用3D姿态数据分析足球突破成功的关键因素
What Makes a Dribble Successful? Insights From 3D Pose Tracking Data
- 通过3D姿态数据提取平衡与攻防方向对齐等新特征
- 结合3D特征后模型预测成功率显著提升
- 适合体育数据分析、智能训练系统研发者
数据科学在足球领域的作用日益重要，为个人与团队表现评估提供新路径。本研究聚焦于突破行为：进攻球员持球一对一摆脱防守球员的情境。以往研究多依赖2D位置追踪数据，难以捕捉平衡、朝向与控球等关键维度，限制了分析深度。本文利用3D姿态追踪数据，从2022/23赛季欧冠联赛的1,736次突破中提取新型姿态特征，并评估其对突破成功率的预测能力。结果表明，反映进攻球员平衡状态以及进攻方与防守方朝向一致性的特征，对预测突破成功具有显著信息量。将这些姿态特征融合进基于传统2D位置数据的模型后，整体性能得到可测量提升。
原文摘要 · Abstract (English)
Data analysis plays an increasingly important role in soccer, offering new ways to evaluate individual and team performance. One specific application is the evaluation of dribbles: one-on-one situations where an attacker attempts to bypass a defender with the ball. While previous research has primarily relied on 2D positional tracking data, this fails to capture aspects like balance, orientation, and ball control, limiting the depth of current insights. This study explores how pose tracking data (capturing players' posture and movement in three dimensions) can improve our understanding of dribbling skills. We extract novel pose-based features from 1,736 dribbles in the 2022/23 Champions League season and evaluate their impact on dribble success. Our results indicate that features capturing the attacker's balance and the alignment of the orientation between the attacker and defender are informative for predicting dribble success. Incorporating these pose-based features on top of features derived from traditional 2D positional data leads to a measurable improvement in model performance.
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