The most exciting young coach in soccer might not be at Bayer Leverkusen or Stade de Reims, or even Bologna FC. It might be at Google DeepMind.
For the past few years, the search giant’s artificial intelligence division has been working with Liverpool Football Club to bring AI to the world’s most popular sport. In 2021, DeepMind researchers developed a model that could predict where players would hit a penalty based on their outfield position. In 2022, they developed one that analyzed video footage of games to predict where players would run next, even when they went off screen. “But none of these systems were a complete prototype that could feasibly give useful suggestions to coaches in the real world,” says Petar Veličković, a staff research scientist at Google DeepMind and coauthor of a paper published today in Nature Communications. “We wanted to actually build something that could lead to a feasible system.”
Enter TacticAI. It started life as a predictive system for open play—one that could analyze a game and tell coaches who was most likely to receive a pass, or what their chances of creating a dangerous goal-scoring opportunity might be. But the data analysts and coaches at Liverpool wanted something simpler. “In open play you can’t make a lot of useful on-the-spot changes, because there’s 22 players, and it’s very dynamic, and if you try to make changes in the heat of the moment you might end up confusing people” says Veličković.
Instead, Liverpool suggested that DeepMind’s researchers focus on corner kicks. Roughly 10 times a game, the action on the field is effectively frozen and the attacking team gets an opportunity to swing the ball into the box. But only one in 50 corners actually results in a goal. Elite clubs already spend a huge amount of time in the lead-up to games preparing corner routines and defensive plans with elaborate running routes and blocking schemes. “If you can increase your chances to score or defend better at corners, that integrates over an entire season to really give you a competitive edge,” says Veličković.
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