AILGMAApr 20

TacticGen: Grounding Adaptable and Scalable Generation of Football Tactics

arXiv:2604.1821055.7h-index: 25
AI Analysis

For football analytics and coaching, TacticGen provides a novel generative approach to tactical design, bridging the gap between predictive analysis and actionable tactic generation.

TacticGen is a generative model for football tactic generation that formulates tactics as sequences of multi-agent movements conditioned on game context. It achieves state-of-the-art precision in predicting player trajectories and enables adaptable tactic generation via classifier guidance, with a case study confirming its practical utility for professional tactical planning.

Success in association football relies on both individual skill and coordinated tactics. While recent advancements in spatio-temporal data and deep learning have enabled predictive analyses like trajectory forecasting, the development of tactical design remains limited. Bridging this gap is essential, as prediction reveals what is likely to occur, whereas tactic generation determines what should occur to achieve strategic objectives. In this work, we present TacticGen, a generative model for adaptable and scalable tactic generation. TacticGen formulates tactics as sequences of multi-agent movements and interactions conditioned on the game context. It employs a multi-agent diffusion transformer with agent-wise self-attention and context-aware cross-attention to capture cooperative and competitive dynamics among players and the ball. Trained with over 3.3 million events and 100 million tracking frames from top-tier leagues, TacticGen achieves state-of-the-art precision in predicting player trajectories. Building on it, TacticGen enables adaptable tactic generation tailored to diverse inference-time objectives through classifier guidance mechanism, specified via rules, natural language, or neural models. Its modeling performance is also inherently scalable. A case study with football experts confirms that TacticGen generates realistic, strategically valuable tactics, demonstrating its practical utility for tactical planning in professional football. The project page is available at: https://shengxu.net/TacticGen/.

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