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A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league

This study investigated differences in external training load between microcycle lengths and its variation between microcycles, players, and head coaches. Commonly used external training load variables including total-, high-speed- (5–7 m∙s(-1)), and sprint-distance (> 7 m∙s(-1)) alongside combin...

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Autores principales: Parmley, James, Jones, Ben, Sawczuk, Tom, Weaving, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803197/
https://www.ncbi.nlm.nih.gov/pubmed/35100267
http://dx.doi.org/10.1371/journal.pone.0263093
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author Parmley, James
Jones, Ben
Sawczuk, Tom
Weaving, Dan
author_facet Parmley, James
Jones, Ben
Sawczuk, Tom
Weaving, Dan
author_sort Parmley, James
collection PubMed
description This study investigated differences in external training load between microcycle lengths and its variation between microcycles, players, and head coaches. Commonly used external training load variables including total-, high-speed- (5–7 m∙s(-1)), and sprint-distance (> 7 m∙s(-1)) alongside combined high acceleration and deceleration distance (> 2 m∙s(-2)). Which were also expressed relative to time were collected using microtechnology within a repeated measures design from 54 male rugby league players from one Super League team over four seasons. 4337 individual observations across ninety-one separate microcycles and six individual microcycle lengths (5 to 10 day) were included. Linear mixed effects models established the differences in training load between microcycle-length and the variation between-microcycles, players and head coaches. The largest magnitude of difference in training load was seen when comparing 5-day with 9-day (ES = 0.31 to 0.53) and 10-day (ES = 0.19 to 0.66) microcycles. The greatest number of differences between microcycles were observed in high- (ES = 0.3 to 0.53) and sprint-speed (ES = 0.2 to 0.42) variables. Between-microcycle variability ranged between 11% to 35% dependent on training load variable. Training load also varied between players (5–65%) and head coaches (6–20%) with most variability existing within high-speed (19–43%) and sprinting (19–65%). Overall, differences in training load between microcycle lengths exist, likely due to manipulation of session duration. Furthermore, training load varies between microcycle, player and head coach.
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spelling pubmed-88031972022-02-01 A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league Parmley, James Jones, Ben Sawczuk, Tom Weaving, Dan PLoS One Research Article This study investigated differences in external training load between microcycle lengths and its variation between microcycles, players, and head coaches. Commonly used external training load variables including total-, high-speed- (5–7 m∙s(-1)), and sprint-distance (> 7 m∙s(-1)) alongside combined high acceleration and deceleration distance (> 2 m∙s(-2)). Which were also expressed relative to time were collected using microtechnology within a repeated measures design from 54 male rugby league players from one Super League team over four seasons. 4337 individual observations across ninety-one separate microcycles and six individual microcycle lengths (5 to 10 day) were included. Linear mixed effects models established the differences in training load between microcycle-length and the variation between-microcycles, players and head coaches. The largest magnitude of difference in training load was seen when comparing 5-day with 9-day (ES = 0.31 to 0.53) and 10-day (ES = 0.19 to 0.66) microcycles. The greatest number of differences between microcycles were observed in high- (ES = 0.3 to 0.53) and sprint-speed (ES = 0.2 to 0.42) variables. Between-microcycle variability ranged between 11% to 35% dependent on training load variable. Training load also varied between players (5–65%) and head coaches (6–20%) with most variability existing within high-speed (19–43%) and sprinting (19–65%). Overall, differences in training load between microcycle lengths exist, likely due to manipulation of session duration. Furthermore, training load varies between microcycle, player and head coach. Public Library of Science 2022-01-31 /pmc/articles/PMC8803197/ /pubmed/35100267 http://dx.doi.org/10.1371/journal.pone.0263093 Text en © 2022 Parmley et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Parmley, James
Jones, Ben
Sawczuk, Tom
Weaving, Dan
A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
title A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
title_full A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
title_fullStr A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
title_full_unstemmed A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
title_short A four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
title_sort four-season study quantifying the weekly external training loads during different between match microcycle lengths in professional rugby league
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803197/
https://www.ncbi.nlm.nih.gov/pubmed/35100267
http://dx.doi.org/10.1371/journal.pone.0263093
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