ArticlePloS one2020
Different race pacing strategies among runners covering the 2017 Berlin Marathon under 3 hours and 30 minutes.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 10 citations in OpenAlex.
- Pacing Profiles in Half-Marathon and Marathon Running Based on Performance Level, Sex, and Age: A Narrative Review.Medicina (Kaunas, Lithuania) · 2026Review
- The New York City Marathon: A systematic review of performance, participation, pacing, and health-related outcomes.EXCLI journal · 2026Review
- Influence of Sex, Athletic Category and Athletic Level on Marathon Pacing Strategy: An Analysis of the Trinidad Alfonso EDP Valencia Marathon From 2014 to 2023.European journal of sport science · 2025Article
- Pacing in ultra-marathon running: the Western States 100-mile endurance run 2006-2023.Scientific reports · 2025Article
- Pacing strategies in marathons: A systematic review.Heliyon · 2024Article
- "Smells like team spirit" the association between running club membership and performance in the London Marathon: An economic analysis.PloS one · 2024Article
- Article
- Consistency of pacing profile according to performance level in three different editions of the Chicago, London, and Tokyo marathons.Scientific reports · 2022Article
- Oxygen Uptake Measurements and Rate of Perceived Exertion during a Marathon.International journal of environmental research and public health · 2022Article
- The Influence of Environmental Conditions on Pacing in Age Group Marathoners Competing in the "New York City Marathon".Frontiers in physiology · 2022Article
- Training and Racing Behavior of Recreational Runners by Race Distance-Results From the NURMI Study (Step 1).Frontiers in physiology · 2021Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purposes of this study were 1) to analyse the different pacing behaviours based on athlete's performance and 2) to determine whether significant differences in each race split and the runner's performance implied different race profiles. A total of 2295 runners, which took part in Berlin's marathon (2017), met the inclusion criteria. 4 different groups were created based on sex and performance. Men: Elite (<02:19:00 h), Top 1 (<02:30:00 h), Top 2 (<02:45:00 h) and Top 3 (<03:00:00 h); women: Elite (02:45:00 h), Top 1 (<03:00:00 h), Top 2 (<03:15:00 h), Top 3 (<03:30:00 h). With the aim of comparing the pacing between sex and performance the average speed was normalized. In men, no statistically significant changes were found between performance group and splits. A large number of significant differences between splits and groups were found amongst women: 5-10 km Top 2 vs Top 3 (P = 0.0178), 10-15 km Top1 vs Top 2 (P = 0.0211), 15-20 km Top1 vs Top 2 (P = 0.0382), 20-21.1 km Elite vs Top 2 (P = 0.0129); Elite vs Top 3 (P = 0.0020); Top1 vs Top 2 (P = 0.0233); Top 1 vs Top 3 (P = 0.0007), 25-30 km Elite vs Top 2 (P = 0.0273); Elite vs Top 3 (P = 0.0156), 30-35 km Elite vs Top 2 (P = 0.0096); Top 1 vs Top 2 (P = 0.0198); Top2 vs Top3 (P = 0.0069). In men there were little significant differences based on athletes' performance which implied a similar pacing behaviour. Women presented numerous differences based on their performance which suggested different pacing behaviours.
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Registered trials
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.