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A football player performs drills on the pitch while a computer vision system tracks and grades his movements

Neural networks are spotting up-and-coming players for some of the best teams in football (known as soccer in the United States).

What’s new: AiSCOUT uses computer vision to grade amateur footballers and recommends those who score highest to representatives of professional teams, Forbes reported.

How it works: Amateurs upload videos of themselves performing eight drills such as passing, shooting, and dribbling around cones. AiSCOUT scores the performance on a scale of 0 to 2 relative to others it has evaluated (a score of 1.7 might prompt an in-person trial with a top team).

  • In addition, the system assigns up to 10 points for skills like “speed,” “dribble,” and “agility” relative to youth players who have been accepted to train with a team. Scouts and coaches can use these scores to compare prospects or track their development over time.
  • A few high-profile soccer clubs have expressed enthusiasm for the app including English Premier League clubs Chelsea (which helped develop the system) and Nottingham Forest, as well as Olympiacos of the Greek Super League.
  • Former English Premier League club Burnley, which also helped develop the system and used it in 2021, fell into the second tier in 2022 — a decline that raises questions about the app’s effectiveness.

Behind the news: Machine learning is being used to improve performance in a wide range of sports.

  • Mustard analyzes video clips to grade baseball pitchers’ performance.
  • Zone7 analyzes data from wearable sensors and athletes’ medical histories to forecast the risk that an athlete will suffer an injury in the future. It also suggests changes to an athlete's routine that may prevent injury.
  • Sportlogiq analyzes broadcasts of ice hockey, soccer, and American football games to help teams, leagues, and media organizations identify promising athletes.
  • SwingVision watches videos of tennis games to track shot type, speed, placement, and posture; leads and evaluates drills; and enables players to compare their performances to those of others.

Why it matters: Talent scouts have been obsessed with data since the days of pencil and paper. Machine learning can help clubs to cast a wider net and give far-flung aspirants a shot at going pro.

We’re thinking: We get a kick out of this app!


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