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J Sports Sci Med. 2017 Jun 1;16(2):187-194. eCollection 2017 Jun.

Predictive Variables of Half-Marathon Performance for Male Runners.

Author information

1
Faculty of Education and Sport, University of the Basque Country, UPV/EHU, Spain.
2
Department of Physical Education and Sports, Institute of Biomedicine (IBIOMED), Faculty of Physical Activity and Sports Sciences (FCAFD) University of León. Spain.
3
Department of Kinesiology and Rehabilitation Science, College of Education, University of Hawaii at Manoa, Honolulu, USA.
4
High Sport Performance Centre of León (CAR-León), Spanish Council of Sports.

Abstract

The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. 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 (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

KEYWORDS:

Running; anthropometry; biomechanics; endurance; physiology; training

PMID:
28630571
PMCID:
PMC5465980

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