Trail running is an endurance sport in which athletes face severe physical challenges. Due to the growing number of participants, the organization of limited staff, equipment, and medical support in these races now plays a key role. Monitoring runner’s performance is a difficult task that requires knowledge of the terrain and of the runner’s ability. In the past, choices were solely based on the organizers’ experience without reliance on data. However, this approach is neither scalable nor transferable. Instead, we propose a firm statistical methodology to perform this task, both before and during the race. Our proposed framework, Trail Running Assessment of Performance (TRAP), studies (1) the assessment of the runner’s ability to reach the next checkpoint, (2) the prediction of the runner’s expected passage time at the next checkpoint, and (3) corresponding prediction intervals for the passage time. We apply our methodology, using the race history of runners from the International Trail Running Association (ITRA) along with checkpoint and terrain-level information, to the “holy grail” of ultra-trail running, the Ultra-Trail du Mont-Blanc (UTMB) race, demonstrating the predictive power of our methodology.

中文翻译：

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TRAP：越野跑性能评估的预测框架

越野跑是一项耐力运动，运动员要面对严峻的身体挑战。由于参赛人数的不断增加，在这些比赛中组织有限的人员，设备和医疗支持现在发挥着关键作用。监视跑步者的表现是一项艰巨的任务，需要了解地形和跑步者的能力。过去，选择仅基于组织者的经验，而不依赖数据。但是，这种方法既不可扩展，也不可转让。相反，我们提出了一种可靠的统计方法来在比赛之前和比赛期间执行此任务。我们提出的框架，即越野跑性能评估（TRAP），用于研究（1）跑步者到达下一个检查点的能力的评估，（2）跑步者在下一个检查点的预期通过时间的预测，（3）通过时间的相应预测间隔。我们将来自国际越野跑协会（ITRA）的跑步者的比赛历史以及检查站和地形级别的信息应用于超级越野跑的“圣杯”，即超勃朗峰（Ultra-Trail du Mont-Blanc）。 UTMB）竞赛，证明了我们方法论的预测能力。