陷阱:在越野跑性能评估的预测框架

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of Quantitative Analysis in Sports Pub Date : 2020-09-30 DOI:10.1515/JQAS-2020-0013
Riccardo Fogliato, N. L. Oliveira, Ronald Yurko
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引用次数: 0

摘要

越野跑是一项耐力运动,运动员面临着严峻的体能挑战。由于参加人数不断增加,在这些比赛中,有限的人员、设备和医疗支持的组织现在起着关键作用。监测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。在过去,选择完全基于组织者的经验,而不依赖于数据。然而,这种方法既不可扩展也不可转移。相反,我们提出了一种可靠的统计方法来完成这项任务,无论是在比赛前还是比赛中。我们提出的越野跑绩效评估(TRAP)框架研究(1)对跑者到达下一个检查点的能力的评估,(2)对跑者在下一个检查点预期通过时间的预测,以及(3)相应的通过时间预测区间。我们利用国际越野跑协会(ITRA)选手的比赛历史以及检查点和地形级别信息,将我们的方法应用于超级越野跑的“圣杯”,即勃朗峰越野跑(UTMB)比赛,展示了我们方法的预测能力。
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TRAP: a predictive framework for the Assessment of Performance in Trail Running
Abstract 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.
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来源期刊
Journal of Quantitative Analysis in Sports
Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
2.00
自引率
12.50%
发文量
15
期刊介绍: The Journal of Quantitative Analysis in Sports (JQAS), an official journal of the American Statistical Association, publishes timely, high-quality peer-reviewed research on the quantitative aspects of professional and amateur sports, including collegiate and Olympic competition. The scope of application reflects the increasing demand for novel methods to analyze and understand data in the growing field of sports analytics. Articles come from a wide variety of sports and diverse perspectives, and address topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and adjudication, within-game strategy, analysis of sporting technologies, and player and team ranking methods. JQAS seeks to publish manuscripts that demonstrate original ways of approaching problems, develop cutting edge methods, and apply innovative thinking to solve difficult challenges in sports contexts. JQAS brings together researchers from various disciplines, including statistics, operations research, machine learning, scientific computing, econometrics, and sports management.
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