Martin D Hoffman1. 1. Dept of Physical Medicine & Rehabilitation, Dept of Veterans Affairs, Northern California Health Care System, and University of California Davis Medical Center, Sacramento, CA.
Abstract
PURPOSE: To examine pacing among the most successful runners in the 161-km Western States Endurance Run (WSER) to determine if variations in segmental speed relate to performance, ambient temperature, and calendar year. METHODS: Segmental speed and coefficient of variation (CV) in speed were analyzed for 10 race segments of 24 races from 1985 through 2013. RESULTS: Segmental speeds did not differ between the eventual winners and lead runners and only differed between the 1st and 2nd finishers in the 2nd half of the race. Mean CV in speed was lower (P < .01) for the winners (12%) than for the other top-5 finishers (14-15%). CV in speed was related (r = .80, P = .006) to finish time for the fastest 10 finish times at the WSER. Multiple linear-regression analysis revealed mean CV in speed for the top-5 runners to be related to maximum ambient temperature (coefficient =.14, P < .05) and calendar year (coefficient = -.086, P = .034). CONCLUSIONS: Mountain trail running is characterized by wide variations in speed, but the fastest times are achieved when speed fluctuations are limited. This is generally accomplished by the winners remaining relatively close behind the lead runners before taking the lead in the middle half of the race, and then avoiding slowing as much as the other top runners in the latter race stages. Variations in speed increase with high ambient temperatures, and the small decrease in segmental speed variability among top runners across the nearly 30 y of this study suggests that the best runners have improved at pacing this race.
PURPOSE: To examine pacing among the most successful runners in the 161-km Western States Endurance Run (WSER) to determine if variations in segmental speed relate to performance, ambient temperature, and calendar year. METHODS: Segmental speed and coefficient of variation (CV) in speed were analyzed for 10 race segments of 24 races from 1985 through 2013. RESULTS: Segmental speeds did not differ between the eventual winners and lead runners and only differed between the 1st and 2nd finishers in the 2nd half of the race. Mean CV in speed was lower (P < .01) for the winners (12%) than for the other top-5 finishers (14-15%). CV in speed was related (r = .80, P = .006) to finish time for the fastest 10 finish times at the WSER. Multiple linear-regression analysis revealed mean CV in speed for the top-5 runners to be related to maximum ambient temperature (coefficient =.14, P < .05) and calendar year (coefficient = -.086, P = .034). CONCLUSIONS: Mountain trail running is characterized by wide variations in speed, but the fastest times are achieved when speed fluctuations are limited. This is generally accomplished by the winners remaining relatively close behind the lead runners before taking the lead in the middle half of the race, and then avoiding slowing as much as the other top runners in the latter race stages. Variations in speed increase with high ambient temperatures, and the small decrease in segmental speed variability among top runners across the nearly 30 y of this study suggests that the best runners have improved at pacing this race.