TacticAI: an AI assistant for football tactics

Zhe Wang (), Petar Veličković (), Daniel Hennes, Nenad Tomašev, Laurel Prince, Michael Kaisers, Yoram Bachrach, Romuald Elie, Li Kevin Wenliang, Federico Piccinini, William Spearman, Ian Graham, Jerome Connor, Yi Yang, Adrià Recasens, Mina Khan, Nathalie Beauguerlange, Pablo Sprechmann, Pol Moreno, Nicolas Heess, Michael Bowling, Demis Hassabis and Karl Tuyls ()
Additional contact information
Zhe Wang: Google DeepMind
Petar Veličković: Google DeepMind
Daniel Hennes: Google DeepMind
Nenad Tomašev: Google DeepMind
Laurel Prince: Google DeepMind
Michael Kaisers: Google DeepMind
Yoram Bachrach: Google DeepMind
Romuald Elie: Google DeepMind
Li Kevin Wenliang: Google DeepMind
Federico Piccinini: Google DeepMind
William Spearman: AXA Training Centre
Ian Graham: Liverpool FC
Jerome Connor: Google DeepMind
Yi Yang: Google DeepMind
Adrià Recasens: Google DeepMind
Mina Khan: Google DeepMind
Nathalie Beauguerlange: Google DeepMind
Pablo Sprechmann: Google DeepMind
Pol Moreno: Google DeepMind
Nicolas Heess: Google DeepMind
Michael Bowling: University of Alberta, Amii
Demis Hassabis: Google DeepMind
Karl Tuyls: Google DeepMind

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract 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.

Date: 2024
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DOI: 10.1038/s41467-024-45965-x

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