📚 Upside Studies: (1) Soccer Study: Evening Smartphone Exposure Impairs Sleep Quality (2) NBA Study: Optimizing Offensive Gameplan with ML (3) Force Plate Jump Study, and More

⚽ Upside Study (1): Evening Smartphone Exposure Impairs Sleep Quality and Next-Day Performance in Elite Soccer Players: A Randomized Controlled Trial

Authors: Nadia Dridi, Mohamed Abdelkader Souissi, Rim Dridi, et al.

Published in: Biology of Sport, 2026

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🔎 Introduction

Sleep is vital for athletic recovery and for optimizing both physical and psychological performance. However, elite athletes are often susceptible to poor sleep quality and habitually short sleep duration. One significant external factor contributing to declining sleep is the use of light-emitting electronic devices, such as smartphones, in the hours before bedtime. Exposure to this blue light can disrupt the human circadian clock, acutely suppressing melatonin, the sleep-facilitating hormone, which can lead to a reduction in overall sleep quality and quantity.

While the acute effects of electronic device use on sleep have been studied, the cumulative impact of consecutive nights of use on an athlete’s next-day cognitive and physical performance, particularly with regard to time-of-day variations, has been largely unexplored in soccer players.

You can download the full PDF study by clicking on the link below:

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🎯 Research Objective and Scope

The study aimed to examine the effects of using a smartphone for two hours prior to bedtime for five consecutive nights on young elite soccer players:

1. To examine the impact on sleep quality.

2. To assess its effect on both cognitive and physical performance.

3. To investigate potential time-of-day variations in these effects.

The researchers hypothesized that smartphone use would impair sleep quality (increasing sleep latency and reducing total sleep duration), lead to declines in cognitive performance (attention and reaction time), and reduce physical performance (reactive agility and explosive strength), with effects more pronounced in the morning due to cumulative sleep deprivation.

⚙️ Methodology

This was a randomized controlled crossover trial involving 16 male elite-level soccer players (mean age 19.75±1.0 years) from a professional Tunisian Premier League club.

• Conditions: Participants were assigned to two trials separated by a one-week washout period:

  • Experimental (Electronic Device, ED): Participants used a tablet (with quantified blue light exposure) to watch standardized, neutral entertainment videos for two hours (8:00 PM to 10:00 PM) before bedtime for five consecutive nights.

  • Control (C): Participants read neutral printed magazines or relaxed while avoiding sleep for two hours (8:00 PM to 10:00 PM) before bedtime for five consecutive nights.

• Measurements: Sleep quality was assessed following nights 1, 3, and 5. Cognitive and physical performance tests were conducted on the mornings (7:00 AM-8:30 AM) and afternoons (5:00 PM-6:30 PM) after days 1, 3, and 5.

  • Sleep Measures (Subjective): Sleep Onset Latency (SOL), Total Sleep Time (TST), Sleep Efficiency (SE), subjective sleep quality (SSQ), Spiegel Score, and Epworth Sleepiness Scale (ESS).

  • Cognitive Tests: Simple Reaction Time (SRT), Choice Reaction Time (CRT), Trail Making Test (TMT), and Digit Cancellation Test (D-CAT, a measure of attention).

  • Physical Tests: Squat Jump (SJ), Countermovement Jump with Arm Swing (CMJA), and Reactive Agility Test (RAT).

• Controls: The study controlled for lighting, room temperature, noise levels, standardized dinner time, and eliminated caffeine/alcohol intake. Training loads were also standardized across all participants.

📊 Key Findings

Sleep Quality Impairment

Five nights of pre-bedtime smartphone use significantly impaired sleep compared to the control group.

• Increased Sleepiness: Subjective sleepiness, measured by the ESS, was significantly higher in the electronic device (ED) group after day 3 and day 5 compared to the control group.

• Reduced Duration and Efficiency: The ED condition significantly shortened Total Sleep Time (TST) and reduced Sleep Efficiency (SE).

• Delayed Onset: Sleep Onset Latency (SOL)—the time it takes to fall asleep—was significantly increased after nights 1, 3, and 5 in the ED group compared to control.

Performance Decline and Time-of-Day Effects

The impairments worsened cumulatively over the five nights and were stronger in afternoon sessions. The typical time-of-day (TOD) advantage, where performance is often better in the afternoon (observed in the control group), disappeared or even reversed following five nights of smartphone use in the ED group.

• Cognitive Performance: After five days of smartphone use, there was a significant deterioration in Choice Reaction Time (CRT) and Simple Reaction Time (SRT) in the afternoon sessions compared to both baseline and the control group. This resulted in enhanced morning performance compared to the afternoon after day 5, a reversal of the pattern seen in the control condition.

• Physical Performance: After five consecutive nights of smartphone use, physical performance tests showed a decreased jumping ability (SJ, CMJA) and slower Reactive Agility Test (RAT) times. This decline was particularly pronounced in the afternoon sessions.

⚠️ Limitations

The study had several methodological limitations:

• Small Sample Size: The sample size (n=16) limits statistical power and the generalizability of the findings.

• Subjective Measures: The reliance on subjective sleep assessments (diaries, ESS) lacks the precision of objective measures like polysomnography or actigraphy.

• Mechanism Ambiguity: The lack of physiological marker assessment (e.g., melatonin, cortisol) limits the ability to confirm the hypothesized underlying biological mechanisms (melatonin suppression).

• Limited Generalizability: The sample consisted exclusively of elite male soccer players, restricting the generalization of the results to female athletes or other sports/age groups.

🧠 Implications for Practice

The findings emphasize the negative impact of prolonged nighttime blue light exposure. The practical implications for athletes and practitioners include:

• Implement Device-Free Periods: Athletes should implement device-free periods prior to bedtime (e.g., minimizing screen exposure) or activate blue light filters to minimize circadian disruption.

• Adjust Training Schedules: Given the cumulative performance decline and the disappearance of the typical afternoon advantage, training and competition schedules may need to be adjusted. Technical and high-intensity sessions may be more effective during morning hours following evening screen exposure.

• Promote Sleep Hygiene: Coaches should educate athletes on the risks of nighttime screen use and promote optimal sleep hygiene practices for recovery and performance.

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✅ Conclusion

The study provides clear evidence that the cumulative effect of five consecutive nights of evening smartphone use significantly impairs sleep quality (reduced TST, increased SOL, increased sleepiness) and negatively impacts both cognitive and physical performance in elite soccer players. Crucially, the effects were stronger in the afternoon, suggesting an interaction with the athlete’s natural circadian rhythm. This underscores the need for strategic management of electronic device use to sustain peak athletic performance.

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🏀 Upside Study (2): Optimizing Offensive Gameplan in the NBA with Machine Learning

Author: Eamon Mukhopadhyay, Purdue University ¹Published in: Unpublished (Conference or journal not specified, paper dated 2024 based on internal references) ²

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🔎 Introduction

The National Basketball Association (NBA) has undergone an analytical revolution over the last two decades, leading to the development of numerous specific metrics beyond general box score quantities. Pioneering work, such as Dean Oliver’s Basketball on Paper (2004), guided the shift toward using metrics alongside the “eye-test” for decision-making⁴. While the main offensive goal is to score points on a possession, the question arises: what truly drives a team’s Offensive Rating (ORTG), a metric developed by Oliver that accounts for possessions?

Traditional metric evaluation uses individual analysis ⁶, but an alternative is to model existing metrics using machine learning techniques to gauge the combined effectiveness of a unique set of features, particularly those related to a team’s offensive game plan. This study aims to use machine learning to determine the specifics of game plan execution that maximize a highly functioning offense^.

You can download the full PDF study by clicking on the link below:

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🎯 Research Objective and Scope

The paper had two main goals:

1. To develop multiple hypotheses for optimizing team game plan by finding the best-fit machine learning models and, if accurate, displaying hypothetical testing data to maximize a team’s ORTG^9999999.

2. To evaluate the effectiveness of using machine learning models to determine what can build an existing metric (like ORTG) using advanced features (offensive play types), rather than simply creating a new one^10101010.

The dependent variable modeled was Offensive Rating (ORTG)^11111111. The independent features were derived exclusively from non-box-score, playtype-based statistics¹².

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⚙️ Methodology

The study used cumulative team playtype statistics from every NBA team from the 2015–2016 to the 2022–2023 NBA seasons, yielding 240 total data points^13131313. All data was sourced from the official NBA website and Synergy¹⁴.

• Dependent Variable: Offensive Rating (ORTG), normalized from 0 to 1^15151515.

• Independent Features: The initial set included 48 features, consisting of 8 play types multiplied by 6 internal features¹⁶.

  • Playtypes Used (8): Isolation, Transition, Pick and Roll Ball Handler, Pick and Roll Roll Man, Post Up, Spot Up, Cut, and Off Screen¹⁷.

  • Internal Features (6): FREQ% (Frequency Percentage), FG% (Field Goal Percentage), FT% (Free Throw Frequency Percentage), TOV% (Turnover Percentage), FREQ% (again), and SCORE FREQ%^18181818.

  • Excluded Playtypes: Putbacks, Misc (Miscellaneous), and Handoff, as they do not typically represent a specific offensive scheme¹⁹.

• Feature Reduction: Principal Component Analysis (PCA) was used to reduce the feature count to 18 to avoid underfitting and improve accuracy.

• Machine Learning Models: Two regression models were tested:

  1. Simple Linear Regression

  2. A supervised Multi-Layer Perceptron Regressor (MLPR) Neural Network

• Validation: Leave-one-out cross-validation was used to build multiple model iterations, with the overall performance judged by Root Mean Square Error (RMSE) and Coefficient of Determination ($\text{R}^2$)^23232323.

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📊 Key Findings

Model Performance

Both models showed a strong correlation with Offensive Rating, but the Neural Network performed slightly better^2424242424.

• Neural Network (MLPR):

  • $\text{R}^2$ (Coefficient of Determination): 0.694²⁵.

  • RMSE: $\approx0.107$ (or 2.16 ORTG points)²⁶.

  • The optimal network had 1 hidden layer with a size of 3²⁷.

• Simple Linear Regression:

  • $\text{R}^2$: $\approx0.665$²⁸²⁸.

  • RMSE: $\approx0.112$ (or 2.26 ORTG points)²⁹.

Game Plan Optimization Hypotheses

Based on the more effective neural network model, the following play types were encouraged to optimize ORTG^30303030:

1. Heavy Isolation Emphasis: One-on-one (isolation) plays should be heavily emphasized, ideally accounting for nearly 20-25% of play frequency³¹. This forces the defense to remain honest and can generate kick-out opportunities for spot-up shooting³².

2. High-Efficiency Spot-Up Shooting: Teams should maximize their spot-up plays with both a high-efficiency (Field Goal Percentage of 40–42% or higher) and a high-rate (25–28% frequency is optimal)³³. The model noted spot-up shooting as an essential play type to score on³⁴.

3. Utilize Transition Opportunities: Transition opportunities should be used to generate offensive firepower, ideally at 17–20% of general plays³⁵. Transition was also noted as a best scoring method³⁶.

4. Efficient, Non-Aggressive Pick-and-Roll: The game plan should use a general rate of around 15% frequency for pick-and-roll possessions finished by the ball-handler and roll-man³⁷. The emphasis should be on ball efficiency (low turnovers) and forcing defensive help to create additional spot-up opportunities. The model suggested a non-aggressive scoring approach to the pick-and-roll may yield higher offensive output.

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⚠️ Limitations

The author noted several limitations in the study:

• Dataset Size: The size of the dataset (240 cumulative team-season statistics) combined with the number of features may raise questions, although PCA was used to mitigate this⁴⁰.

• Model Scope: The study did not test higher, more advanced machine learning systems (like Bayesian methods or polynomial regression) despite the initial models having notable correlations⁴¹.

• Exceptions Exist: The hypotheses represent general offensive trends, and exceptions exist, such as the Golden State Warriors’ unique playstyle or the 2022-23 Sacramento Kings’ record ORTG achieved with a limited use of isolation plays^42424242.

• Context Missing: The model does not measure the true impact of the schemes on other factors like defensive intensity or offensive discipline⁴³. Also, it delegates the in-depth analysis of whether a team’s players are sufficient to meet the game plan’s goals to other papers⁴⁴.

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✅ Conclusion

The study successfully demonstrated that a machine learning model, specifically a Multi-Layer Perceptron Regressor (MLPR) neural network, can effectively model a well-known statistic like NBA Offensive Rating (ORTG) using advanced playtype features. The derived model showed a strong correlation and was used to mathematically visualize an optimal hypothetical game plan. The four game plan hypotheses—emphasizing high-frequency, high-efficiency isolation, spot-up shooting, and transition plays, along with efficient, secondary use of the pick-and-roll—can guide coaches and executives toward a successful offensive scheme. The paper advocates for the widespread use of this machine learning method in sports analytics to determine what builds an existing metric, rather than relying solely on simple metric analytics^.

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🏀 Upside Study (3): Investigation of Force Plate Jump Testing Metrics Relevant to Return to Play Decision Making in Basketball Athletes After Anterior Cruciate Ligament Reconstruction

Authors: Christopher S Hart, Elizabeth S Chumanov

Published in: International Journal of Sports Physical Therapy (IJSPT), 2025

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🔎 Introduction

Basketball is a high-risk sport for lower limb injuries, with knee injuries accounting for 16.3% of total injuries in adolescent competitive players. The ACL injury incidence rate is 0.16 per 1,000 athlete-exposures for collegiate or semi-professional players. Following Anterior Cruciate Ligament Reconstruction (ACLR), roughly one in three young athletes suffer a second ACL injury upon returning to sport, despite following recommended timelines and achieving satisfactory performance benchmarks.

Force plate vertical jump testing is used in the clinical setting to identify persistent lower limb asymmetries that can remain even after an athlete has been cleared on conventional strength and horizontal hop tests. However, there is no consensus on which vertical jump task, or which of the hundreds of available metric combinations, is most relevant for basketball athletes post-ACLR.

You can download the full PDF study by clicking on the link below:

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🎯 Research Objective and Scope

The purpose of this retrospective cohort study was to examine the jump performances of male high school and collegiate basketball athletes in the final stages of ACLR rehabilitation to:

1. Establish referenceable between-limb symmetry scores.

2. Identify metrics that best detect between-limb asymmetry during common vertical jump tasks.

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⚙️ Methodology

• Study Design: Retrospective cohort examination.

• Participants: 49 male high school and collegiate basketball athletes who underwent primary ACLR. Participants were in the final stages of rehabilitation and intended to return to competitive basketball.

• Grouping: Participants were divided into two groups based on their isokinetic quadriceps peak torque Limb Symmetry Index (LSI):

  • Quad LSI <90% (n=24).

  • Quad LSI >90% (n=25).

• Testing: Athletes completed testing using in-ground, dual force plates (sampling at 1,000Hz). The tests included:

  1. Double-Leg Countermovement Jump (DL-CMJ).

  2. Single-Leg Countermovement Jump (SL-CMJ).

  3. Single-Leg Repeat Hop (SL-RH).

• Analysis: Independent samples t-tests were used to compare the LSI of various jump metrics between the two quadriceps strength groups. The LSI was calculated as (Surgical Limb/Nonsurgical Limb) * 100.

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📊 Key Findings

Asymmetry Detection by Task

Basketball athletes with quadriceps strength asymmetry (Quad LSI <90% ) demonstrated greater asymmetry in two of the three jump tasks:

• Double-Leg Countermovement Jump (DL-CMJ): Significant differences in LSI were found between the groups.

• Single-Leg Repeated Hop (SL-RH): Significant differences in LSI were found between the groups.

• Single-Leg Countermovement Jump (SL-CMJ): No significant differences in LSI were found between the groups.

Key Metrics for Detecting Asymmetry

Metrics that showed statistically significant differences (p<0.05) between the Quad LSI <90% and Quad LSI >90% groups (with large effect sizes) included:

DL-CMJEccentric Rate of Force Development (RFD)−22.71.28Concentric Impulse−22.41.06Concentric Impulse 100ms−24.01.50Peak Take-Off Force−12.72.61SL-RHJump Height−12.40.81Flight Time:Contact Time13.30.84

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🧠 Implications for Practice

• Battery of Tests is Crucial: The inconsistency in findings—especially the lack of difference in the SL-CMJ test between groups—suggests that isokinetic testing (quadriceps strength) does not consistently align with jump test findings across all tasks. This highlights the importance of implementing a battery of jump tests to ensure the restoration of multiple physical qualities required for basketball.

• DL-CMJ and SL-RH are More Sensitive: DL-CMJ and SL-RH metrics demonstrated the highest sensitivity for detecting between-limb asymmetry in this population when a quadriceps deficit was present.

• Limitations of 90% LSI: The referenceable data shows large variability between jump tasks and metrics, which discourages relying on the 90% LSI benchmark as a single proxy for jump symmetry criteria. Clinicians are encouraged to reference the standard deviations and coefficient of variation for jump metrics as supplemental criteria.

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📚 Future Research Directions

Future research should address limitations by:

• Including allometric scoring (relative to body weight) to establish meaningful cutoffs.

• Conducting longitudinal research to compare performance against uninjured control groups and to analyze the relationship between graft type and outcomes.

• Including psychological readiness outcome measures.

• Utilizing peak eccentric velocity to standardize the effort of the athlete during testing.

✅ Conclusion

The three studies presented offer critical, data-driven insights into optimizing performance and recovery in elite athletes across soccer and basketball, validating the necessity of an evidence-based approach in modern sports science and management.

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⚾ Effectiveness of Single Leg Isometric Bridge and Nordic Hamstring Exercise Testing for Prediction of Hamstring Injury Risk in Professional Baseball Players

Authors: Austin R. Driggers, Andrew C. Fry, Kristen C. Chochrane-Snyman, John P. Wagle, and Jeffrey M. McBride

Published in: The American Journal of Sports Medicine, 2025

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🔎 Introduction

Hamstring strain injury (HSI) imposes a significant burden on elite athletes, including those in professional baseball, leading to substantial financial costs for organizations¹¹¹¹. While various factors have been studied, muscular strength is the only modifiable risk factor with robust support for injury risk mitigation strategies²²²².

Previous research has linked low eccentric hamstring strength, as measured by the Nordic Hamstring Exercise (NHE), to an increased risk of future HSI in other sports³³³³. However, the efficacy of strength testing remains inconsistent across studies, leading to a need for further investigation⁴⁴⁴⁴. Furthermore, no studies have examined the new modified Single Leg Isometric Bridge Test (SLIBT) as a predictor of HSI risk, nor have either the SLIBT or NHE been specifically studied in professional baseball players⁵⁵⁵⁵.

You can download the full PDF study by clicking on the link below:

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🎯 Research Objective and Scope

The primary aims of this prospective cohort study were to determine:

1. Whether preseason hamstring strength and interlimb asymmetry measured using the modified SLIBT and the standard NHE are associated with future HSI in professional baseball players⁶⁶⁶⁶.

2. The relationship (correlation) between hamstring strength and interlimb asymmetry measures obtained from the SLIBT versus the NHE⁷⁷⁷⁷.

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⚙️ Methodology

• Study Design: Prospective cohort study; Level of evidence, 3⁸⁸⁸⁸.

• Participants: 465 male professional baseball players from 8 teams affiliated with a single Major League Baseball (MLB) organization⁹⁹⁹.

• Data Collection: Preseason hamstring strength assessments were completed as part of routine athlete monitoring before the 2019, 2021, and 2022 seasons¹⁰. A total of 38 new HSI events were recorded in 36 players over 751 player-seasons^11111111.

• Testing Procedures (Force Measurement):

  • Nordic Hamstring Exercise (NHE): Participants performed the standard bilateral eccentric lowering motion on a NordBord apparatus, which independently measured the eccentric peak force of each leg^12121212.

  • Modified Single Leg Isometric Bridge Test (SLIBT): Participants performed a single-leg isometric bridge on dual-force platforms (ForceDecks) with two modifications: a $20^\circ$ knee angle (to maximize biceps femoris activation) and a loaded barbell ($100 \text{kg}$) to secure the hips. Isometric peak force was measured for each leg^13131313.

• Statistical Analysis:

  • Absolute Strength Comparison: Injured limb strength was compared to the mean strength of the uninjured group¹⁴.

  • Relative Risk (RR): RR was calculated using ROC-determined strength cutoffs to assess HSI risk^15151515.

  • Logistic Regression: Used to determine the odds ratio for HSI incidence with every $10\text{N}$ increase in strength¹⁶.

  • Correlation: Pearson $r$ was calculated for strength and asymmetry measures between the NHE and SLIBT^171717171717.

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📊 Key Findings

1. Low Hamstring Strength is a Risk Factor (NHE & SLIBT)

Lower hamstring strength levels in subsequently injured limbs were observed compared with the two-limb mean strength of healthy, uninjured players for both tests^{1818181818181818}.

• NHE Absolute Strength: Players with an NHE strength of $<377 \text{N}$ had a 2.5-fold higher risk of subsequent HSI (Relative Risk (RR), $2.49$; $P=.027$)^191919191919.

• Risk Reduction per 10-N Increase (Logistic Regression): An inverse relationship was found between strength and HSI risk²⁰²⁰.

  • SLIBT: Each $10\text{N}$ increase in peak force corresponded to a $7.4\%$ HSI risk reduction ($P=.019$)^21212121.

  • NHE: Each $10\text{N}$ increase in peak force corresponded to a $6.2\%$ HSI risk reduction ($P=.019$)^22222222.

2. Interlimb Asymmetry is NOT Predictive

Interlimb asymmetry measures from both the SLIBT and NHE were not indicative of subsequent HSI^{23232323232323}. Additionally, no significant differences were found when comparing the strength of the subsequently injured limb versus the contralateral uninjured limb within the injured group²⁴.

3. Correlation Between Tests is Moderate

• Strength: Moderate significant correlations were observed for both absolute strength ($r=0.39$; $P<.001$) and relative strength ($r=0.33$; $P<.001$) between the SLIBT and the NHE^{25252525252525252525}.

• Asymmetry: No significant correlations were found between measures of interlimb asymmetry when assessed by the SLIBT versus the NHE^26262626.

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🧠 Implications for Practice

• Screening and Intervention: Both the SLIBT and NHE can be valuable tools to identify professional baseball players at risk of future HSI due to low strength levels^27272727.

• Targeted Training: For players exhibiting low hamstring strength on either test, strength and preventative training prescriptions should specifically target improving these scores to decrease individual HSI risk, especially targeting low levels of eccentric strength (NHE)²⁸.

• Combined Testing: The moderate correlation and lack of correlation for asymmetry between the two tests reinforce that a multifaceted strength testing process offers the most value, as results from one test cannot be used to inform the results of the other^{2929292929292929}.

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⚠️ Limitations

• Recurrent Injuries Excluded: Recurrent HSIs were excluded, limiting analysis of reinjury risk³⁰.

• Injury Severity: The grade of the HSI was not included in the study, focusing instead on time missed (player availability) rather than radiological severity³¹.

• Specificity of Injury Mechanism: The difference in SLIBT (isometric) and NHE (eccentric) tests measures different actions, and the low agreement between them aligns with the general challenge of lower body strength testing^32323232.

• Bland-Altman Bias: Bland-Altman analysis indicated a bias toward higher strength values using the NHE compared with SLIBT scores (mean difference of $34.4 \text{N}$)^33333333.

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✅ Conclusion

The current investigation demonstrates that low levels of hamstring strength, as measured by both the SLIBT and the NHE, are significantly associated with an increased risk of future HSI in professional baseball players^34343434. Crucially, an NHE peak force of $<377 \text{N}$ was linked to a 2.5-fold higher risk^35353535. The findings support using both the SLIBT and NHE preseason to identify at-risk players and to inform mitigation strategies aimed at increasing strength to limit HSI rates and maximize time at play^36363636. While strength levels were predictive, interlimb asymmetry was not, and the moderate correlation between tests indicates that they measure related but distinct aspects of hamstring strength^37373737.

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🏀 Upside Special Report: High Stakes and Hard Lessons: Examining the NBA’s Latest Gambling Scandal and Its Implications for Professional Sports

The NBA is currently embroiled in a significant gambling scandal that has raised serious concerns about the integrity of the league. On October 23, 2025, federal authorities arrested several individuals, including Portland Trail Blazers head coach Chauncey Billups, Miami Heat guard Terry Rozier, and former Cleveland Cavaliers assistant coach Damon Jones, as part of a wide-ranging investigation into illegal sports betting and rigged poker games. These developments have sent shockwaves through the basketball community and prompted urgent questions about the intersection of sports, gambling, and organized crime.

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What We Know So Far

The federal investigation, led by the FBI, has uncovered two primary schemes:

1. Rigged Poker Games: Billups and Jones are accused of participating in high-stakes poker games orchestrated by the Gambino and Lucchese crime families. These games allegedly employed advanced cheating devices, such as rigged shuffling machines, x-ray tables, and marked cards, to defraud wealthy players out of millions of dollars. The FBI claims that insiders relayed information about winning hands to off-site operators, who then communicated with players through concealed technology.

2. Insider Sports Betting: Rozier is accused of providing non-public information about game outcomes to bettors, including details about his own performance and potential injuries. In one instance, he allegedly informed gamblers that he would exit a game early due to a feigned injury, allowing them to place profitable bets against the Miami Heat.

These activities have led to charges of wire fraud conspiracy and money laundering conspiracy against all three individuals. If convicted, they face potential prison sentences of up to 40 years.

Here is the FBI press conference on the arrests of Chauncey Billups, Terry Rozier & Damon Jones:

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The Types of Technologies used in the NBA gambling scandal

Rigged Poker Devices

• Shuffling Machines: Advanced automatic shuffling machines were allegedly manipulated to control the order of cards, giving certain players a huge advantage.

• X-ray Tables or Scanners: Some tables reportedly had embedded devices capable of “seeing” cards through minor modifications, allowing players or co-conspirators to know opponents’ hands.

• Marked Cards with Optical or Magnetic Tracking: Certain cards may have been marked subtly so that accomplices could detect their value using hidden optical sensors or small magnetic devices.

Electronic Communication and Data Transmission

• Hidden Earpieces and Bluetooth Devices: Players and co-conspirators could receive real-time information about hands or game conditions through concealed earpieces.

• Smartphone or Tablet Signals: Coordinators off-site could monitor live games and communicate instructions discreetly, essentially acting as a remote “cheating hub.”

Insider Information for Sports Betting

• Real-Time Game Data Access: Terry Rozier and others allegedly shared non-public information about player injuries, minutes, or strategy, which could be exploited for bets.

• Encrypted Messaging Apps: The use of secure or encrypted apps allowed conspirators to coordinate bets and relay sensitive information without detection.

In short, the scandal isn’t just about illegal betting—it’s about combining traditional gambling with modern technology to gain unfair advantages. The sophisticated tech used here raises concerns not just for the NBA but for the broader sports gambling ecosystem.

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How Much Money Is Involved?

The financial implications of these schemes are substantial. The rigged poker operations alone reportedly defrauded victims of over $7 million. Additionally, the insider betting activities have led to fraudulent wagers worth hundreds of thousands of dollars. While exact figures for the total amount of illicit gains are still being determined, the scale of the operations suggests that tens of millions of dollars may have been involved across both schemes.

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What Is the NBA Doing So Far?

In response to the arrests, the NBA has taken immediate action. Both Billups and Rozier have been placed on indefinite leave, and former NBA player Tiago Splitter has been named interim head coach of the Trail Blazers. Commissioner Adam Silver expressed deep concern over the allegations, stating that preserving the integrity of the game is paramount for the league and its fans.

The NBA is cooperating fully with federal authorities and has pledged to take further action as the investigations progress. However, the league’s authority is limited compared to that of federal investigators, and Silver has emphasized the importance of due process.

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Where Do We Go From Here?

The NBA faces significant challenges in restoring its reputation and ensuring such incidents do not recur. Congress has requested a briefing from Commissioner Silver by October 31, 2025, to address concerns about the scandal and its implications for sports betting and game integrity.

In the meantime, the league may need to implement stricter policies, enhance monitoring systems, and collaborate more closely with law enforcement to prevent future breaches. The outcome of this scandal will likely have long-term implications for the NBA’s policies and its relationship with the burgeoning sports betting industry.

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How Big Is Gambling in the NBA?

The NBA has a complex relationship with sports betting. While the league has embraced partnerships with sportsbooks like FanDuel and data firms such as Sportradar, the recent scandal highlights the risks associated with the growing industry. Legal sports betting in the U.S. generated $10 billion in revenue through the third quarter of 2025, marking a 19% increase from the previous year. The NBA’s involvement in this market has raised questions about the balance between revenue generation and maintaining the integrity of the sport.

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Past Scandal: The 2007 NBA Referee Betting Scandal

The current scandal is not the first time the NBA has faced issues related to gambling. In 2007, former NBA referee Tim Donaghy was implicated in a betting scandal that shook the league. Donaghy admitted to betting on NBA games, including those he officiated, and providing inside information to gamblers. He was sentenced to 15 months in prison and three years of supervised release.

Picture: Former NBA referee Tim Donaghy

The 2007 scandal led to significant changes in the NBA’s policies regarding officiating and gambling. The league implemented stricter monitoring of referees and established a zero-tolerance policy for any involvement in gambling activities. Despite these measures, the recent scandal involving players and coaches suggests that the NBA’s efforts to maintain the integrity of the game may need to be reevaluated and strengthened.

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Gambling Scandals Across Other Sports

The NBA is not alone in grappling with gambling-related controversies. Other major sports leagues have faced similar issues:

• Major League Baseball (MLB): In 2024, San Diego Padres infielder Tucupita Marcano was banned for life for betting on baseball games, including those of his own team. He placed 387 bets totaling over $150,000. Additionally, four other players received one-year suspensions for betting on baseball. This marked the first lifetime ban in MLB for gambling since Pete Rose in 1989.

Picture: Tucupita Marcano

• National Football League (NFL): In 2019, Arizona Cardinals cornerback Josh Shaw was suspended for the entire 2020 season for placing a legal bet on NFL games while on injured reserve. The league emphasized its strict policy against any form of gambling involvement by players.

Picture: Former Arizona Cardinals cornerback Josh Shaw

• National Hockey League (NHL): In 2006, assistant coach Rick Tocchet of the Phoenix Coyotes was implicated in a gambling ring that involved placing bets on NHL games. The scandal, known as “Operation Slap Shot,” led to legal actions against several individuals, including Tocchet.

Picture: Rick Tocchet

These incidents underscore the pervasive nature of gambling-related issues across professional sports and highlight the ongoing challenges leagues face in safeguarding the integrity of their games.

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Gambling’s Expanding Role in Elite Sports

Gambling has become a significant revenue stream for elite sports leagues worldwide. The global sports betting market was valued at approximately $108.92 billion in 2024 and is projected to reach $198.53 billion by 2030, driven by regulatory reforms and increased adoption (Source: Yahoo Finance)

In the United States, legal sports betting has been rapidly expanding since the repeal of PASPA in 2018. As of 2025, 39 states and Washington, D.C., have legalized sports betting in some form PlayToday.co. In 2025 alone, U.S. bettors are expected to wager a record $30 billion on the NFL season, marking an 8.5% increase from the previous season (Source: New York Post)

This surge in sports betting has led to increased partnerships between leagues and gambling operators. For instance, Flutter Entertainment, the world’s largest online betting company, projects substantial earnings growth for 2025, driven by its U.S. brand, FanDuel (Source: The Times)

However, this rapid growth also raises concerns about the potential for misconduct and the integrity of the games. The recent NBA gambling scandal serves as a stark reminder of the risks associated with the increasing intertwining of sports and gambling.

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Recommendations for Mitigating Future Gambling Issues

• Enhanced Monitoring and Analytics: Implement advanced data analytics and monitoring systems to detect unusual betting patterns, suspicious transactions, or irregular in-game behavior among players, coaches, referees, and other team personnel. Continuous monitoring can help identify potential issues before they escalate into scandals.

• Mandatory Education and Awareness Programs: Require all team members, including players, coaches, referees, and support staff, to participate in annual education programs. These should cover the legal and financial risks of gambling, the ethical implications, and the potential personal and professional consequences of misconduct.

• Strengthened Partnerships with Regulators and Law Enforcement: Build stronger relationships with federal and state law enforcement agencies, gaming regulators, and licensed sportsbooks. Sharing intelligence and collaborating on investigations can help prevent illegal betting networks from targeting NBA personnel.

• Stricter Internal Policies and Oversight: Enforce clear internal rules regarding gambling, including mandatory disclosure of financial transactions and restrictions on access to gambling platforms. Teams should regularly audit communications and financial activity related to betting to maintain accountability.

• Promoting a Culture of Integrity and Accountability: Encourage open conversations about ethics, integrity, and responsible behavior. Leadership at both the league and team levels should model zero-tolerance behavior toward gambling violations, reinforcing the NBA’s commitment to fair play.

• Proactive Use of Technology: Explore using secure apps and AI-based surveillance tools to flag suspicious communications or transactions in real time. Technology can serve as an early warning system to prevent misconduct before it affects the league.

• Support Systems for At-Risk Individuals: Offer confidential counseling or support programs for personnel who may be vulnerable to gambling-related pressures, helping to mitigate personal risks and protect the league’s reputation.

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Conclusion

The recent gambling scandal involving NBA figures has cast a shadow over the league’s commitment to fair play and integrity. As investigations continue, the NBA must take decisive action to address the issue, restore public trust, and implement measures to safeguard against future misconduct. The outcome of this scandal will likely have long-term implications for the league’s policies and its relationship with the burgeoning sports betting industry.

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🚀 Upside Weekly Recap: Newly Redesigned Upside Global Site,Upside Career Launch, Samsung Launches XR Glasses; Oura app debuts Cumulative Stress Feature; New SKUs Added to Database.

As a reminder, in July 2025 we announced our new AI based product comparison tool (Interactive tables, Upside AI Assistant) which is part of our Upside Tech scouting platform which is being trusted by 100+ teams (NBA, NFL, MLS, MLB, NHL, WNBA, Premier League, NCAA, national rugby teams, Top 14, Calcio, laliga, pro tennis..).

At Upside, we’ve built one of the most comprehensive performance technology databases in sports and tech with the top 500 products and companies in performance tech. From GPS tracking and recovery systems to strength training solutions and biometric monitoring tools, our platform covers the products shaping athlete performance today.

But technology in sports moves fast—new SKUs, product launches, and price changes are happening constantly. That’s why our team updates the database every single week, so that teams, practitioners, and decision-makers always have access to the most accurate and up-to-date information.

Our brand-new Product Comparison Tool offers a comprehensive comparison of over 500 performance products and companies across a wide range of categories (AMS, GPS, hydration assessment tools, cognitive training, velocity training systems, video analysis, sleep tech, etc..). Whether you’re evaluating vendors for AMS platforms, velocity training, or other categories, this tool allows you to compare pricing, specifications, customer bases, capabilities, funding, and more—all in one place.

Here is a screenshot of what our Upside AI assistant looks like:

Picture: Upside Global, confidential, October 2025

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🚀 Official Announcement: Newly Redesigned Upside Global Site, with the introduction of Upside Career

This week we also unveiled our newly redesigned Upside Global site, with Upside Global now including three core businesses:

• Upside Tech Scouting: An AI-based platform designed to help sports teams discover and vet top technologies to boost performance, save time and money, and maintain a competitive edge.

• Upside Career: An AI-powered recruiting platform that connects sports organizations and technology vendors with ideal candidates.

• Upside Consulting: Focuses on accelerating business development for startups in elite sports by helping them expand into new markets/leagues and assisting with fundraising through a network of trusted teams and investors. Upside also helps teams with special projects focused on innovation, tech scouting, and so on.

As part of that, we officially announced this week at our Upside US Summit “Upside Career”—our new AI-driven recruiting platform designed to connect practitioners, teams, and startups in sports, performance, and technology.

What Upside Career Will Offer:

• Create a Career Profile – Showcase your experience, education, and unique skill set.

• Explore Job Listings – Browse open positions across elite teams, leagues, and startups.

• Upload Your Resume – Keep your credentials ready for rapid applications.

• AI Job Matching – Get matched to relevant roles based on your profile.

• Smart AI Introductions – Our AI assistant introduces candidates directly to employers.

• Connect with Teams – Communicate with hiring teams about opportunities and growth.

• Attend Job Fairs – Join Upside-hosted virtual and in-person career fairs.

Here is a video explaining how the Upside Career platform works:

We will soon allow candidates to create their profiles and for teams to post job opportunities. We are also in advanced conversations with top Universities to organize job fairs with top universities/NCAA organizations and teams in 2026. More details coming soon.

As a reminder, Upside Global is a network of 10,000 sports executives. The Upside Newsletter is sent 5 days per week to practitioners (Head of performance, HAT, Head of rehab, S&C coaches, PTs..) of all the NBA, NFL, MLS, MLB, NHL teams, 130 NCAA teams, top European soccer teams (Premier League, Calcio, Laliga, Ligue 1..), national rugby teams, tennis academies, top VCs, investors.

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📩 Summit Recap Coming Soon

Next week, we’ll be sending out a full event recap including photos, videos, and highlights from all panel discussions and key moments—stay tuned!

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📅 What’s Next for Upside

Join us at our upcoming events:

• 2025 Upside VIP Dinner – MLS Symposium | December 10 | Atlanta, GA

• 2026 Upside VIP Dinner – NBA Summer League | July 2026

• 2026 Upside VIP Event – Atlético Madrid Stadium | September 2026

• 2026 Upside Annual Summit | Date & Location TBD

We are working on organizing additional Upside events in the US and Europe in 2026.

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Want to Speak or Sponsor an Upside Event?

If you’re interested in speaking or sponsoring one of our future Upside events, please contact us at: julien@upsideglobal.co

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📘 New Products Added this Week to the Upside Product & Company Database

This week we added the following new specs/pricing changes, and new SKUs and products below to our database of the top 500 performance tech products and companies.

Source: Upside Product/company Database, Confidential, October 2025

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Learn More About Upside Global

If you want to learn more about Upside Global and our services—including Upside Tech scouting platform, Upside Career, and Upside Consulting—please visit www.upsideglobal.co or email us at julien@upsideglobal.co.

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Join Today

All these features—the product comparison tool, Upside AI assistant, are available through flexible membership options, including monthly and annual plans. The practitioner community and product review sections are free for all practitioners. So if you are a practitioner who wants to join our online community of practitioners please contact us at julien@upsideglobal.co and we will create your online exec profile.

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📖 Upside Analysis of the Week

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🔍 Recent M&A Deals Of The Week

Excel Sports Management majority-stake acquisition by Goldman Sachs (~US$1 billion)
The asset-management arm of Goldman Sachs is reportedly finalizing a deal to acquire a controlling interest in Excel Sports Management, valuing the talent-agency at around US$1 billion. (Source: Reuters)
Upside Take: This deal underscores how institutional investors continue to view sports ecosystem firms (talent agencies, representation, brand management) as vehicles for growth and diversification. The near-US$1 billion valuation reflects scale, global reach, and premium multiples in the sports-business intermediary layer. The risk: talent agencies are exposed to athlete performance, reputational risk, and regulatory scrutiny; effective integration and alignment between Goldman’s infrastructure and Excel’s talent-led culture will be critical.

Adapti signs LOI to acquire Levelution Sports
Adapti (OTC: ADTI) has signed a Letter of Intent to acquire Levelution Sports, a sports-technology/analytics provider; financial terms have not been disclosed. (Source: Seeking Alpha)
Upside Take: This acquisition highlights the ongoing strategic interest in sports-tech and analytics firms — rather than traditional team or league assets. For Adapti, buying a company like Levelution could bolster its product ecosystem with data/analytics capabilities, positioning the firm for growth in the intersection of sports + technology. The risk: Integration and monetisation of sports-analytics businesses are still challenging—realising value will depend on converting tech into scalable revenue.

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📌 Big Picture / Significance

• The fact that a leading global bank is acquiring a major sports-talent agency shows how financial institutions are moving deeper into the sports value chain, beyond teams and rights.

• The deal signals valuation strength in adjacent sports services firms (agent/management, brand representation) not just franchise ownership.

• This transaction could act as a precedent for further consolidation in the sports-services sector (agencies, marketing firms, talent-management) especially as margins for teams tighten and rights grow expensive.

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👀 Things to Watch Next

• Which other major agency or brand-management firms become targets for private equity or strategic buyers?

• How Goldman Sachs utilises Excel’s platform—Will the agency continue operating as stand-alone or integrate into a broader “sports asset” platform?

• Regulatory/league approval—While this is not a team purchase, athlete-representation deals can trigger attention around antitrust, league rules, and athlete compensation.

• Talent retention and culture—Post-deal execution will matter: will Excel maintain its competitive edge in attracting top athletes and securing high-value contracts?

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⌚ New Product / Initiative / Structural Moves

• Audicin’s wearable aims to hack your recovery while you work (Source: Wareable)

• Samsung teases smart glasses and partnerships with Warby Parker and Gentle Monster (Source: Wareable)

• Samsung officially launches $1,799 Galaxy XR headset with Google and Qualcomm (Source: Wareable)

• Oura app update debuts Cumulative Stress and enhanced Cycle Insights (Source: Wareable)

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⭐ Major Coaching / Practitioner Moves

⚽ Soccer / Premier Leagues

Al-Ittihad appoints Sérgio Conceição (Saudi Pro League)
Sérgio Conceição has been hired to lead Al-Ittihad on a contract through 2028, replacing Laurent Blanc. Conceição arrives with a track record in Europe and a reputation for a high-tempo, disciplined style. Reuters

CF Montréal names Marco Donadel permanent head coach (MLS)
After serving as interim for much of 2025, Marco Donadel was given the permanent job at CF Montréal this week. mlssoccer

Nottingham Forest replace Ange Postecoglou with Sean Dyche (Premier League)
After poor results, Forest moved quickly to sack Postecoglou and appointed Sean Dyche as the new manager. Capital FM

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🏀 Basketball (NBA)

Phoenix Suns — Jordan Ott officially the head coach
Jordan Ott was named Phoenix’s head coach in the offseason and enters the 2025-26 season with a revamped staff and roster adjustments. Suns

New York Knicks — Mike Brown installed as head coach
Following Tom Thibodeau’s departure, the Knicks moved to Mike Brown as Thibodeau’s replacement. The move continues the league’s pattern of teams choosing experienced, defensive-minded coaches to maintain competitive windows. Yahoo Sports

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🏒 NHL

Coaching & staff churn continues
Staff changes are surfacing early in the 2025-26 NHL season — e.g., the New York Islanders moved on from goalie coach Piero Greco after a short stretch. (reporting via local outlets). New York Post

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⚽ MLS

Atlanta United parts ways with Ronny Deila
Atlanta United announced the club has parted ways with head coach Ronny Deila after a disappointing season. mlssoccer

MLS coaching tracker: multiple clubs formalizing internal hires
Several clubs have used interim promotions this season and are converting successful caretaker runs into full appointments (examples tracked by MLSsoccer). mlssoccer

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⚾ MLB

Texas Rangers promote Skip Schumaker to manager
Skip Schumaker was officially named the Rangers’ manager — an internal promotion and continuity hire after front-office involvement during 2025. Reuters+1

Rays Assistant GM Carlos Rodriguez departs after 15 years
Longtime Rays executive Carlos Rodriguez left the organization this week, ending a 15-year tenure. DRaysBay+1

Other MLB notes: Several franchises have finalized internal extensions or retained interim managers (Pirates extended Don Kelly; Giants and Twins moves continue to ripple through the market). FanGraphs Baseball

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🏫 NCAA (College Football / Basketball)

Florida fires Billy Napier (Football)
Florida dismissed Billy Napier after a 3-4 start; an interim coach has been named for the remainder of the season. This is part of a rapidly developing college-coaching carousel with multiple Power-4 jobs now open. ESPN.com

Broader NCAA signal: Multiple FBS and FCS programs have made midseason changes, reflecting escalating impatience among boosters and ADs. CBS Sports

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🏉 Rugby

St Helens parted ways with Paul Wellens; Munster backs Clayton McMillan
Clubs oscillate between severing ties for missed objectives (St Helens) and doubling down with financial support for new coaches (Munster CEO publicly backing Clayton McMillan). Matt Ferguson is also linked to involvement with England A coaching. (previous reports updated). saudigazette

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🔍 Big Picture — What’s New / Why It Matters

• Continuity + internal promotions remain the dominant theme across leagues. Teams prefer trusted insiders who can maintain cultural momentum (MLB Rangers; MLS/MLS clubs converting interims). MLB.com

• Boards and owners are more interventionist and faster to act. From England’s Premier League quick hires/fires to collegiate ADs pulling triggers midseason, decision-makers want immediate results. The Masters News

• Front-office churn (Rays) and coaching shakeups (Forest, Atlanta, Florida) will affect pipelines and recruitment. Expect scouting and developmental adjustments as new regimes stamp their philosophies. DRaysBay

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👀 Things to Watch Next (highest leverage)

1. Who fills the remaining Premier League vacancies? (Forest’s path and ripple effects).

2. MLB offseason managerial dominoes — will veteran managers be poached/rehired? (Giants/Twins/Braves watchlist). FanGraphs Baseball

3. Florida’s replacement and the broader Power-4 coaching market — this will reallocate top coaching candidates across college football. ESPN.com

4. Munster’s recruitment under McMillan — will pledged support convert into marquee signings and sustained competitiveness? The Times of India

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🩸Upside Analysis: Why Fewer Blood Tests in Elite Sports Are Better than Too Many

Blood analysis has emerged as one of the most powerful tools in elite sport. It can help teams detect overtraining, undertraining, early signs of illness, and nutritional deficiencies before they translate into missed training days or injuries. However, many teams fall into the trap of over-testing—running too many blood tests without clear decision-making frameworks. This creates unnecessary noise, athlete frustration, and wasted resources. The future of blood analysis lies not in more tests, but in fewer, smarter, and more integrated tests that directly inform performance and recovery decisions.

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The Issue: Teams Run Too Many Tests

Elite organizations sometimes run broad blood panels weekly or even more often, without clear thresholds or intended interventions. This creates three core problems:

• Noise and false positives: More biomarkers mean more statistical noise. With dozens of analytes, abnormal values are expected by chance, leading to unnecessary concern or interventions (Mayo Clinic Proceedings).

• Athlete burden: Frequent blood draws can reduce athlete trust and compliance, especially when they don’t see actionable outcomes.

• Resource inefficiency: Broad panels are expensive and time-consuming for medical staff, siphoning budgets away from interventions with clearer impact (e.g., sleep optimization, recovery tech).

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Why Fewer Tests—and the Right Tests—Matter

• Sharper signal: Fewer but carefully selected biomarkers (such as creatine kinase, cortisol, testosterone:cortisol ratio, and salivary IgA) provide clearer trends tied directly to training load and recovery (PubMed Central).

• Athlete-specific insights: Longitudinal monitoring relative to baseline matters more than population norms (Frontiers in Sports).

• Actionability over curiosity: Every test should map to a clear action—whether that’s altering training load, adjusting nutrition, or triggering recovery modalities.

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Blood Analysis as the “Secret Sauce”

Blood analysis is now considered a hidden competitive advantage. Done well, it allows teams to:

• Detect overtraining through markers like reduced testosterone:cortisol ratios (Scientific Reports).

• Spot undertraining by identifying blunted immune or hormonal responses.

• Predict illness risk through salivary IgA monitoring (Journal of Strength & Conditioning Research).

By integrating these signals with load and sleep data, practitioners can intervene earlier and keep players available.

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Key Stats

• Illness absences: In elite soccer, median illness absence is 3 days per episode, showing the importance of preventive monitoring rather than blanket testing (PubMed).

• Role of illness in male professional football: Not a major contributor to time loss (Bjørneboe J, Kristenson K, Waldén M, Bengtsson H, Ekstrand J, Hägglund M; Br J Sports Med. 2016;50(11):699-702). (Source: PubMed)

  Key details:

  • The study covered 73 European professional football teams over four seasons (2011-2014), with 1,261,367 player-days recorded.

  • They found 1,914 illness episodes recorded.

  • They reported a median of 3 days absence per illness episode.

  • Illness incidence was 1.5 per 1000 player-days.

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Key Studies (with URLs)

1. Blood-based biomarkers for managing workload in athletes (Source here)

2. Emerging load-sensitive biomarkers (IL-6, HSPs, etc.) (Source here)

3. Hormonal aspects of overtraining (systematic review) (Source here)

4. Testosterone–cortisol ratio & stress in athletes (Source here)

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Why AI and AMS Integration Is a Winning Formula

Modern Athlete Management Systems (AMS) enhanced with AI are crucial for making blood analysis actionable:

• Integration over silos: Biomarker data layered with GPS, wellness, sleep, and training load creates a holistic picture (Source: Orreco + Kinduct partnership). Please note that Kinduct is now part of Teamworks.

• Predictive insights: AI can detect patterns (e.g., CK spike + low sleep + poor IgA) that precede soft tissue injuries.

• Translation to staff: Dashboards translate complex data into simple green/amber/red flags and recommendations.

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Case Studies

• Orreco × Orlando City SC (MLS): Orreco’s BioMarkers 3.0 platform provides targeted blood analysis, helping the club individualize training and recovery (Orreco case reference).

• Atlanta Hawks (NBA): Orreco helped Hawks players integrate biomarker insights into training load and recovery, reducing overtraining risk (Source: Orreco NBA partnership).

• England Women’s National Team (Lionesses): Used Orreco’s FitrCoach and FitrWoman to integrate menstrual cycle, blood markers, and training load to optimize performance (Sky Sports report).

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Future of Blood Analysis (5–10 Years)

• Less invasive monitoring: Move from venous blood draws to finger-prick, saliva, or sweat sensors for continuous data (NIH Roadmap).

• AI-driven digital twins: Personalized models predicting how an athlete will respond to training and nutrition.

• Context-aware alerts: Smart algorithms filtering “expected” changes from true red flags.

• Federated learning: Clubs sharing anonymized biomarker data to improve global reference ranges while keeping competitive IP safe.

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Recommendations to Teams

1. Define the question before testing. What decision will this test influence?

2. Adopt lean testing menus. Use broad screens in preseason, then shift to targeted readiness markers in-season.

3. Build individual baselines. Track changes relative to an athlete’s own norm, not population averages.

4. Integrate with AMS. Make biomarkers part of the same workflow as GPS and sleep—not standalone reports.

5. Educate athletes. Explain why fewer, focused tests are more accurate and less intrusive.

6. Measure ROI. Track reductions in injuries and illness against testing protocols to prove value.

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Conclusion

Blood analysis has enormous potential in elite sport, but more testing is not better testing. Oversampling creates noise, false positives, and athlete fatigue. The winning model is to focus on fewer, more meaningful biomarkers, integrate them into AI-powered AMS platforms, and link them directly to actionable decisions. Teams that adopt this approach will maximize player availability, reduce wasted resources, and stay ahead in the performance race.

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🏟️ Thank You for Making the 2025 Upside US Sports Tech Summit a Success! Announcing the Upside Career, an AI driven Recruiting Platform for Teams and Startups

Thank You for Making the 2025 Upside US Sports Tech Summit a Success!

What an unforgettable day at the 2025 Upside US Sports Tech Summit at the Amerant Bank Arena, home of the two-time Stanley Cup Champion Florida Panthers.

This Summit would not have been possible without the incredible support of our partners, sponsors, speakers, volunteers, and the Upside team—as well as the exhibitors, pro teams, investors, and attendees who traveled from around the world to be part of this event. Thank you for helping us bring the global sports tech community together.

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🌟 Highlights from the Summit

• Inspiring Speakers: 50+ industry experts—shared powerful insights shaping the future of sports.

• Speed Dating with Pro Teams: One of the most anticipated sessions brought together 27 innovative exhibitors and 30+ pro teams from the NBA, MLB, NHL, MLB, NWSL, UFL, USL, NCAA, WWE, tennis —5 minutes per team, real conversations, real deals.

• Unmatched Networking: Over 250 leaders across sports tech, venture capital, elite teams, startups, and performance connected to collaborate and innovate.

• Top-Tier Content & Innovation: 10 panels, 2 keynotes, and 27 cutting-edge exhibitors showcased the latest in AI, wearables, biometrics, rehab tech, performance analytics, fan engagement, and venue innovation.

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🙏 A Special Thank You to Our 26 Sponsors

We’re deeply grateful for the support of our sponsors:

Kinmetrix, HigherDOSE, Winback, Maxxx Force, Kinvent, Multi Radiance, Vert, Orreco, VALD, Quantum Movement, Aris, Cerbrec Beyond Blood, BrainLit, Danu Sports, ActivBody, OxiWear, Myocene, Prism Neuro, Machina Sports, Respo.Vision, GameRun.ai, Summus Medical Laser, Box Altitude, ThermoHuman, KinetikIQ, Output Sports.

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🚀 Official Announcement: Upside Career

We also officially announced Upside Career—our new AI-driven recruiting platform designed to connect practitioners, teams, and startups in sports, performance, and technology.

What Upside Career Will Offer:

• Create a Career Profile – Showcase your experience, education, and unique skill set.

• Explore Job Listings – Browse open positions across elite teams, leagues, and startups.

• Upload Your Resume – Keep your credentials ready for rapid applications.

• AI Job Matching – Get matched to relevant roles based on your profile.

• Smart AI Introductions – Our AI assistant introduces candidates directly to employers.

• Connect with Teams – Communicate with hiring teams about opportunities and growth.

• Attend Job Fairs – Join Upside-hosted virtual and in-person career fairs.

Here is a video explaining how the Upside Career platform works:

We will soon allow candidates to create their profiles and for teams to post job opportunities. We are also in advanced conversations with top Universities to organize job fairs with top universities/NCAA organizations and teams in 2026. More details coming soon.

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📩 Summit Recap Coming Soon

Next week, we’ll be sending out a full event recap including photos, videos, and highlights from all panel discussions and key moments—stay tuned!

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📅 What’s Next for Upside

Join us at our upcoming events:

• 2025 Upside VIP Dinner – MLS Symposium | December 10 | Atlanta, GA

• 2026 Upside VIP Dinner – NBA Summer League | July 2026

• 2026 Upside VIP Event – Atlético Madrid Stadium | September 2026

• 2026 Upside Annual Summit | Date & Location TBD

We are working on organizing additional Upside events in the US and Europe in 2026.

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Want to Speak or Sponsor an Upside Event?

If you’re interested in speaking or sponsoring one of our future Upside events, please contact us at: julien@upsideglobal.co

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Learn More About Upside Global

If you want to learn more about Upside Global and our services—including Upside Tech scouting platform, Upside Career, and Upside Consulting—please visit www.upsideglobal.co or email us at julien@upsideglobal.co.

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Thank You

To our partners, sponsors, speakers, volunteers, exhibitors, pro teams, and the entire Upside team—thank you for your trust, energy, and dedication. Upside is more than an event—it’s a community shaping the future of sports and technology.

See you at the next Upside event!

— The Upside Global Team

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