Predictive Performance Models in Long-Distance Runners: A Narrative Review

José Ramón Alvero-Cruz, Elvis A. Carnero, Manuel Avelino Giráldez García, Fernando Alacid, Lorena Correas-Gómez, Thomas Rosemann, Pantelis T. Nikolaidis and Beat Knechtle
Additional contact information
José Ramón Alvero-Cruz: Faculty of Medicine, University of Málaga, Andalucía TECH, 29071 Málaga, Spain
Elvis A. Carnero: AdventHealth Translational Research Institute, AdventHealth Oralndo, Orlando, FL 32804, USA
Manuel Avelino Giráldez García: Faculty of Sports Science and Physical Education, University of A Coruña, 15179 Oleiros, Spain
Fernando Alacid: Department of Education, Health Research Centre, University of Almería, 04120 Almería, Spain
Lorena Correas-Gómez: Faculty of Education Sciences, University of Málaga, Andalucía TECH, 29071 Málaga, Spain
Thomas Rosemann: Institute of Primary Care, University of Zurich, 8006 Zurich, Switzerland
Pantelis T. Nikolaidis: School of Health and Caring Sciences, University of West Attica, 12243 Athens, Greece
Beat Knechtle: Institute of Primary Care, University of Zurich, 8006 Zurich, Switzerland

IJERPH, 2020, vol. 17, issue 21, 1-23

Abstract: Physiological variables such as maximal oxygen uptake (VO 2 max), velocity at maximal oxygen uptake ( v VO 2 max), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VO 2 max, v VO 2 max), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.

Keywords: prediction equations; performance; long-distance runners (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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