Assessing course difficulty and the effect of weather in amateur cross country running races
Kevin J Wilson, Nina Wilson

TL;DR
This study models finish times in cross country races to assess course difficulty and weather effects, revealing significant impacts of rainfall and course variability, but not windspeed, using Bayesian mixed effects models.
Contribution
It introduces a Bayesian mixed effects modeling approach to quantify course difficulty and weather impacts on cross country race times.
Findings
Rainfall increases finish times in the race month and the previous month.
Course difficulty varies significantly across different courses.
Windspeed does not significantly affect finish times.
Abstract
Cross country running races are different to track and road races in that the courses are not typically accurately measured and the condition of the course can have a strong effect on the finish times of the participants. In this paper we investigate these effects by modelling the finish times of all participants in 28 cross country running races over 5 seasons in the North East of England. We model the natural logarithm of the finish times using linear mixed effects models for both the senior men's and senior women's races. We investigate the effects of weather and underfoot conditions using windspeed and rainfall as covariates, fit distance as a covariate, and investigate the effect of time via the season of the race, in particular investigating any evidence of a pre- to post-Covid effect. We use random athlete effects to model the participant to participant variability and identify…
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Taxonomy
TopicsSports Performance and Training · Winter Sports Injuries and Performance · High Altitude and Hypoxia
