Key Takeaways
- ai.io’s aiScout app now serves 45,000 athletes in MLS’s MLSNext program with three annual assessments tracking performance over time
- The smartphone-based platform uses computer vision to analyze 22 body segments from video, creating standardized athletic profiles accessible anywhere
- Premier League partnerships with Chelsea FC and Burnley FC shaped the app’s football-specific metrics and benchmarking algorithms
- Reliance Foundation in India screens tens of thousands of youth annually, with one athlete earning a scholarship from a shared community phone
- The platform can reverse-match athletes to sports based on physical strengths, helping Olympic committees identify untapped talent pools
From Biomechanics Lab to Smartphone Screen
Ai.io developed aiScout while working in biomechanics research, the science of human motion. His co-founder Darren Peries identified a core problem: traditional scouting relies on limited human capacity and geographic proximity.
The numbers illustrate the challenge. Each Premier League scout can evaluate approximately 2,000 players annually, despite millions playing the game. Geography, cost, and access restrict even that limited pool.
aiScout addresses the bottleneck through cloud-based computer vision technology. Athletes download the free app, record themselves performing standardized drills, and receive analysis of their movement patterns. The system tracks metrics including speed, jump height, symmetry, coordination, and turning mechanics by analyzing 22 body segments and converting 2D video into inferred 3D models.
Building Club-Specific Assessment Criteria
Felton-Thomas partnered with Chelsea FC and Burnley FC to develop the platform’s football applications. Both clubs requested comparable, benchmarkable data with transparent methodology.
The development process required translating intuitive scouting expertise into algorithmic scoring. Scouts reviewed thousands of video pairs, indicating preferences between players. Their insights became the foundation for age and gender-specific benchmarks, ensuring 13-year-olds compete against their peers rather than older, more developed athletes.
The standardized drills include 10-meter sprints, counter-movement jumps, cone dribbling, passing, and shooting. These reflect traditional scouting assessments, now delivered through smartphone technology.
Early Success: The Player Down the Road
During initial testing with 50 UK college athletes, one participant stood out significantly. Ben, age 17, lived minutes from Chelsea FC’s training grounds but had never been scouted through traditional channels.
Based on his aiScout results, Ben received a trial with Chelsea FC. He scored in his under-18 debut and later signed with another Premier League club, eventually representing his country. The case demonstrated that talent proximity doesn’t guarantee visibility in conventional systems.
Scaling Across Markets and Sports
Reliance Foundation in India uses aiScout to extend its annual scholarship program beyond traditional scouting reach. The organization offers 11-year-old athletes five-year scholarships combining sport and education. Tens of thousands now complete assessments annually via the app, with scouts using the data to inform in-person selection days.
One athlete downloaded the app from a shared community phone, had never played organized sport, and earned a five-year scholarship based on his results.
The IOC and Intel deployed the technology in Senegal ahead of the Youth Olympics. The app was loaded onto tablets and distributed to military leaders and school teachers, who recorded thousands of students. Forty athletes were selected for training in wrestling, athletics, and football based on their performance data.
The platform also performs reverse talent matching. Athletes with high acceleration and reactive strength might suit rugby sevens or futsal. Strong upper body power and hand-eye coordination could indicate potential in baseball or softball.
MLS Integration and Multi-Sport Expansion
Major League Soccer rolled out aiScout to its MLSNext program, serving 45,000 athletes with pre-season, mid-season, and post-season assessments. Coaches and scouts access performance data in real time through a control center dashboard, tracking individual development over time.
The platform is expanding its movement libraries to include American football, basketball, baseball, and cricket. Core movement patterns including cuts, deceleration, jumps, throws, and strikes translate across multiple sports.
The system now supports multiple languages and is developing cloud-agnostic capabilities to enable country-specific customization in any region.
Strategic Implications
aiScout demonstrates how cloud-based computer vision can supplement traditional talent identification infrastructure. The technology addresses geographic and resource constraints while maintaining sport-specific assessment criteria developed with professional clubs and federations.
The MLS implementation provides longitudinal data tracking, a capability that extends beyond one-time scouting to ongoing athlete development monitoring. As the platform expands into additional sports and regions, its benchmark databases grow more comprehensive across age groups and athletic profiles.
via: TED
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