It’s often the way. I posted recently about how to pace a marathon and very quickly received feedback that would’ve improved the original post. Oh well, no going back. This is take two. So, we have a dataset of all runners from the 2025 New York City Marathon. We want to know how should you […]

R-bloggers

Using 2025 NYC Marathon split data, this analysis examines optimal pacing strategies for runners targeting a sub-3-hour finish. By focusing on runners finishing between 2:55 and 3:05, the author infers runner intent and compares outcomes. Key finding: most successful sub-3 runners go out slightly ahead of goal pace (more than 2 s/km faster) rather than negative splitting. Probability curves show that being ahead of pace at 5 km gives a 65% success rate, while being behind at 10 km drops it to 19%. The R code using ggplot2 and dplyr is provided in full.

Marathon Man II: how to pace a marathon