![]() ![]() Among the different race distances, the 100 km ultra-marathon distance is highly popular where the number of female and male finishes increased exponentially in the last 50 years. Ultra-marathon running involves any race distance longer than the classical marathon distance of 42.195 km. To summarize, ( i) athletes in age group 18–24 years were slower than athletes in most other age groups and ( ii) there was no trend of slowing down for older athletes. Regression analysis showed no trend across age groups (r 2 = 0.003, p > 0.05). The trend across age groups was investigated using simple regression analysis with age as the dependent variable. The ratios between elite and age group runners were investigated using one-way ANOVA with Dunnett’s multiple comparison post-hoc tests. The ratios between the age cohorts were compared using one-way ANOVA and Tukey’s post-hoc test. ![]() which may have impacted the final relative to the first segment across years. These ratios were combined across years with the assumption that there were no ‘extreme’ wind events etc. For each year, the ratio of the running speed from the final to the first segment for each age cohort was determined. relative to segment 1 of the race corrected for gradient) was analysed as a proxy for pacing in elite and age group finishers. elite and age group runners) competing between 20 in the ‘100 km Lauf Biel’ were identified. This study investigated changes in normalised running speed as a proxy for effort distribution over segments in male elite and age group 100 km ultra-marathoners with the assumption that older runners would slow down more than younger runners.
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