Study May Predict Runner’s Half-Marathon Performance

males running in a race

A Review by Alyssa Bialowas

Participating in marathons and half-marathons has become a very popular means of exercise for elite and recreational runners alike. Level aside, endurance athletes search for predictive training equations for optimal performance. The aim of this study were to validate four predictive equations for half-marathon performance involving anthropometric, training, biomechanics and physiological variables.

The Study

Seventy-eight male half-marathon runners from two different cities participated in two different phases of this study. Phase 1 was used to establish equations for predicting running performance, and Phase 2 was used as a test phase to validate these equations. Participants in Phase 1 were required to have completed a half-marathon in less than 105 minutes in the 6 weeks of the study, and participants in Phase 2 were to complete a half-marathon in the four weeks following testing. 48 male runners participated in Phase 1, 30 in Phase 2.

Participants had their anthropometrical characteristics recorded, and both groups underwent the same testing. Participants performed an incremental test on a treadmill, in which VO2max, speed at aerobic threshold, and peak speed were recorded. Biomechanical variables, such as contact and flight times, step length and step rate were registered.

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The Results

In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance. The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners.


Training and anthropometrical variables as well as physiological variables such as years of experience, peak and RCT speeds, improved the power of prediction compared to previous research. Maximal step length and step rate were studied as variables that were related to half-marathon performance in runners. These variables can be used to predict performance prior to competition.

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Camara, J., Garcia-Lopez, J., Gomez-Molina, J., Ogueta-Alday, A., Rodriguez-Marrayo,

J., & Stickley, C. (2017). “Predictive Variables of Half-Marathon Performance

for Male Runners.” Journal of Sports Science and Medicine, 16, 187-194.

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