Abstract
Purpose - Pacing strategies are key to overall performance outcome in distance running events. Presently, no literature has examined pacing strategies utilised by masters athletes, of all running levels, during a competitive marathon. Therefore, this study aimed to examine masters athletes’ pacing strategies, categorised by gender, age and performance level.
Methods - Data were retrieved from the 2015 TSC New York City Marathon for 31,762 masters athletes (20,019 men and 11,743 women). Seven performance classification (PC) groupings were identified via comparison of overall completion time compared to current world records, appropriate to age and gender. Data were categorised via, age, gender, and performance level. Mean 5 km speed for the initial 40 km was calculated and the fastest and slowest 5 km split speeds were identified and expressed as a percentage faster or slower than mean speed. Pace range, calculated as the absolute sum of the fastest and slowest split percentages, was then analysed.
Results - Significant main effects were identified for age, gender and performance level (p < 0.001); with performance level the most determining factor. Athletes in PC1 displayed the lowest pace range (14.19 ± 6.66%) and as the performance levels of athletes decreased, pace range increased linearly (PC2 – PC7, 17.52 ± 9.14% – 36.42 ± 18.32%). A significant interaction effect was found for gender×performance (p < 0.001), with women showing a smaller pace range (-3.81%).
Conclusions - High performing masters athletes utilise more controlled pacing strategies than their lower ranked counterparts, during a competitive marathon, independent of age and gender.
Methods - Data were retrieved from the 2015 TSC New York City Marathon for 31,762 masters athletes (20,019 men and 11,743 women). Seven performance classification (PC) groupings were identified via comparison of overall completion time compared to current world records, appropriate to age and gender. Data were categorised via, age, gender, and performance level. Mean 5 km speed for the initial 40 km was calculated and the fastest and slowest 5 km split speeds were identified and expressed as a percentage faster or slower than mean speed. Pace range, calculated as the absolute sum of the fastest and slowest split percentages, was then analysed.
Results - Significant main effects were identified for age, gender and performance level (p < 0.001); with performance level the most determining factor. Athletes in PC1 displayed the lowest pace range (14.19 ± 6.66%) and as the performance levels of athletes decreased, pace range increased linearly (PC2 – PC7, 17.52 ± 9.14% – 36.42 ± 18.32%). A significant interaction effect was found for gender×performance (p < 0.001), with women showing a smaller pace range (-3.81%).
Conclusions - High performing masters athletes utilise more controlled pacing strategies than their lower ranked counterparts, during a competitive marathon, independent of age and gender.
Original language | English |
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Number of pages | 25 |
Journal | International Journal of Sports Physiology and Performance |
Early online date | 17 Jul 2017 |
DOIs | |
Publication status | Early online - 17 Jul 2017 |
Keywords
- efficiency
- long distance running
- performance
- strategy