使用预测XGBoost模型对50英里超级马拉松距离的分析
Jonas Turnwald1, David Valero2, Pedro Forte3
1Centre for Rehabilitation and Sports Medicine, University Hospital Bern, Inselspital Bern, University of Bern, Bern, Switzerland.
Scientific reports
|March 16, 2025
概括
比赛地点和运动员的性别显著影响50英里超级马拉松速度. 性能随着年龄的增长而下降,从40-44岁开始,在特定的国籍和比赛地点发现的速度更快.
科学领域:
- 运动科学 运动科学 运动科学
- 耐力运动研究 耐力运动研究
- 人类绩效分析 人类绩效分析
背景情况:
- 50英里超级马拉松很受欢迎,但研究不足.
- 影响超级马拉松比赛速度的因素需要科学研究.
研究的目的:
- 分析运动员人口统计 (年龄组,性别,国籍) 和比赛地点对50英里超级马拉松速度的影响.
- 使用机器学习开发一个用于赛车速度的预测模型.
主要方法:
- 利用了50英里超级马拉松比赛 (1863-2022) 的综合数据集.
- 开发并应用XGBoost机器学习模型用于速度预测.
- 采用模型可解释性工具来识别关键影响因素.
主要成果:
- 比赛地点和运动员的性别是比赛速度的最重要的预测因素.
- 最快的中位速度预测来自斯洛文尼亚,新西兰和保加利亚的运动员.
- 从40-44岁的年龄组开始,表现下降变得明显;男性预测的速度比女性更快.
结论:
- 确定了影响50英里超级马拉松表现的关键人口和地理因素.
- 调查结果为运动员,教练和比赛组织者提供了宝贵的见解.
- 为未来研究超级马拉松赛事动态和性能优化提供了基础.
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