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贝叶斯-xG:使用贝叶斯的等级方法对预期目标 (xG) 的球员和位置进行校正
Alexander Scholtes1, Oktay Karakuş1
1School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom.
Frontiers in sports and active living
|July 1, 2024
概括
贝叶斯分析显示,虽然球员位置影响得分概率 (预期进球或xG),但个体球员的技能显著影响xG更多,即使考虑到游戏环境. 这一发现适用于欧洲主要足球联赛.
科学领域:
- 运动分析 运动分析
- 统计建模 统计建模
- 足球分析 足球分析
背景情况:
- 预期进球 (xG) 度量对于评估足球投篮质量至关重要.
- 了解影响xG的因素,如球员位置和个人技能,对于性能分析至关重要.
研究的目的:
- 用贝叶斯方法研究球员位置和个人球员对预期目标 (xG) 预测的影响.
- 为了确定球员或位置因素是否显著地影响了射门导致进球的概率.
主要方法:
- 贝叶斯层次逻辑回归被应用于足球投篮数据.
- 分析使用了公开的StatsBomb数据,这些数据来自英格兰英超联赛,西班牙西甲和德国德甲.
- 模型结合了预测因素,如距离目标,射门角度和特定球员的调整.
主要成果:
- 在基本模型中观察到xG的位置效应,前和进攻中场显示得分可能性更高.
- 这些位置效应随着包含更具信息性的预测因素而减少.
- 显著的球员级别影响持续存在,表明单个球员对他们的xG有不同的影响,独立于其他因素.
结论:
- 球员特定的调整是预期目标 (xG) 预测中的持续和重要因素.
- 贝叶斯模型为分析足球投篮数据提供了可靠的结果,尽管先前的分配选择可以改进以提高效率.
- 这些发现为足球中的球员评估和战术分析提供了宝贵的见解.
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