Institute of Exercise Training and Sport Informatics, German Sport University Cologne, Cologne, NRW, Germany.
PLoS One. 2019 Jan 30;14(1):e0210191. doi: 10.1371/journal.pone.0210191. eCollection 2019.
The presented field experiment in an 11 vs. 11 soccer game set-up is the first to examine the impact of different formations (e.g. 4-2-3-1 vs. 3-5-2) on tactical key performance indicators (KPIs) using positional data in a controlled experiment. The data were gathered using player tracking systems (1 Hz) in a standardized 11 vs. 11 soccer game. The KPIs were measured using dynamical positioning variables like Effective Playing Space, Player Length per Width ratio, Team Separateness, Space Control Gain, and Pressure Passing Efficiency. Within the experimental positional data analysis paradigm, neither of the team formations showed differences in Effective Playing Space, Team Separateness, or Space Control Gain. However, as a theory-based approach predicted, a 3-5-2 formation for the Player Length per Width ratio and Pressure Passing Efficiency exceeded the 4-2-3-1 formation. Practice task designs which manipulate team formations therefore significantly influence the emergent behavioral dynamics and need to be considered when planning and monitoring performance. Accordingly, an experimental positional data analysis paradigm is a useful approach to enable the development and validation of theory-oriented models in the area of performance analysis in sports games.
本研究在 11 对 11 的足球比赛场景中进行了现场实验,首次使用位置数据在受控实验中检验了不同战术阵型(例如 4-2-3-1 对阵 3-5-2)对战术关键绩效指标(KPI)的影响。该数据是使用球员跟踪系统(1Hz)在标准化的 11 对 11 足球比赛中收集的。KPI 使用动态定位变量进行测量,例如有效比赛空间、球员宽度比、球队分离度、空间控制增益和传球效率。在实验性位置数据分析范式中,两种团队阵型在有效比赛空间、球队分离度或空间控制增益方面均无差异。然而,正如基于理论的方法所预测的,3-5-2 阵型在球员宽度比和传球效率方面优于 4-2-3-1 阵型。因此,在设计实践任务时操纵团队阵型会显著影响涌现的行为动态,在规划和监测表现时需要加以考虑。因此,实验性位置数据分析范式是在体育比赛表现分析领域开发和验证面向理论的模型的有用方法。