Vickers Andrew J, Vertosick Emily A
Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017 USA.
BMC Sports Sci Med Rehabil. 2016 Aug 26;8(1):26. doi: 10.1186/s13102-016-0052-y. eCollection 2016.
Studies of endurance running have typically involved elite athletes, small sample sizes and measures that require special expertise or equipment.
We examined factors associated with race performance and explored methods for race time prediction using information routinely available to a recreational runner. An Internet survey was used to collect data from recreational endurance runners (N = 2303). The cohort was split 2:1 into a training set and validation set to create models to predict race time.
Sex, age, BMI and race training were associated with mean race velocity for all race distances. The difference in velocity between males and females decreased with increasing distance. Tempo runs were more strongly associated with velocity for shorter distances, while typical weekly training mileage and interval training had similar associations with velocity for all race distances. The commonly used Riegel formula for race time prediction was well-calibrated for races up to a half-marathon, but dramatically underestimated marathon time, giving times at least 10 min too fast for half of runners. We built two models to predict marathon time. The mean squared error for Riegel was 381 compared to 228 (model based on one prior race) and 208 (model based on two prior races).
Our findings can be used to inform race training and to provide more accurate race time predictions for better pacing.
耐力跑研究通常涉及精英运动员、小样本量以及需要特殊专业知识或设备的测量方法。
我们研究了与比赛成绩相关的因素,并利用普通跑步爱好者常规可获取的信息探索比赛时间预测方法。通过网络调查收集普通耐力跑者(N = 2303)的数据。将该队列按2:1比例分为训练集和验证集,以创建预测比赛时间的模型。
性别、年龄、体重指数和比赛训练与所有比赛距离的平均比赛速度相关。男女速度差异随距离增加而减小。短距离比赛中,节奏跑与速度的关联更强,而对于所有比赛距离,典型的每周训练里程和间歇训练与速度的关联相似。常用的比赛时间预测里格尔公式在半程马拉松及以内的比赛中校准良好,但显著低估了马拉松比赛时间,导致一半跑者的预测时间至少快10分钟。我们构建了两个预测马拉松比赛时间的模型。里格尔公式的均方误差为381,而基于一场之前比赛的模型为228,基于两场之前比赛的模型为208。
我们的研究结果可用于指导比赛训练,并为更好地控制配速提供更准确的比赛时间预测。