🎙️ Upside Video Chat with Shaun Jayachandran, Product Advisor at GameRun.ai, a Leading AI Powered Athlete Analysis Tool.

Today we have the honor of interviewing Shaun Jayachandran, AI product advisor at GameRun.ai a leading AI powered athlete analysis tool.

GameRun.ai is a New York-based company that provides AI-driven solutions for youth sports management, including a platform for event information and performance analytics. The app works by having users upload a video for AI-based analysis to level up their skills. The AI analyzes game scores and provides personalized feedback to help athletes improve. Additionally, the platform allows users to build an athletic profile, track progress, and connect with coaches.

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 the pictures of GameRun.ai app:

Here is the picture illustrating the process to upload and analyze videos via the GameRun.ai app:

Picture: GameRun.ai

Here are the types of analyses performed by the GameRun.ai app:

Here is a video explaining how GameRun.ai works:

📝Show Notes: During his interview, Shaun discussed his journey from coaching and education to becoming the AI product lead for GameRun.ai. He described their product as an AI-powered athlete analysis tool that is agnostic to any camera system, providing detailed reports on player strengths, weaknesses, and potential. Shaun highlighted the benefits for teams, including unbiased analysis and the ability to evaluate an athlete’s body language and leadership. He explained that their AI determines player maturity by being trained on a tiered system from a young age.

He mentioned their large database of tens of thousands of films and their focus on including female athletes. As a key example, he shared how the app identified Cooper Flagg as a generational talent and accurately predicted an ankle injury based on his biomechanics. He also outlined their competitive advantages, business model, and future plans, which include expanding into sports like soccer, fencing, and lacrosse

Please note that GameRun.ai will be exhibiting at booth #28 at our 2025 Upside US Summit on October 21 at the Florida Panthers (NHL) stadium.

Here are the best quotes from the interview with Shaun:

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Q1. Tell me about your background.

“I’ve had a diversified background, starting in education and coaching basketball at very high levels. My high school coach was even coached by John Wooden from UCLA, so he brought that Wooden philosophy with him. About seven or eight years ago, I moved from education to the product side of tech in Boston. This journey was a combination of my passions and problem-solving, which led me to Game Run as the AI product lead for basketball”.

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Q2. Tell me about your company and product.

“What we’ve designed is unique because it’s agnostic of any camera system. We’re not a video subscription service. You simply upload a video of an athlete, whether it’s three minutes or two hours long, and provide demographic information like age, height, gender, and weight. Within four minutes, our system produces a detailed player report on strengths, weaknesses, and skill sets, and even offers a projection of where the athlete could be in a year. The reports can be provided in multiple formats, including a spoken avatar or a five-to-six-page PDF”.

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Q3. What are the benefits for teams to use your product and platform?

“The first benefit is an unbiased approach to evaluation. Our system doesn’t rely on subjective opinions; it analyzes an athlete’s skills and explosiveness based entirely on the film. Second, it provides the athlete with solid feedback, including timestamps, and even analyzes body language, coachability, and leadership. This allows the athlete to process feedback independently and see what the film shows without personal bias. For coaches, it serves as an extra tool to check their own biases and provides tangible evidence to share with parents regarding their child’s performance”.

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Q4. How do you determine the level of maturity of each player?

“We built our visual learning model from the ground up, starting with very young athletes. Instead of beginning with professional leagues, we introduced the platform to the sport in tiers, starting with a 7-year-old and building up from there. The system continually learns, and we’ve fine-tuned it with extensive analysis from experienced coaches and former professional athletes. This programmatic approach allows the AI to understand and distinguish different levels of play, such as a recreational level versus an EYBL player in basketball”.

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Q5. How big is your database?

“Our database consists of tens of thousands of films and analyses from different athletes. It was crucial for us to build a data set that included a strong representation of female athletes, as there hasn’t been as much research or data on them. Both my colleague Brendan, who leads the hockey side, and I have daughters, so we understand the importance of this representation”.

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Q6. What is your competitive advantage?

“Our competitive advantage is our focus on sport-specific, athlete-specific analysis. While other companies may focus on a single moment or overall game strategy, we hone in on a single person and what they do throughout an entire game. This allows us to track performance and decision-making over time, even as an athlete becomes exhausted. We believe in a blend of art and science, so we don’t just provide numerical data. We analyze how an athlete’s body moves and whether it’s progressing correctly. This helps us identify potential future stars based on skill, not just on being bigger or faster at a young age”.

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Q7. What kind of insights does your app generate on the athletes?

“We’re able to produce a detailed player report on strengths, weaknesses, different skill sets, assessments, how they compare against the level that you have set that they are playing at. (..) We also have PDF reports that comes out as a five six page PDF report that can provide that in analysis”.

“In our research and development, we are looking at ways to present this both as a single page cover page infographic, and then on the backend, another infographic on the biomechanics, that include like injury potential and where we see them.”

“We actually built in the idea of body language coachability leadership. So we’ve trained it to listen to and look at how it’s reacting, how the athlete’s reacting to their teammates, how they’re reacting when they go to the bench... what’s that feedback? Is it positive? Is it negative?”

“Our app actually shared low risk or higher risk of ACL. For example it can tell if there is a very high risk of injuring in the athlete’s ankle based on the way he jumps in traffic. (..) It was able to pick up on those small details of even how he was landing in the lane.”

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Q8. How the GameRun.ai app was able to identify Cooper Flagg as a generational talent.

“And in our research development, we looked at a young man who was just drafted into the NBA and we ran a game film from two years ago on him and and it was on Cooper Flag. We ran everything. We obtained a video from an AAU tournament and we identified who Cooper Flagg was in the video jersey number. And we told the learning model nothing about this young man. We run it and it was both telling us that he was a generational talent by telling us “Here’s the style of play that he excelled in”. And we looked at his biomechanics (see the analysis here). It actually shared low risk of ACL (see analysis here) because of the way ACL teared, and the way he rubbed higher risk, a very high risk of injuring his ankle based on the way he jumps in traffic in the lane.”

“And if you remember, in March, that’s exactly how Cooper Flagg got injured (see video here) at Duke. So our app was able to pick up on those small details of even how he was landing in the lane and. Fortuitously, it actually happened this march.”

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Q9. What is your business model?

“We’ve recently moved from a beta to open beta with paid subscriptions. We offer a few free videos to start. Our pricing varies based on the length of the film. For example, a package of three full-length game films costs about $300. We’re also developing enterprise packages for major programs and professional teams, like those in the MLB and NHL, who want to analyze their entire roster every game”.

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Q10. What are your plans for the next 12 months?

“We recently closed our seed round. We are now bringing our product to market and introducing paid subscriptions from the open beta. Our goal is to raise our Series A round later this winter. We are creating services for a few major league and NHL teams, but we also want to ensure the platform is accessible to everyone, which is the core ethos of AI. In the coming months, we will be expanding our sports offerings to include soccer, baseball, fencing, and lacrosse. We are also considering American football, but we’re also looking at flag football as an option”.

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