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Natural experiments in marathon running

Daniel Muniz‐Pumares, Ed Maunder, Barry Smyth, Ben Hunter · Journal of Applied Physiology · 2026

This review explains how "natural experiments" \u2014 analysing huge real-world datasets of runners' training and race data rather than lab testing \u2014 have been used to study marathon physiology. It reports that such studies show marathons are run just below critical speed (with faster runners holding a higher fraction of it), and that heat, altitude, training program design, and pacing all affect marathon performance, largely agreeing with smaller lab studies while revealing subtler trends.
Takeaway: Pace your marathon just below your critical speed, and factor in heat, altitude, and pacing strategy when setting goal times.
Abstract (source)

Natural experiments are a form of passive experiments that analyse populations exposed to environmental or behavioural stimuli. Here, we review natural experiments using marathon running as an example of an unusual physiological stressor to illustrate how such approaches can generate new hypotheses or test competing ones using large datasets of training and performance data. Natural experiments have been able to demonstrate that marathons are completed close to, but below, critical speed, and that faster athletes complete marathons at a higher fraction of critical speed compared with slower runners. Environmental conditions, such as heat and altitude, as well as training and racing behaviours including the characteristics of training programmes and pacing strategies, have also been demonstrated to impact marathon performance.

Findings: from the natural experiments discussed herein often align with

Results: from smaller, laboratory-controlled studies. However, the scale of these datasets has allowed for the detection of subtle trends and interactions that otherwise would remain undetected in smaller cohorts. In

Conclusion: , natural experiments have helped advanced our understanding of marathon physiology and can effectively complement traditional laboratory-based interventions. Future research may explore hybrid approaches in which researchers conducting well-controlled laboratory experiments collaborate with running platforms to

Design: integrated research studies that combine large sample sizes with laboratory-controlled interventions.

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