From DeepMind It can suggest tactics for soccer set-pieces that are even better than those created by professional club coaches. The system, called TacticAI, w

From DeepMind It can suggest tactics for soccer set-pieces that are even better than those created by professional club coaches. The system, called TacticAI, works by analyzing a dataset of 7,176 corner kicks taken by players for Liverpool FC, one of the biggest soccer clubs in the world. Corner kicks are awarded to an attacking team when the ball passes over the goal line after touching a player on the defending team. In a sport as free-flowing and unpredictable as soccer, corners -- like free kicks and penalties -- are rare instances in the game when teams can try out pre-planned plays. TacticAI uses predictive and generative AI models to convert each corner kick scenario -- such as a receiver successfully scoring a goal, or a rival defender intercepting the ball and returning it to their team -- into a graph, and the data from each player into a node on the graph, before modeling the interactions between each node. The work was published in Nature Communications today. Using this data, the model provides recommendations about where to position players during a corner to give them, for example, the best shot at scoring a goal, or the best combination of players to get up front. It can also try to predict the outcomes of a corner, including whether a shot will take place, or which player is most likely to touch the ball first.