Pacing patterns of female runners in the Comrades marathon “down run”: a retrospective descriptive research design

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2026

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University of Cape Town

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Appropriate pacing is considered optimal for successful endurance performance (Casado et al., 2021a). The Comrades Marathon has been subject to multiple studies (Boulter et al., 2011, Coetzee et al., 2022, Hagemann et al., 2008, Nikolaidis and Knechtle, 2019, Woyo and Nyamandi, 2022); however, there are currently no published studies on the pacing patterns used by runners in the Comrades Marathon. Aims: This study aimed to determine the pacing patterns of the fastest through to the slowest female runners in the Comrades Marathon “down” run, between the years 2016 and 2023. This will be conducted by analysing the pacing patterns to determine if the pacing patterns differ between runners of different abilities, and to determine how their pace changes between different sections of the race. Methods: Results of all the female finishers of the Comrades Marathon who fulfilled the inclusion and exclusion criteria were combined into a single spreadsheet. The data was separated into four groups, based on time, from fastest to slowest. Race pace was analysed using a Generalised Linear Mixed Effects Model (GLMM) to determine any statistically significant differences. Pairwise comparisons and post-hoc tests utilizing the Bonferroni method were then used to determine which average paces demonstrated statistically significant differences (p<0.05). Results: 7818 results were analysed. The mean race time for all female participants was 10:40:57 (hh:mm:ss). The faster runners (group A) showed the least variable pacing pattern, while the slowest runners (group D) showed the most variable pacing pattern. The pacing pattern used was variable, with runners showing decreased pace in segments 4 and 6 from the mean race pace. Conclusion: The pacing patterns differ between runners of different abilities. The greatest differences of average pace were seen in the first 30km, where the slower runners ran at significantly higher percentages of their average race pace. It is evident that the course profile significantly affected the pacing selected by the participants. All athletes had significant speed reductions in segments 4 and 6.
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