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title: Marathon Man II: how to pace a marathon | daily.dev
description: Using 2025 NYC Marathon split data, this analysis examines optimal pacing strategies for runners targeting a sub-3-hour finish. By focusing on runners...
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og:description: Using 2025 NYC Marathon split data, this analysis examines optimal pacing strategies for runners targeting a sub-3-hour finish. By focusing on runners...
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# Marathon Man II: how to pace a marathon

**[R-bloggers](https://daily.dev/sources/rbloggers)** · 14 min read · 0 upvotes · 0 comments

## Summary

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.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.r-bloggers.com/2026/04/marathon-man-ii-how-to-pace-a-marathon/>

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Tags: [#r](https://daily.dev/tags/r), [#data-analysis](https://daily.dev/tags/data-analysis), [#data-visualization](https://daily.dev/tags/data-visualization)

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