderson:

“Not only can we do VBT on barbells, but we can do VBT [...] on a wearable form factor Or if they’re more interested in isometric, then it’s the same device that can do that capability.”

4. VBT Market & Trends

What trends are shaping the VBT market, and where are the gaps?

Isaiah Anderson:

“A lot of vendors in VBT today are guided towards a lot of the practitioners and a lot of the top gyms in the country and in the world.”

“Our benefit again is that two in one, not just doing VBT, but also strength collection as well.”

Tyler Sauter:

“In the current market it’s really focused on this kind of enterprise pricing model that isn’t accessible for individual consumers or individual one-on-one trainers.”

“We’re trying to pass those cost savings onto the consumer and access lower and lower spend levels of teams.”

5. Benefits for Teams

What are the main performance and operational benefits?

Tyler Sauter:

“Premium tracking outside of their own strength facility, so portability is huge.”

“It really enables remote coaching. The quick and easy way to do return to play. This is something you can have on the sidelines.”

“We’re working on hooking this up to a wide, wide variety of additional sensors.”

6. Competitive Advantages

What differentiates DetecFit from other solutions?

Tyler Sauter:

“They’re compressing all of the rep information into a single data point, whereas we’re providing the entire data stream.”

“We do have a screen which allows offline use and without having to use apps, and the optional force sensor input.”

Isaiah Anderson:

“They’re only fixed to one exercise or maybe a few. We can really take that multi-exercise approach.”

7. What Teams and Trainers Like About the Product

What feedback are you receiving?

Isaiah Anderson:

“Our trainers are already loving it as they can show and say, ‘Hey, look, on the first set you went a lot lower. Let’s recreate that arc in this next set.’”

“That’s what 3D Replay really unlocks, is not just this speed number [...] Actually having those 3D replays that we’re collecting shows that someone was actually doing the exercise that they say they were doing.”

Tyler Sauter:

“For one of our trainers, there was a great story of an avid tennis player that had to have elbow surgery.”

He explained that measuring the athlete’s force and movement speed during rehabilitation improved her confidence in her recovery.

8. Business Model

How does DetecFit structure its pricing and packages?

Isaiah Anderson:

“Right now we’re still very early, still in the testing stages. So I’d say for price, we’re doing it case by case basis based on how many are needed.”

“We don’t really have a full-fledged price that we’re sharing yet.”

“What we want this to be is really [...] what implementation does this coach or this gym want?”

9. Plans for the Next 12 Months

What are the company’s main priorities?

Isaiah Anderson:

“We’re trying to kick off a raise end of October, early November.”

“Since we are moving to a more consumer-friendly, smaller wearable, I think that is our entry point to just the average lifter.”

When asked about the fundraising target, the founders confirmed:

“Two million.”

Tyler Sauter:

“We’re releasing Android later this week in beta to some of our Android users.”

“We just recently solved up to five simultaneous device connections to a single phone.”

“We have our much smaller wearable that’s in electrical engineering design review right now.”

The founders also discussed plans for a consolidated team dashboard, additional sensor connectivity and organization-level data aggregation.

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Dear Colleague,

This weekend, I will be heading to Nashville, Tennessee, to attend the ASPU Health and Performance Summit, catch up with local professional sports teams (MLS, NHL), reconnect with industry peers and colleagues, and explore some of the latest innovations in sports performance technology.

During my visit to Nashville, I plan to:

1. Meet with local professional sports teams (MLS, NHL)

Catch up with practitioners and decision-makers from Nashville SC (MLS) and the Nashville Predators (NHL) to discuss their latest initiatives, challenges and approaches to training, rehabilitation, athlete performance and innovation.

2. Attend the ASPU Health and Performance Summit

Connect with leading sports and military performance practitioners, exchange ideas and learn about the latest research, technologies and best practices in strength and conditioning, athletic medicine, rehabilitation and performance optimization.

3. Scout innovative sports technologies

Catch up with several innovative sports-tech companies, including:

• Myocene — Muscle fatigue assessment technology to help teams optimize training, recovery and rehabilitation.

• DetectFit — Portable strength assessment and velocity-based training (VBT) technology.

• Aris Training — Innovative strength and performance training solutions.

• VALD — Performance assessment technologies, including force plates, dynamometers and athlete monitoring tools.

• QuickBoard — Sensor-based technology for reaction time, agility, motor learning and rehabilitation.

• TeamBuildr — Strength and conditioning software that helps coaches design training programs, track athlete progress, manage workouts and analyze performance data.

I am particularly interested in exploring the latest advancements in AI-powered performance tools, biomechanics, force plates, velocity-based training, athlete monitoring, rehabilitation technologies and neuromuscular assessment.

4. Reconnect with industry peers and colleagues

Meet with sports performance practitioners, sports-tech founders, investors and colleagues to discuss emerging trends, challenges and opportunities across professional and collegiate sports.

5. Highlight innovative sports-tech startups

Discover emerging technologies, learn more about their applications in elite sports and share insights with our Upside network of 10,000+ sports executives and practitioners worldwide.

Let’s meet in Nashville!

If you work for an MLS, NHL or NCAA team, a sports-tech startup, or a VC firm, and plan to be in Nashville this weekend, I would love to connect.

Feel free to reach out to me at julien@upsideglobal.co if you would like to meet one-on-one for coffee, exchange ideas, discuss the latest trends in sports and technology, or explore potential collaborations.

Looking forward to seeing many of you in Nashville!

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Upside Global | Investment & Sports Business Analysis | October 2026

Introduction: Professional Sports Have Become a Major Investment Asset Class

For decades, professional sports teams were primarily owned by wealthy individuals, families and business entrepreneurs. Owning a franchise was often considered a prestigious investment, driven as much by passion and personal ambition as financial returns.

That model is changing rapidly.

Today, some of the world’s largest private equity firms, institutional investors, sovereign wealth funds and investment groups are acquiring stakes in professional sports organizations.

Companies such as Apollo Global Management, KKR, RedBird Capital Partners, Ares Management, Sixth Street and Silver Lake are increasingly treating professional sports as a strategic investment category.

The numbers illustrate the scale of this transformation.

Sources: S&P Global Market Intelligence and Dakota, using their respective deal and franchise samples.

This trend is particularly visible across the NFL, NBA, MLB, NHL, MLS, European soccer, Formula 1 and women’s professional sports.

One of the most significant recent transactions occurred in March 2026, when Apollo Sports Capital completed its acquisition of a majority stake in Atlético de Madrid, one of Europe’s leading soccer clubs.

Another major development came when KKR acquired Arctos Partners in February 2026, expanding its exposure to professional sports franchises around the world.

These investments raise several important questions.

Why are private equity firms investing billions in professional sports? Which firms are building the largest portfolios? And what does this growing institutional ownership mean for teams, athletes, fans and the sports technology industry?

Why Private Equity Firms and Investment Groups Are Buying Sports Teams

A. Scarcity and rising franchise valuations

Unlike most businesses, professional sports franchises are extremely scarce assets.

There are only 32 NFL franchises, 30 NBA franchises and 30 MLB franchises. Investors cannot simply create another team in an established league without approval and an expansion opportunity.

This scarcity, combined with global demand, helps support franchise valuations.

The 2026 sports M&A market demonstrates how far investors are willing to go to acquire ownership of these assets.

B. Predictable and diversified revenue

Professional sports organizations generate revenue through multiple channels:

• National and international broadcasting rights

• Sponsorship and commercial partnerships

• Ticketing, hospitality and premium seating

• Merchandise and licensing

• Stadium events and entertainment

• Digital content and international brand expansion

Centralized league media contracts can provide a degree of revenue visibility that is attractive to long-term investors.

C. Global expansion opportunities

A professional sports team is no longer simply a local organization.

Major European soccer clubs have millions of supporters across Asia, North America, Africa and the Middle East. NFL and NBA organizations are also pursuing international audiences.

Investment firms see opportunities to monetize these global communities through sponsorships, streaming, licensing, international events and digital platforms.

D. Sports franchises as long-term assets

Private equity investors increasingly view sports franchises as assets that can appreciate over extended periods.

Unlike traditional leveraged buyouts, many sports investments involve minority equity positions where investors have limited operational control.

The financial thesis often combines franchise appreciation, revenue growth, infrastructure development and an eventual sale of the ownership stake.

However, rising valuations do not guarantee attractive returns. Limited liquidity, high acquisition multiples, player payrolls, debt and league restrictions all create risks.

E. Stadiums and real estate

Stadium development is becoming a major part of the investment thesis.

Modern venues can generate revenue far beyond game days through concerts, conferences, restaurants, hotels, retail and mixed-use real estate.

Apollo’s investment in Atlético de Madrid is a particularly interesting example. Its strategy includes supporting the Ciudad del Deporte development surrounding the club’s stadium.

F. Technology, data and operational efficiency

Investment groups are also attracted by opportunities to modernize sports organizations.

These include AI-powered analytics, ticketing optimization, personalized fan engagement, commercial data platforms, athlete performance technologies and improved business operations.

For sports-tech startups, this creates a potentially important new category of customers and strategic partners.

Private equity-backed ownership groups may be able to introduce technologies across multiple teams, although investment decisions remain dependent on each organization’s sporting priorities and management structure.

The Major Private Equity Firms and Investment Groups Buying Sports Teams

The investment landscape includes several distinct models: majority-control acquisitions, minority franchise investments, multi-club ownership platforms and investments in leagues, media rights or sports infrastructure.

It is important to distinguish direct team ownership from indirect stakes held through a parent company, and from loans or commercial partnerships that do not confer ownership.

A. Apollo Global Management — A major new investor in European soccer

Apollo’s acquisition of Atlético de Madrid represents one of the most important recent private equity investments in European soccer.

Through Atlético’s club structure, the transaction also encompasses Atlético de San Luis in Mexico and Atlético Ottawa in Canada.

The firm’s broader sports investments include interests in the Mutua Madrid Open and Miami Open tennis tournaments, although these are event investments rather than soccer-team acquisitions.

Upside Take: Apollo’s investment illustrates how private equity is moving beyond minority financial investments toward majority ownership of globally recognized sports brands.

Its emphasis on stadium development and commercial infrastructure also suggests that future returns may come from activities extending far beyond matchday revenues.

B. Arctos Partners / KKR — One of the largest portfolios of minority team investments

Arctos has become one of the most prominent institutional investors in professional sports.

Its investment model generally focuses on acquiring minority stakes in established franchises rather than taking operational control.

In February 2026, KKR acquired Arctos, creating a powerful combination of sports-investment expertise and global institutional capital.

These are selected reported investments across different dates and ownership vehicles; the table is not a representation that every position is unchanged or directly held as of October 2026.

Upside Take: Arctos is particularly interesting because of its diversified exposure across American professional sports and international soccer.

Rather than betting on the success of a single team, its portfolio provides exposure to multiple leagues, media markets and commercial ecosystems.

KKR’s acquisition could accelerate this strategy by providing additional capital, institutional relationships and distribution capabilities.

C. RedBird Capital Partners — Building a global sports and entertainment ecosystem

RedBird Capital has pursued a different approach, combining team ownership with investments in media, entertainment, technology and commercial infrastructure.

Selected investments:

RedBird has also developed investments across sports media, distribution and entertainment.

Upside Take: RedBird’s strategy is not simply to acquire sports teams. It aims to connect sports franchises with media, content distribution and commercial opportunities.

This approach could become increasingly important as clubs seek to monetize international audiences and build direct relationships with fans.

D. Ares Management — Expanding across American and European sports

Ares has built a diversified sports investment business spanning team ownership, financing and related assets.

Its reported investments include:

• Miami Dolphins (NFL): Minority investment of approximately 10%.

• Inter Miami CF (MLS): Institutional investment.

• Atlético de Madrid: Retained minority exposure following Apollo’s majority acquisition.

• European soccer: Additional financing and investment relationships, including Chelsea-related exposure.

Ares has also invested in motorsports-related assets.

Upside Take: Ares illustrates how private equity firms can participate in sports without necessarily controlling teams.

For many existing franchise owners, minority investments offer access to capital while allowing them to retain management control.

E. Sixth Street — Teams, media rights and women’s sports

Sixth Street has emerged as an important sports investor with exposure to professional franchises, stadium financing and media rights.

Selected investments and relationships:

The Real Madrid and Barcelona transactions are not equivalent to owning equity in those soccer clubs.

Upside Take: Sixth Street demonstrates that institutional investment in sports extends well beyond franchise ownership.

Its investments in women’s soccer are especially noteworthy, as women’s professional sports continue to attract greater institutional attention.

F. Clearlake Capital — Majority ownership and multi-club strategies

Clearlake Capital partnered with investors led by Todd Boehly to acquire Chelsea FC in 2022.

The ownership platform subsequently expanded into French soccer through RC Strasbourg.

This strategy offers potential opportunities to coordinate scouting, recruitment, player development and business operations across clubs.

Upside Take: Multi-club ownership could become an increasingly important investment model, particularly in European soccer.

However, conflicts of interest, competitive balance, supporter opposition and UEFA ownership regulations present significant challenges.

G. Silver Lake — Investing in global sports platforms

Silver Lake has pursued a broader technology-driven sports investment strategy.

Its reported investments and exposures include:

• City Football Group: Minority investment in the ownership platform associated with Manchester City and other soccer clubs.

• New Zealand Rugby: Minority commercial investment associated with the All Blacks and wider New Zealand rugby business.

• Madison Square Garden Sports: Investment exposure to the company associated with the New York Knicks and New York Rangers.

• Sports-related businesses: Investments across sports media, technology and commercial platforms.

These positions differ significantly in structure. In particular, an investment in New Zealand Rugby’s commercial business is not equivalent to owning the All Blacks national team.

Upside Take: Silver Lake represents the intersection of sports, technology, media and institutional investment.

Its strategy demonstrates how investors can seek exposure to sports economics through commercial platforms as well as franchise ownership.

H. Other important investors to watch

Several other investment groups are helping reshape the sports ownership landscape.

The table combines reported equity holdings, indirect exposures and league-approved investment vehicles. CVC’s league-level commercial investments, for example, should not be interpreted as direct ownership of every club in those competitions.

How the Major Sports Leagues Regulate Private Equity Ownership

Not all professional leagues allow investment firms to buy teams under the same conditions.

In North America, institutional investors generally face restrictions on ownership percentages, governance rights and investment holding periods.

The NFL is especially conservative. Its framework limits institutional investment to minority positions and maintains strong protections for controlling owners.

The league’s decision to admit institutional investors in 2024 nevertheless opened a major new market for private capital.

In European soccer, controlling acquisitions are more common, although league rules, competition regulations and financial oversight create different constraints.

Upside Take: The differences between leagues will influence where private equity firms deploy capital.

The NFL offers exposure to highly valuable franchises through restricted minority positions, while European soccer provides more opportunities for investors seeking majority control and operational influence.

Future Trends: Where Is Private Equity Investment in Sports Heading?

Trend 1: More NFL franchises will attract institutional capital

The NFL’s decision to permit private equity investment represents a significant structural change.

As franchise valuations continue rising, minority stake sales could become increasingly attractive to owners seeking liquidity without surrendering control.

More investment firms may also seek approval to participate.

Prediction: Institutional minority ownership could become a standard feature of NFL franchise capital structures over the next decade.

Trend 2: Women’s sports will become an increasingly important investment target

Women’s professional sports represent one of the most compelling growth opportunities for institutional investors.

Investment activity is expanding across the NWSL, WNBA and other women’s competitions.

According to the CFA Institute’s May 2026 analysis, global elite women’s sports revenues reached approximately $2.35 billion in 2025, with further growth expected.

Investors are attracted by opportunities in media rights, sponsorships, facilities, franchise expansion and international growth.

Prediction: More investment funds will create dedicated strategies for women’s professional sports, particularly where commercial development and infrastructure remain underfunded.

Trend 3: Multi-club and multi-sport ownership will continue expanding

Investment groups are increasingly interested in building portfolios rather than owning individual franchises.

These portfolios could combine soccer clubs, basketball teams, motorsports organizations and other sports businesses.

Deloitte’s 2026 Sports Industry Outlook identifies this convergence as an important structural trend.

Potential benefits include shared commercial relationships, centralized technology platforms, scouting networks and operational expertise.

However, multi-club ownership will face growing scrutiny over competitive integrity, conflicts of interest and governance.

Trend 4: AI and sports technology will become important value-creation tools

One of the most interesting implications for the sports technology industry is the opportunity for investment groups to accelerate innovation within their portfolios.

Private equity-backed organizations may increasingly invest in:

• Athlete performance: GPS, wearables, biomechanics, workload monitoring and recovery technologies.

• Sports medicine: Injury-risk assessment, rehabilitation platforms and return-to-play technologies.

• AI and analytics: Computer vision, video analysis, predictive models and decision-support systems.

• Business operations: Dynamic ticket pricing, fan engagement, sponsorship analytics and revenue optimization.

• Infrastructure: Smart stadiums, connected facilities and energy management.

Upside Take: This could create new opportunities for sports-tech startups.

A technology company that successfully demonstrates value within one team might be introduced to other organizations in the same investment portfolio.

However, shared ownership does not automatically translate into centralized purchasing. Performance directors, medical departments and coaching staffs will still need evidence that a technology solves a meaningful problem.

Trend 5: More investment will flow into sports infrastructure and media

Investors are likely to expand beyond direct franchise ownership into adjacent assets.

These include stadiums, training facilities, media-rights businesses, data companies, sports technology platforms and live-event operations.

This approach can offer exposure to the economics of professional sports without requiring investors to acquire a multibillion-dollar franchise.

It may also provide different liquidity, governance and return characteristics.

Trend 6: Investment groups will face greater pressure to deliver returns

Rising franchise valuations create opportunities but also introduce challenges.

Investors purchasing teams at historically high multiples must eventually demonstrate how those assets will generate acceptable returns.

Potential risks include:

• Slower growth in media-rights revenues.

• Increasing player salaries and transfer costs.

• Expensive stadium and infrastructure projects.

• Limited opportunities to exit large ownership positions.

• Fan resistance to aggressive commercialization.

• Governance conflicts between investors and club management.

A recent analysis by Morrison Foerster highlights ownership restrictions, regulatory complexity and stakeholder concerns as important considerations for private capital entering global sports.

Prediction: The next phase of investment will increasingly distinguish firms capable of creating sustainable operating value from those relying primarily on rising franchise valuations.

What This Means for the Sports Technology Industry

For sports-tech founders and investors, the growing involvement of private equity creates several important opportunities.

First, access to capital could expand. Investment firms building sports portfolios may also invest in technology companies serving those organizations.

Second, commercial opportunities could become more scalable. Multi-team ownership platforms may facilitate introductions, pilot programs and technology adoption across their portfolios.

Third, due diligence requirements could become more demanding. Institutional owners may increasingly expect vendors to demonstrate measurable financial, operational or sporting outcomes.

Fourth, technology companies may become acquisition targets. Firms investing in teams, media, analytics and performance infrastructure could seek strategic acquisitions that complement their broader portfolios.

At Upside, we believe this convergence between institutional investment and sports technology is particularly important.

For years, sports technology companies have focused primarily on selling products directly to performance directors, sports scientists, rehabilitation specialists and coaching staffs.

Those relationships remain essential.

However, investment groups and ownership platforms may become an additional channel for technology adoption, financing and strategic partnerships.

The opportunity is not simply to sell more technology. It is to demonstrate how innovation can create measurable value across professional sports organizations.

Conclusion: A New Era of Sports Ownership

The growing presence of Apollo, KKR, Arctos, RedBird, Ares, Sixth Street, Clearlake and Silver Lake illustrates a fundamental transformation in professional sports.

Teams are no longer viewed exclusively as prestigious assets owned by wealthy individuals and families.

They are increasingly part of sophisticated global investment portfolios encompassing franchises, media, entertainment, technology, infrastructure and commercial rights.

The investment thesis is compelling: scarce assets, loyal audiences, international growth opportunities and the potential for long-term value appreciation.

But there are important challenges.

Investors must balance financial performance with sporting success, fan expectations and the cultural identity of teams.

They must also recognize that professional sports organizations are fundamentally different from traditional portfolio companies.

For the sports technology industry, this shift could be significant.

The next major wave of sports-tech adoption may be influenced not only by coaches, performance directors and sports scientists, but also by the investment groups that increasingly own and finance professional sports organizations.

The firms that successfully combine financial resources, operational expertise, technology and respect for sporting culture could be among the most influential players in the next decade of professional sports.

And for sports-tech startups, understanding these ownership groups may become just as important as understanding the teams themselves.

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Dear Colleague,

We are excited to announce that Tiny Health and Aris Training are the two latest sports-tech companies confirmed to present at our upcoming Upside VIP Lunch at the 2026 PSPA Conference in Atlanta.

⚽ Upside VIP Lunch
📅 December 18, 2026, 12 pm - 2.30 pm
📍 Atlanta, Georgia, US Soccer HQ

The event will bring together approximately 200 leading MLS and NWSL practitioners and decision-makers, including Performance Directors, Heads of Athletic Therapy, Directors of Rehabilitation, Sports Scientists and representatives from clubs across the leagues.

Each presenting startup will be able to present for 15 minutes to MLS/NWSL practitioners, have a booth and be part of a speed dating session with the teams.

Due to high demand, we extended the number of presenting startups to ten. Next week we plan to announce some new startups presenting at our VIP Lunch, We have a lot of startups interested in taking the last six spots so please reach out to us ASAP if interested in presenting.

🚀 Meet the Other Two Startups Presenting Startups

🏃 Aris Training

Aris Training is building an integrated athletic-performance platform that brings elite-level testing and training technology to every level of the performance market. Aris's digital-resistance hardware, including ArisPro, ArisSpeed and ArisFlight, measures speed, force, velocity, power and recovery. Unlike most systems that stop at measurement, Aris adds an interpretation and prescription layer that explains what the data means for each athlete and automates progression for the next training session. Every rep becomes a clear coaching decision, without extra analysis work for coaches or performance staff. Aris is already deployed with professional teams in football, basketball and baseball and with the product-testing lab of a global athletic brand.

You can watch the video interview we did with Aris Training CEO:

Here is a look at Aris Training software:

🧬 Tiny Health

Tiny Health is a precision microbiome company that gives performance and medical staff an in-depth, individualized look at each athlete’s gut health from a simple at-home test. Results come with personalized, evidence-based recommendations to support nutrition, gut health, and performance optimization. Built by scientists and physicians from Mayo Clinic, Stanford, and Johns Hopkins, Tiny Health is trusted by 200,000+ people and 6,000+ practitioners.

We are looking forward to having Tiny Health present its approach and discuss how microbiome data could potentially fit into the evolving world of athlete health and performance.

⚠️ Only Six Presentation Spots Remain

Selected sports technology startups will have the opportunity to:

• Present directly to MLS and NWSL teams and practitioners

• Demonstrate and exhibit their technology

• Receive feedback from experienced sports performance professionals

• Participate in meaningful conversations with key decision-makers

• Explore potential pilots, partnerships and commercial opportunities

• Build relationships in an intimate, highly targeted environment

We only have 6 spots for startups to present, so if you want to sponsor, exhibit and present at the Upside VIP Lunch, please contact us as soon as possible at julien@upsideglobal.co. The remaining presentation opportunities will be confirmed on a first-come basis.

Last year’s Upside VIP Dinner welcomed more than 50 practitioners representing over 20 MLS clubs.

You can view the recap and recorded panel discussions and presentations here:

📅 What’s Next for Upside

2026 Austin Peay State University Health & Performance Summit
📅 October 17, 2026
📍 Tennessee
Event information

This summit will bring together leaders from organizations across professional sports, health, performance, sports science, the military and government.

For sponsorship information, contact Dr. Tim Leszczak, Chair of the APSU Department of Health and Human Performance, at Leszczakt@apsu.edu.

🇫🇷 Upside Tech Summit—France
📅 First half of 2027
📍 France

We are planning to host this summit at a major stadium, bringing together leading organizations from Ligue 1, the Premier League, LaLiga, international rugby, basketball, the NBA, MLS, the NFL and other elite sports.

We are also developing additional Upside VIP events with major leagues, teams, VCs across the United States and Europe in 2026 and 2027.

Interested in attending, speaking, presenting, exhibiting or sponsoring an upcoming Upside event? Contact me at julien@upsideglobal.co.

Best,

Julien

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Upside Global | Sports Technology & Market Intelligence | October 13, 2026

Introduction: Google makes another major move in wearables

On October 12, 2026, Google officially unveiled the Google Fitbit Edge, its latest fitness and health wearable, priced at $179.99 and scheduled to become available on October 27.

The announcement represents more than another hardware upgrade. It reinforces Google’s ambition to combine wearable sensors, artificial intelligence, personalized coaching and longitudinal health data into a connected ecosystem.

Fitbit Edge sits between the minimalist Fitbit Air and the more advanced Pixel Watch 5. It offers an attractive combination of advanced biometric monitoring, built-in GPS, AI-powered health coaching and up to seven days of battery life.

Google is also strengthening its connection with professional sports through its collaboration with four-time NBA champion Stephen Curry, who helped create a special-edition Fitbit Edge priced at $219.99.

The strategic question is no longer simply whether Google can build a competitive fitness tracker. It is whether Google can use its hardware, AI capabilities and distribution to become a major player in the increasingly competitive health and sports-performance technology market.

For professional sports teams, the implications are interesting. Although Fitbit Edge is primarily a consumer device, its combination of affordability, biometric monitoring and continuous data collection could create opportunities in athlete recovery monitoring, sleep management, wellness and offseason training.

However, its usefulness in elite sports will depend on measurement accuracy, data accessibility, athlete compliance and whether its insights can be integrated into existing performance-management systems.

Key features of the Fitbit Edge

U.S. pricing and announced specifications; battery life varies by settings and usage.

A. Advanced biometric and recovery monitoring

Fitbit Edge integrates several sensors and metrics that could be relevant to sports performance and athlete wellness.

Google has also introduced Health Guardian capabilities designed to identify longer-term trends associated with blood pressure and insulin resistance. These are wellness indicators, not clinical measurements or diagnostic substitutes, and some capabilities are marked as coming soon or subject to regional availability.

Upside analysis: The greatest potential value is not an isolated HRV, sleep or temperature reading. It is the ability to establish individual baselines and identify meaningful changes over weeks or months.

For example, an athlete experiencing consistently reduced sleep duration, elevated resting heart rate and lower HRV could warrant a conversation with the performance staff. These signals are nonspecific, however, and should not independently determine training availability.

B. AI-powered coaching and automatic activity detection

Google is integrating Fitbit Edge into its broader Google Health Coach platform, powered by Gemini.

The system can provide personalized workout suggestions, adjust plans based on user goals and routines, and help interpret changes in health and fitness data.

Google says Fitbit Edge supports more than 50 exercise modes and can automatically recognize up to 100 types of workouts.

This creates an opportunity to move beyond passive data collection toward contextual recommendations.

Upside analysis: AI-powered coaching could become one of the most consequential areas of competition in wearables.

However, consumer AI recommendations should not be confused with individualized training prescriptions developed by qualified sports scientists, strength coaches or medical staff.

C. GPS, display and usability improvements

For teams, the integrated GPS could be useful for tracking individual outdoor runs and general activity. It should not be considered a replacement for dedicated team-sport GPS systems from providers such as Catapult Sports or STATSports without sport-specific validation.

D. Battery life, durability and repairability

Fitbit Edge offers up to seven days of battery life under Google’s specified conditions, although using the always-on display can reduce that to approximately two days.

The device also features a replaceable battery, a repairable architecture and water resistance rated to 5 ATM.

These features could matter for professional teams seeking to reduce charging interruptions, hardware replacement costs and gaps in continuous monitoring.

How Fitbit Edge fits into Google’s broader portfolio strategy

Google is building a more segmented wearables portfolio rather than relying on a single device to satisfy every consumer.

Google’s strategy appears to have four major dimensions.

First, expanding the addressable market. Fitbit Air appeals to consumers who prefer discreet, screenless monitoring. Fitbit Edge targets active users who want visible metrics without a full smartwatch. Pixel Watch serves users seeking more extensive smartwatch functionality.

Second, creating a unified health intelligence platform. Google Health Coach provides a software layer that can connect data from multiple wearable form factors and turn it into personalized recommendations.

Third, increasing recurring revenue opportunities. Google Health Premium provides subscription-based coaching capabilities, potentially expanding revenue beyond the initial hardware sale.

Fourth, using athletes to strengthen credibility. Stephen Curry’s involvement helps Google connect its consumer health proposition with athletic performance, although an athlete endorsement does not establish scientific validation for elite-sport applications.

The bigger strategic opportunity: owning the health intelligence layer

In the longer term, Google’s advantage could come less from the Fitbit Edge hardware itself and more from its ability to combine data, AI models and consumer distribution.

Google can potentially collect longitudinal wellness information, interpret patterns through Gemini-powered services and create increasingly personalized user experiences.

This could reshape competition by making software quality, data integration and actionable insights as important as hardware accuracy.

The key challenge is trust. Consumers and athletes will need clarity about data ownership, privacy, model reliability and how recommendations are generated.

How competitors are likely to react

Fitbit Edge enters an increasingly crowded market dominated by established brands including Apple, WHOOP, Oura, Garmin and Samsung.

At $179.99, Google is positioning the device at a price that could appeal to consumers who want sophisticated health monitoring without purchasing a more expensive smartwatch.

Importantly, the following competitive responses are Upside’s forecasts, not confirmed announcements.

The competitive context is significant. Earlier in 2026, Google’s launch of Fitbit Air had already put pressure on the screenless wearable category, prompting industry discussion about WHOOP’s competitive response.

The next battleground: AI and subscriptions

We expect competition to intensify across four areas:

1. AI-driven interpretation: Turning raw physiological data into personalized and understandable insights.

2. Pricing: Offering more health and fitness functionality at accessible hardware and subscription prices.

3. Ecosystem integration: Connecting wearables with third-party platforms, training applications and health records.

4. Measurement quality: Demonstrating reliable accuracy across different populations, sports and conditions.

Google has the scale and technical resources to compete aggressively. However, WHOOP, Garmin and Oura retain specialized expertise and established customer relationships that Google will need to overcome.

How professional sports teams could use Fitbit Edge

Although Google has not positioned Fitbit Edge as a dedicated professional team-performance platform, there are several applications worth evaluating.

E. Athlete monitoring at scale

One potential advantage of Fitbit Edge is its relatively affordable price.

For example, the upfront hardware cost for a hypothetical deployment would be:

Calculated using the announced $179.99 U.S. retail price, excluding taxes, replacement devices, subscriptions, support and integration costs.

At this price point, teams could consider deploying devices across first-team squads, academy athletes or development programs.

However, the financial comparison should include the total cost of ownership, not just hardware.

An additional question is whether Google will develop enterprise-level dashboards, bulk device management, team-specific reporting and direct integration with athlete management systems.

Without these capabilities, Fitbit Edge may be more practical as an individual wellness device than as a fully integrated team monitoring solution.

Recommendations to professional sports teams

Rather than immediately replacing existing wearables, we recommend a structured evaluation of Fitbit Edge.

Recommendation 1: Conduct a controlled pilot

Start with 10–15 volunteer athletes over a six-to-eight-week period.

Compare Fitbit Edge against the team’s existing devices and measurement protocols.

Focus on heart rate accuracy, HRV consistency, sleep duration, GPS tracking, athlete comfort and data completeness.

Recommendation 2: Evaluate data accessibility before purchasing

This is particularly important.

Google is transitioning from the legacy Fitbit Web API to the new Google Health API, with the legacy API scheduled to shut down on October 30, 2026.

Google’s new API supports modernized data access and integration capabilities, but developer onboarding and access are subject to restrictions.

Teams should confirm whether they can securely access the metrics they need and integrate them into their existing athlete management systems.

Recommendation 3: Assess real-world athlete compliance

Even the most sophisticated wearable has limited value if athletes refuse to wear it consistently.

Teams should evaluate comfort during sleep, charging requirements, compatibility with training routines and willingness to share data.

Recommendation 4: Validate the metrics independently

Do not assume Google’s consumer accuracy claims translate directly to professional athletes.

In particular, teams should examine whether optical heart rate, HRV and sleep metrics perform reliably across different skin tones, movement intensities, environmental conditions and individual physiology.

Compare relevant outputs with established reference methods rather than relying solely on correlations between consumer devices.

Recommendation 5: Protect athlete privacy and autonomy

Biometric information can be sensitive.

Teams should establish clear policies covering informed consent, data ownership, access permissions, retention periods and whether information may be used in employment or selection decisions.

Health-related and reproductive-health data require particularly careful governance.

Recommendation 6: Evaluate AI recommendations separately from sensor accuracy

Even if Fitbit Edge measures certain metrics accurately, it does not automatically follow that its AI-generated recommendations are appropriate for elite athletes.

Teams should test whether the Google Health Coach provides useful, explainable guidance without making unsupported assumptions about readiness, injury risk or recovery needs.

Recommendation 7: Consider complementary deployment

Fitbit Edge could complement rather than replace existing solutions.

For example, a team could continue using Catapult or STATSports for on-field external-load monitoring while evaluating Fitbit Edge for overnight wellness and offseason activity.

This approach may provide more complete athlete context without abandoning existing investments.

Key questions Google still needs to answer

Despite its promising specifications, several questions remain important for professional sports adoption.

• Will Google offer dedicated team dashboards, group analytics or enterprise licensing?

• How accurately will Fitbit Edge measure HRV, sleep and heart rate in elite athletes compared with reference methods?

• Can performance staff access sufficiently granular data through supported APIs?

• Will Google provide validated sport-specific algorithms and actionable insights?

• How will Google protect sensitive athlete information when AI coaching and third-party integrations are involved?

These questions will ultimately determine whether Fitbit Edge can become a credible option in the professional sports technology market.

Conclusion: The wearable market is becoming an AI ecosystem battle

Google’s introduction of Fitbit Edge is an important development in the evolution of wearable technology.

At $179.99, the device combines a broad set of physiological monitoring features, GPS, AI-powered coaching and a lightweight design at a competitive price.

More importantly, it reflects a shift in Google’s strategy: from selling individual fitness devices toward building a connected health ecosystem that combines hardware, software, data and artificial intelligence.

For competitors such as WHOOP, Oura, Garmin and Apple, the pressure will increasingly extend beyond sensor technology. Companies will need to differentiate through accuracy, user experience, AI-driven insights, interoperability and long-term value.

For professional sports organizations, Fitbit Edge deserves attention, particularly for sleep monitoring, recovery trends, offseason training and broader athlete wellness.

However, Google has not yet demonstrated that Fitbit Edge can replace the specialized systems used by elite teams.Independent validation, enterprise capabilities and data integration remain essential.

The larger industry trend is clear: the future of wearables will not be defined solely by who collects the most data, but by who can transform reliable data into useful, trustworthy and actionable insights.

Our view at Upside: Google’s greatest opportunity may not be selling Fitbit Edge to professional teams. It may be establishing Google Health and Gemini as a foundational intelligence layer across the broader sports-performance and wellness ecosystem.

That is a development every sports technology company—and every professional team’s performance department—should be watching.

Primary sources and further reading

• Google’s official Fitbit Edge announcement — October 12, 2026

• Fitbit Edge technical specifications

• Google Health ecosystem strategy

• Google Health API and developer integration

• DC Rainmaker’s Fitbit Edge technical analysis

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Why proprietary data, intellectual property, scientific validation and domain expertise will determine the winners and losers in the next generation of sports technology.

Introduction: The Explosion of AI in Sports Technology

Over the past several years, I have seen an increasing number of sports technology startups positioning themselves as AI companies.

Every week, it seems that another startup is launching an AI-powered platform promising to transform professional sports.

Some claim they can predict injuries before they happen. Others promise to revolutionize scouting, biomechanics, athlete monitoring, coaching, recovery, performance analytics or tactical analysis.

And while I believe artificial intelligence has tremendous potential to transform professional sports, I am increasingly concerned about something.

Many of these startups are starting to look and sound remarkably similar.

They use similar language, promise similar outcomes and often present similar dashboards.

Almost every company claims to have proprietary algorithms, predictive analytics or an AI-powered platform capable of generating insights that traditional technologies cannot provide.

But how many of these companies actually possess technology that competitors cannot easily replicate?

And how many are essentially building applications on top of commercially available foundation models, third-party APIs and widely accessible datasets?

These are becoming increasingly important questions for professional sports teams, investors and the sports technology industry.

The next phase of AI in sports will not simply be about who uses artificial intelligence. It will be about who has developed something genuinely differentiated, defensible and scientifically validated.

The Problem: AI Is Becoming Increasingly Accessible

One of the biggest changes in the technology industry is that developing AI-powered applications has become significantly easier.

A few years ago, building sophisticated machine learning capabilities often required substantial investment in data science teams, infrastructure, model development and specialized engineering.

Today, startups can access powerful foundation models from companies such as OpenAI, Google, Anthropic and Meta.

They can also leverage cloud computing, open-source machine learning frameworks, pretrained computer vision models and commercially available analytics tools.

This has dramatically reduced the barriers to entry.

A startup can now develop an AI-powered athlete monitoring dashboard, video analysis platform or coaching assistant much faster than was possible just a few years ago.

That is a positive development because it accelerates innovation.

However, it also creates a major challenge: if everyone has access to similar AI capabilities, what makes one sports-tech startup fundamentally different from another?

Consider a hypothetical example.

Two startups offer AI-powered athlete monitoring platforms.

Both integrate GPS data, training loads, wellness questionnaires and historical injury records.

Both use machine learning to identify patterns and provide recommendations to performance practitioners.

Both claim their platform can help reduce injuries and optimize performance.

But one company has spent years collecting unique longitudinal datasets, developing proprietary algorithms and validating its models across multiple teams.

The other uses a commercially available machine learning model trained on a relatively small dataset.

Their marketing materials might look remarkably similar.

Yet the underlying scientific credibility, commercial value and defensibility of these businesses could be very different.

This is why teams and investors need to look beyond the AI label.

What Actually Creates a Competitive Moat in AI Sports Technology?

In venture capital, a competitive moat refers to the advantages that protect a business from competitors and make its position difficult to replicate.

In sports technology, I believe there are six major sources of defensibility.

A. Proprietary Data

One of the strongest potential competitive advantages is access to unique, high-quality datasets that competitors cannot easily obtain.

For example, a company that has collected longitudinal athlete performance data over ten years across multiple sports may have an advantage over a startup relying on publicly available information.

But proprietary data alone is not sufficient.

The quality, consistency and relevance of that data are equally important.

A database containing millions of GPS measurements is not necessarily valuable if it lacks reliable injury outcomes, athlete context or standardized measurement protocols.

Teams and investors should ask:

• What proprietary datasets does the company actually control?

• How many athletes, teams and seasons are represented?

• How were the data collected and standardized?

• Does the company have the legal rights to use those data for model training?

• Can the dataset be expanded as the business grows?

• Are the data representative of the populations where the product will be deployed?

There is also an important distinction between having access to data and owning the rights to use them.

A startup may integrate data from Catapult, STATSports, Garmin or another platform without owning those underlying datasets.

Access to third-party data is not necessarily a competitive moat, especially if competitors can obtain similar access.

B. Proprietary Algorithms and Technology

The second potential moat is the underlying technology.

Many AI startups describe their algorithms as proprietary.

But what does that actually mean?

Does the company own the underlying model architecture?

Has it developed a unique machine learning approach?

Does it use proprietary signal processing, computer vision or feature extraction methods?

Or is it primarily using a commercially available AI model with a customized interface?

There is nothing inherently wrong with using foundation models or third-party APIs. In fact, doing so can be an efficient development strategy.

However, using commercially available AI technology does not automatically create a sustainable competitive advantage.

One question I would ask is:

If I gave the same dataset and problem to another competent AI development team, could they reproduce essentially the same results?

If the answer is yes, the company may need to demonstrate other sources of differentiation.

These could include proprietary data, superior workflow integration, distribution, customer relationships or independently demonstrated performance.

C. Intellectual Property and Patents

Intellectual property can provide another layer of protection.

Some sports-tech companies have developed patented technologies in areas such as wearable sensors, biomechanics, computer vision, physiological monitoring and hardware design.

However, patents should not be treated as automatic proof of defensibility.

Teams and investors need to understand:

• What exactly is patented?

• Does the patent protect the core technology or a relatively narrow feature?

• Is the intellectual property owned by the startup?

• How long will the protection remain in effect?

• Could a competitor develop a different technical approach that achieves similar results?

• Is the technology difficult to reproduce even without patent protection?

Patents can be particularly relevant for companies developing novel hardware, sensors or measurement systems.

For software-based AI companies, proprietary data, technical know-how and distribution may sometimes be more important than patents.

D. Scientific Validation

This is where I believe many AI sports-tech startups need to improve.

A company can have impressive technology, sophisticated algorithms and an attractive dashboard.

But does its product actually work?