ArticleSports medicine - open2022
The Effects of Sex, Age and Performance Level on Pacing in Ultra-Marathon Runners in the 'Spartathlon'.
Article in Sports medicine - open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- TheFrontiers in physiology · 2026Pooled it
- Pacing profiles and slowdown patterns in ultra-triathlon performance.Scientific reports · 2026Article
- 24-Hour Ultra-Marathon Running: A Narrative Review of Performance Factors and Physiological Impacts.Sports medicine - open · 2026Review
- Impact of sodium alginate energy gel on the marathon performance of amateur runners: a randomized controlled study.Frontiers in physiology · 2026Article
- Pacing in ultra-marathon running: the Western States 100-mile endurance run 2006-2023.Scientific reports · 2025Article
- Article
- Article
- Running Variability in Marathon-Evaluation of the Pacing Variables.Medicina (Kaunas, Lithuania) · 2024Article
- Case Report: Differences in self-selected pacing in 20, 40, and 60 ironman-distance triathlons: a case study.Frontiers in sports and active living · 2024Article
- Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study.JMIR formative research · 2023Article
- Article
- The pacing differences in performance levels of marathon and half-marathon runners.Frontiers in psychology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPacing has been investigated in different kinds of ultra-marathon races, but not in one of the toughest ultra-marathons in the world, the 'Spartathlon'.
objectiveThe aim of the present study was to analyse the pacing of female and male finishers competing in the 'Spartathlon' in regards to their age and performance groups.
methodsA total of 2598 runners (2255 men and 343 women) finishing 'Spartathlon' between 2011 and 2019 were analysed. We selected 10 checkpoints with split times corresponding to important race sections. Average running speed was calculated for each participant and the average checkpoint running speed for each of the 10 race checkpoints. Furthermore, to assess the pacing strategy of each runner, the percentage of change in checkpoint speed (CCS) in relation to the average race speed was calculated (for each of 10 checkpoints). Finally, the average change in checkpoint speed (ACCS) was calculated for each participant as a mean of the 10 CCSs.
resultsBoth women and men slowed down through the first 7 checkpoints but increased running speed towards the end of the race (reverse J-shaped pacing). Men showed a significantly greater CCS in the first and second checkpoint (p < 0.01 and p < 0.05, respectively), whereas women showed a more significant change in CCS in the last checkpoint (p < 0.05). Furthermore, age and sex showed no effect on ACCS, whereas ACCS differed between the performance groups. In particular, the slowest and the fastest runners showed a more minor change in ACCS than the two medium groups of both men and women (p < 0.01).
conclusionsIn summary, successful finishers in 'Spartathlon' showed a reverse J-shaped pacing curve with a decrease in running speed from the start to the 7th checkpoint and an increase in running speed thereafter. This strategy was most probably due to the profile of the race course. Men showed a more significant change in checkpoint speed in the first two checkpoints, whereas women showed a more substantial change in the last checkpoint. Age and sex did not affect average checkpoint speed, whereas this speed was different between the different performance groups. The slowest and the fastest runners showed fewer changes in average checkpoint speed than the two medium groups in men and women.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.