Analysis of quantile regression for race time in standard distance triathlons

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.