An artificial intelligence model can predict the outcome of corner kicks in football matches and help coaches design tactics that increase or decrease the probability of a player taking a shot at goal. Petar Veličković at Google DeepMind and his colleagues developed the tool, called TacticAI, as part of a three-year research collaboration with Liverpool Football Club. Corner kicks are awarded when the ball goes out of play over the goal line, and can be a good scoring opportunity for the attacking team. Because of this, football coaches develop detailed plans for various scenarios, which players learn ahead of games. TacticAI was trained on data from 7176 corner kicks in England's 2020 to 2021 Premier League season, including each player's position over time and their height and weight.

The main benefit is that the AI assistant reduces the workload of the coaches, says Ondřej Hubáček, an analyst at the sports data firm Ematiq who specializes in predictive models, and who did not work on the project. "An AI system can go through the data quickly and point out errors a team is making--I think that's the added value you can get from AI assistants," he says. To assess TacticAI's suggestions, GoogleDeepMind presented them to five football experts: three data scientists, one video analyst, and one coaching assistant, all of whom work at Liverpool FC. Not only did these experts struggle to distinguish's TacticAI's suggestions from real game play scenarios, they also favored the system's strategies over existing tactics 90% of the time. These findings suggest that TacticAI's strategies could be useful for human coaches in real-life games, says Petar Veličković, a staff research scientist at GoogleDeepMind who worked on the project.

Identifying key patterns of tactics implemented by rival teams, and developing effective responses, lies at the heart of modern football. However, doing so algorithmically remains an open research challenge. To address this unmet need, we propose TacticAI, an AI football tactics assistant developed and evaluated in close collaboration with domain experts from Liverpool FC. We focus on analysing corner kicks, as they offer coaches the most direct opportunities for interventions and improvements. TacticAI incorporates both a predictive and a generative component, allowing the coaches to effectively sample and explore alternative player setups for each corner kick routine and to select those with the highest predicted likelihood of success. We validate TacticAI on a number of relevant benchmark tasks: predicting receivers and shot attempts and recommending player position adjustments. The utility of TacticAI is validated by a qualitative study conducted with football domain experts at Liverpool FC. We show that TacticAI's model suggestions are not only indistinguishable from real tactics, but also favoured over existing tactics 90% of the time, and that TacticAI offers an effective corner kick retrieval system. TacticAI achieves these results despite the limited availability of gold-standard data, achieving data efficiency through geometric deep learning.