How does the average marathoner pace their race? In this post, we’ll use R to have a look at a large dataset of marathon times to try to answer this question. The ideal strategy would be to “even split” the race. This is where you run continually at the same pace from kilometre 0 to […]

R-bloggers

Using R and a dataset of 56,480 runners from the 2025 NYC Marathon, this analysis examines how marathoners pace their races. The data shows most runners positive split (run the second half slower), with faster runners fading less. A linear regression constrained through an even-split anchor yields a fade coefficient of 1.24, meaning a 90-minute first half predicts a ~97-minute second half. A simpler mean-ratio approach gives a coefficient of 1.13. Practical pace targets are provided for finish times from 3:00 to 6:00 hours, showing runners should target a faster-than-even-split first half pace to account for inevitable fade. Full R code using ggplot2 is included.

Marathon Man: how to pace a marathon