像梅西一样错过它:在足球中从目标外射中提取价值
Ethan Baron1, Nathan Sandholtz2, Devin Pleuler3
1University of Toronto, Toronto, ON, Canada.
Journal of quantitative analysis in sports
|March 13, 2024
概括
这项研究引入了新的足球分析指标,这些指标重视了远离目标的投篮,与当前的模型不同. 这些新型指标通过分析射击轨迹来更好地衡量射击技巧,提供更好的稳定性和预测能力.
科学领域:
- 运动分析 运动分析
- 足球分析 足球分析
- 性能测量 性能测量 性能测量 性能测量 性能测量
背景情况:
- 由于得分数据有限和上下文因素,测量足球射击技巧很困难.
- 现有的先进指标,如预期目标添加和后拍摄的预期目标,可以提高转化率,但忽视目标外拍.
- 非目标射击,占所有尝试的近三分之二,目前在所有开发的指标中都被赋予零值.
研究的目的:
- 提出新的足球射击技巧指标,这些指标包含了目标外射的数据.
- 开发一个特定于球员的射击轨迹生成模型,以量化在非目标尝试中的技能.
- 与现有最先进的方法相比,证明这些新指标的稳定性和预测能力的提高.
主要方法:
- 开发了一种特定于球员的足球投篮轨迹生成模型,使用了截断的双变高斯分布的混合物.
- 利用生成模型计算新的射击技巧指标,将非零值赋予非目标射击.
- 对当前最先进的指标进行稳定性和预测准确性的评估.
主要成果:
- 拟议的指标成功地结合了非目标射线轨迹中存在的技能信号.
- 与现有的先进足球分析指标相比,新的指标显示出更大的稳定性.
- 改进的指标在评估射击性能时显示出更强的预测能力.
结论:
- 目标外射线轨迹包含了评估足球射击技能的宝贵信息.
- 开发的生成模型和相关指标为测量射击性能提供了更全面的方法.
- 这些新型指标在足球分析中提供了对球员射击能力的更准确,更稳定的评估.
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