构建足球战术风格模仿数据集，让AI更真实复现球队实战行为。
TacSIm: A Dataset and Benchmark for Football Tactical Style Imitation
- 基于英超比赛画面，还原22名球员位置与动作，统一到标准球场坐标。
- 用空间占据相似度和运动向量相似度评估战术风格匹配程度。
- 提供统一仿真环境，支持量化与可视化评估团队协同表现。
当前足球模仿研究多聚焦于以进球或胜率为目标的奖励优化，较少关注真实球队战术行为的精准复现。本文提出TacSIm，一个大规模足球战术风格模仿数据集与基准测试。TacSIm基于单视角英超比赛转播画面，还原一队全部11名球员的动作，并将攻防场景下两队共22名球员的初始位置与动作投影至标准球场坐标系。该数据集定义了明确的风格模仿任务与评估协议，通过在规定时间段内的空间占据相似度与运动向量相似度，评估单支球队在时空维度上的战术风格一致性。我们在统一虚拟环境中运行多种基线方法，生成完整球队行为，实现对战术协作的定量与可视化评估。通过从转播到仿真的统一数据与度量标准，TacSIm建立了严谨的基准，用于衡量和建模符合真实战术风格的足球模仿任务。
原文摘要 · Abstract (English)
Current football imitation research primarily aims to opti mize reward-based objectives, such as goals scored or win rate proxies, paying less attention to accurately replicat ing real-world team tactical behaviors. We introduce Tac SIm, a large-scale dataset and benchmark for Tactical Style Imitation in football. TacSIm imitates the acitons of all 11 players in one team in the given broadcast footage of Pre mier League matches under a single broadcast view. Under a offensive or defensive broadcast footage, TacSIm projects the beginning positions and actions of all 22 players from both sides onto a standard pitch coordinate system. Tac SIm offers an explicit style imitation task and evaluation protocols. Tactics style imitation is measured by using spatial occupancy similarity and movement vector similarity in defined time, supporting the evaluation of spatial and tem poral similarities for one team. We run multiple baseline methods in a unified virtual environment to generate full team behaviors, enabling both quantitative and visual as sessment of tactical coordination. By using unified data and metrics from broadcast to simulation, TacSIm estab lishes a rigorous benchmark for measuring and modeling style-aligned tactical imitation task in football.
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