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Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer

This study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive...

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Autores principales: Rago, Vincenzo, Brito, João, Figueiredo, Pedro, Krustrup, Peter, Rebelo, António
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126260/
https://www.ncbi.nlm.nih.gov/pubmed/32269668
http://dx.doi.org/10.2478/hukin-2019-0113
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author Rago, Vincenzo
Brito, João
Figueiredo, Pedro
Krustrup, Peter
Rebelo, António
author_facet Rago, Vincenzo
Brito, João
Figueiredo, Pedro
Krustrup, Peter
Rebelo, António
author_sort Rago, Vincenzo
collection PubMed
description This study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4–19.8, 19.8–25.1 and ≥25.2 km·h-1, and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80–100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably.
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spelling pubmed-71262602020-04-08 Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer Rago, Vincenzo Brito, João Figueiredo, Pedro Krustrup, Peter Rebelo, António J Hum Kinet Section III – Sports Training This study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4–19.8, 19.8–25.1 and ≥25.2 km·h-1, and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80–100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably. Sciendo 2020-03-31 /pmc/articles/PMC7126260/ /pubmed/32269668 http://dx.doi.org/10.2478/hukin-2019-0113 Text en © 2020 Vincenzo Rago, João Brito, Pedro Figueiredo, Peter Krustrup, António Rebelo, published by Sciendo http://creativecommons.org/licenses/by-nc-nd/3.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Section III – Sports Training
Rago, Vincenzo
Brito, João
Figueiredo, Pedro
Krustrup, Peter
Rebelo, António
Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer
title Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer
title_full Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer
title_fullStr Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer
title_full_unstemmed Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer
title_short Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer
title_sort application of individualized speed zones to quantify external training load in professional soccer
topic Section III – Sports Training
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126260/
https://www.ncbi.nlm.nih.gov/pubmed/32269668
http://dx.doi.org/10.2478/hukin-2019-0113
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