从视觉运动控制数据预测篮球投篮结果,使用可解释的机器学习
Nikki Aitcheson-Huehn1, Ryan MacPherson2, Derek Panchuk3
1Human Movement Science Curriculum, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Journal of sport & exercise psychology
|September 7, 2024
概括
安静的眼睛 (QE),在行动之前的视觉固定期,可以预测篮球表现. 训练以延长QE持续时间可能会提高射击精度.
科学领域:
- 运动科学 运动科学 运动科学
- 发动机控制器的控制器
- 人类表现的人类表现.
背景情况:
- 安静的眼睛 (QE) 是在关键行动之前对目标的视觉固定,与提高性能有关.
- 虽然QE是可训练的,但其对绩效结果的直接预测能力仍在调查中.
- 了解QE的预测能力对于开发有效的体育训练干预措施至关重要.
研究的目的:
- 使用视觉运动控制变量预测篮球投篮结果 (击中或错过).
- 调查不同QE参数和其他与射击相关的变量的预测准确度.
- 为了确定QE是否可以作为篮球中直接的绩效预测指标.
主要方法:
- 采用决策树分类方法来预测拍摄结果.
- 12名篮球运动员在球场的不同位置进行了200次投篮,同时戴着移动眼镜.
- 使用决策树和随机森林建模了八个预测因素,包括射击位置,手臂延伸时间和QE指标 (开始,偏移,持续时间).
主要成果:
- 决策树模型准确预测了超过66%的成功拍摄和超过50%的错过拍摄.
- 相对安静的眼睛持续时间成为射击成功的主要预测因素.
- 成功注射与相对QE持续时间超过18.4%有关.
结论:
- 安静的眼睛持续时间是篮球投篮成功的重要预测因素.
- 旨在延长QE持续时间超过18%的培训干预措施可以提高射击性能.
- 这些发现支持使用QE作为提高运动表现的可测量目标.
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