Analysis of quantile regression for race time in standard distance triathlons

标准距离铁人三项比赛成绩的分位数回归分析

阅读:1

Abstract

PURPOSE: This study aims to quantitatively analyze the impact of split times on overall performance in standard distance triathlon events. It also examines how environmental factors such as water type, temperature, and altitude affect overall race outcomes. METHODS: Quantile regression was employed to analyze the race records of 1,580 triathletes participating in 46 standard distance events in China. RESULTS: Swim time significantly influences race performance among the top 50% of elite athletes (p < 0.05). For slower elite athletes, bike time is more critical. Temperature has a positive effect on race times, while altitude also shows a significant positive impact, with race times decreasing as altitude increases (up to 1,600 meters in this study's dataset). River water enhances race times compared to still water, whereas sea water generally slows athletes down. CONCLUSION: The influence of split times and environmental factors on overall race rime varies according to the athletes' performance levels. To optimize results, training plans and race strategies should be tailored to each athlete's capabilities. Additionally, understanding and adapting to environmental conditions in advance is crucial.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。