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瓦伦西亚马拉松的性能预测方程基于半程马拉松的时间和节奏

Fran Oficial-Casado¹, Jose Ignacio Priego-Quesada¹, Pedro Pérez-Soriano¹

¹Research Group in Sports Biomechanics (GIBD), Department of Physical Education and Sports, University of Valencia, Valencia, Spain.

Frontiers in physiology

|February 3, 2026

概括

预测马拉松表现通过分析半马拉松时间和跑者人口统计学来提高. 节奏范围并没有显著改善预测准确性,这与VDOT系统相当.

科学领域:

运动科学运动科学运动科学
运行性能分析的运行.

背景情况:

马拉松跑的表现受到节奏策略的影响.
现有的马拉松时间预测模型缺乏对节奏变量的全面分析.

研究的目的:

利用半程马拉松数据开发一个线性回归模型来预测马拉松比赛时间.
评估节奏范围 (半程马拉松期间速度的变化) 对预测准确性的影响.
为了将开发的模型的准确性与已建立的丹尼尔斯VDOT系统进行比较.

主要方法:

利用了从8261名参加瓦伦西亚半程马拉松和马拉松的2022年和2023年的跑步者的数据.
开发了三种线性回归模型,逐渐添加变量:半程马拉松时间,性别,年龄类别和节奏范围.
使用解释差异和平均绝对误差评估模型准确性,将最佳模型与VDOT系统进行比较.

主要成果:

最终的线性回归模型,包括半程马拉松时间,性别和年龄类别,实现了85%的解释差异和5.9%的平均绝对误差.
整合节奏范围变量并没有显著提高预测模型的准确性.
开发的模型显示了与VDOT系统相似的整体准确性,尽管性能在不同的跑者能力水平上有所不同.

结论:

半程马拉松时间,性别和年龄类别是马拉松表现的关键预测因素.
节奏范围不是提高马拉松时间预测准确性的重要因素.
这些发现为教练和跑步者提供了宝贵的见解,以优化基于性能预测的训练和比赛策略.

关键词:

瓦伦西亚跑步城市跑步城市耐久性耐久性耐久性赛车时间赛车时间跑步跑步跑步跑步跑步跑步培训培训培训培训培训培训培训

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