Pacing profiles of male runners in the Comrades ultra-marathon "down" run

Wilson, Leanne

Pacing profiles of male runners in the Comrades ultra-marathon "down" run

Thesis / Dissertation

2026

Publisher

University of Cape Town

Department

Department of Health and Rehabilitation Sciences

Faculty

Faculty of Health Sciences

Abstract

Background: Running has gained in popularity both globally and in South Africa. In South Africa, the Comrades ultra-marathon attracts thousands of runners every year and is one of the largest ultra-marathons in the world. To date, no literature has been published on the pacing profiles of male runners in the Comrades marathon “down” run. Pacing is a dynamic, comprehensive physiological and psychological response to race circumstances. It is influenced by multiple intrinsic and extrinsic factors, which vary by individual and race. Understanding the pacing profiles of male runners in the Comrades ultra-marathon “down” run will provide insight into any differences that may exist between faster and slower finishers. The findings will offer data to optimise pacing for runners of all abilities competing in this world-renowned event, potentially improving finishing times. Aim and Objectives: This study aimed to establish the different pacing profiles of male runners (from fastest to slowest) who have completed the last four Comrades ultra-marathon “down” runs from 2016 to 2023 and compare the pacing profiles of participants of different abilities. The objectives were: a) to identify the differences in pacing profiles between faster and slower male runners, specifically describing the pacing patterns in each quartile (based on finishing time) of runners completing the race; b) to determine if there are changes in pace throughout different segments of the race in faster and slower male runners respectively, relative to mean race pace (MRP), expressed as a percentage; c) to determine if there is a difference in pace in km/h within each quartile when comparing segment pace relative to the first segment. It was hypothesized that a) faster runners would finish the race with less variation in speed, b) all runners would produce an end spurt, and c) a reverse J-shaped pacing profile would be demonstrated by all runners. Methods: This was a descriptive retrospective study. Race time data of the “down” run between 2016 and 2023 was collected from the Comrades ultra-marathon online database and entered into Excel spreadsheets. After ranking from fastest to slowest, 27, 817 finishers over the period studied were divided into quartiles based on finishing time. Overall, the seven segments, with split times recorded for all finishers on the approximately 90km route, were analysed. The split times of the finishers at each segment of each respective year were used to calculate MRP and mean running speed for each segment. In addition, speed for each segment and overall race speed were normalized to speed in the first segment as well as to overall race speed. All segments of each quartile were compared to assess pacing patterns. Results: As the race progressed, there was a trend of decreasing pace, indicating a natural slowdown in all runners. However, the fastest runners (Q1) paced themselves with less change in pace throughout the race. The extent of pace reduction varied by quartile. When comparing segment pace between quartiles, relative to segment one (S1) pace (expressed as a percentage), there was a general slowing down in race pace. All quartiles had the slowest pace at segment seven (S7), relative to S1. The faster runners (Q1) were the only group to run S1 to segment two (S2) at a lower percentage of starting race pace than S1. Q1 runners decreased pace from S1 (100%) to S2 (99.18%). Runners in quartiles two, three, and four all sped up initially, as there was an increase in running pace percentage at S2 (>100%). Q4 runners sped up the most of all groups to 105.94%. Overall, the results demonstrate a positive pacing profile in all four groups, and no end spurt was observed. Conclusion: Despite the significant differences in pace between the fastest to slowest runners, there was a general slowing down as the race progressed. Q1 runners maintained a significantly faster pace compared to the other runners and paced themselves more efficiently with less pace change. The extent of pace reduction varied between quartiles. These findings demonstrate that there was a general slowing down of speed as the race progressed, with less experienced runners pacing less consistently. The pacing patterns were similar for most of the race distance between the fastest through to the slowest runners, just the absolute speed varied. Implications: Ultra-marathon runners should adopt a consistent running pace, regardless of performance level, as this could enhance their performance. Runners should have a well-thought-out pacing plan. This should include preventing rapid increases in speed, as this may aid in conserving energy, preventing early onset of fatigue, and optimising their race times.

Keywords

Pacing, Comrades, ultra-marathon

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