title: Predicting Marathon Time Using Exhaustive Graded Exercise Test in Marathon Runners.
abstract: The study aimed to investigate the correlation between time on a treadmill test and exhaustion 2 weeks before a road marathon and the subsequent road marathon performance time (MPT). The study recruited 59 runners entered in the Melbourne 2012 marathon, Canberra 2013 marathon, and Gold Coast 2013 marathon. Forty runners completed both the graded exercise treadmill test to exhaustion and the 42.2 km marathon. Nineteen participants dropped out of the study due to illness, injury, or did not begin the treadmill test. A statistically significant correlation was found between treadmill time and MPT (adjusted R(2) = 0.447). Sex, weekly running duration (t = -1.58, p = 0.12), years of running (t = 1.10, p = 0.28), and age (t = 0.94, p = 0.36) did not statistically correlate with MPT. The relationship between the graded exercise test and MPT can be used to predict MPT using y = -3.85x + 351.57, where y is MPT and x is treadmill time. This is a simple, accessible, and cost-effective method to aid athletes in predicting their race time over 42.2 km. Prediction of marathon time in a simple and accessible manner was believed to be useful to the growing population of marathon runners around the world.
authors.affiliation: 1MP Sports Physicians, Mornington, Australia;2Anglesea Sports Medicine, Hamilton, New Zealand; and3Department of Physiotherapy, Monash University, Melbourne, Australia.
authors.forename: Eloise S
authors.initials: ES
authors.lastname: Till
authors.forename: Stuart A
authors.initials: SA
authors.lastname: Armstrong
authors.forename: Greg
authors.initials: G
authors.lastname: Harris
authors.forename: Stephen
authors.initials: S
authors.lastname: Maloney
mesh_terms: D000328:Adult; D054874:Athletic Performance / Q000502:physiology / Q000706:statistics & numerical data*; D003163:Competitive Behavior; D005080:Exercise Test / Q000379:methods* / Q000706:statistics & numerical data; D005221:Fatigue / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012420:Running / Q000502:physiology / Q000706:statistics & numerical data*; D013997:Time Factors