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

Physiological variables such as maximal oxygen uptake (VO(2)max), velocity at maximal oxygen uptake (vVO(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 m...

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Autores principales: Alvero-Cruz, José Ramón, Carnero, Elvis A., García, Manuel Avelino Giráldez, Alacid, Fernando, Correas-Gómez, Lorena, Rosemann, Thomas, Nikolaidis, Pantelis T., Knechtle, Beat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665126/
https://www.ncbi.nlm.nih.gov/pubmed/33182485
http://dx.doi.org/10.3390/ijerph17218289
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author Alvero-Cruz, José Ramón
Carnero, Elvis A.
García, Manuel Avelino Giráldez
Alacid, Fernando
Correas-Gómez, Lorena
Rosemann, Thomas
Nikolaidis, Pantelis T.
Knechtle, Beat
author_facet Alvero-Cruz, José Ramón
Carnero, Elvis A.
García, Manuel Avelino Giráldez
Alacid, Fernando
Correas-Gómez, Lorena
Rosemann, Thomas
Nikolaidis, Pantelis T.
Knechtle, Beat
author_sort Alvero-Cruz, José Ramón
collection PubMed
description Physiological variables such as maximal oxygen uptake (VO(2)max), velocity at maximal oxygen uptake (vVO(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, vVO(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.
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spelling pubmed-76651262020-11-14 Predictive Performance Models in Long-Distance Runners: A Narrative Review Alvero-Cruz, José Ramón Carnero, Elvis A. García, Manuel Avelino Giráldez Alacid, Fernando Correas-Gómez, Lorena Rosemann, Thomas Nikolaidis, Pantelis T. Knechtle, Beat Int J Environ Res Public Health Review Physiological variables such as maximal oxygen uptake (VO(2)max), velocity at maximal oxygen uptake (vVO(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, vVO(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. MDPI 2020-11-09 2020-11 /pmc/articles/PMC7665126/ /pubmed/33182485 http://dx.doi.org/10.3390/ijerph17218289 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Alvero-Cruz, José Ramón
Carnero, Elvis A.
García, Manuel Avelino Giráldez
Alacid, Fernando
Correas-Gómez, Lorena
Rosemann, Thomas
Nikolaidis, Pantelis T.
Knechtle, Beat
Predictive Performance Models in Long-Distance Runners: A Narrative Review
title Predictive Performance Models in Long-Distance Runners: A Narrative Review
title_full Predictive Performance Models in Long-Distance Runners: A Narrative Review
title_fullStr Predictive Performance Models in Long-Distance Runners: A Narrative Review
title_full_unstemmed Predictive Performance Models in Long-Distance Runners: A Narrative Review
title_short Predictive Performance Models in Long-Distance Runners: A Narrative Review
title_sort predictive performance models in long-distance runners: a narrative review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665126/
https://www.ncbi.nlm.nih.gov/pubmed/33182485
http://dx.doi.org/10.3390/ijerph17218289
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