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Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach

Applying data-reduction techniques to extract meaningful information from electronic performance and tracking systems (EPTS) has become a hot topic in football training load (TL) monitoring. The aim of this study was to reduce the dimensionality of the internal and external load measures, by a princ...

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Autores principales: Teixeira, José Eduardo, Forte, Pedro, Ferraz, Ricardo, Branquinho, Luís, Morgans, Ryland, Silva, António José, Monteiro, António Miguel, Barbosa, Tiago M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405799/
https://www.ncbi.nlm.nih.gov/pubmed/37554335
http://dx.doi.org/10.7717/peerj.15806
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author Teixeira, José Eduardo
Forte, Pedro
Ferraz, Ricardo
Branquinho, Luís
Morgans, Ryland
Silva, António José
Monteiro, António Miguel
Barbosa, Tiago M.
author_facet Teixeira, José Eduardo
Forte, Pedro
Ferraz, Ricardo
Branquinho, Luís
Morgans, Ryland
Silva, António José
Monteiro, António Miguel
Barbosa, Tiago M.
author_sort Teixeira, José Eduardo
collection PubMed
description Applying data-reduction techniques to extract meaningful information from electronic performance and tracking systems (EPTS) has become a hot topic in football training load (TL) monitoring. The aim of this study was to reduce the dimensionality of the internal and external load measures, by a principal component approach, to describe and explain the resultant equations for TL monitoring during a standard in-season microcycle in sub-elite youth football. Additionally, it is intended to identify the most representative measure for each principal component. A principal component analysis (PCA) was conducted with a Monte Carlo parallel analysis and VariMax rotation to extract baseline characteristics, external TL, heart rate (HR)-based measures and perceived exertion. Training data were collected from sixty sub-elite young football players during a 6-week training period using 18 Hz global positioning system (GPS) with inertial sensors, 1 Hz short-range telemetry system, total quality recovery (TQR) and rating of perceived exertion (RPE). Five principal components accounted for 68.7% of the total variance explained in the training data. Resultant equations from PCA was subdivided into: (1) explosiveness, accelerations and impacts (27.4%); (2) high-speed running (16.2%); (3) HR-based measures (10.0%); (4) baseline characteristics (8.3%); and (5) average running velocity (6.7%). Considering the highest factor in each principal component, decelerations (PCA 1), sprint distance (PCA 2), average HR (PCA 3), chronological age (PCA 4) and maximal speed (PCA 5) are the conditional dimension to be considered in TL monitoring during a standard microcycle in sub-elite youth football players. Current research provides the first composite equations to extract the most representative components during a standard in-season microcycle in sub-elite youth football players. Futures research should expand the resultant equations within training days, by considering other well-being measures, technical-tactical skills and match-related contextual factors.
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spelling pubmed-104057992023-08-08 Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach Teixeira, José Eduardo Forte, Pedro Ferraz, Ricardo Branquinho, Luís Morgans, Ryland Silva, António José Monteiro, António Miguel Barbosa, Tiago M. PeerJ Kinesiology Applying data-reduction techniques to extract meaningful information from electronic performance and tracking systems (EPTS) has become a hot topic in football training load (TL) monitoring. The aim of this study was to reduce the dimensionality of the internal and external load measures, by a principal component approach, to describe and explain the resultant equations for TL monitoring during a standard in-season microcycle in sub-elite youth football. Additionally, it is intended to identify the most representative measure for each principal component. A principal component analysis (PCA) was conducted with a Monte Carlo parallel analysis and VariMax rotation to extract baseline characteristics, external TL, heart rate (HR)-based measures and perceived exertion. Training data were collected from sixty sub-elite young football players during a 6-week training period using 18 Hz global positioning system (GPS) with inertial sensors, 1 Hz short-range telemetry system, total quality recovery (TQR) and rating of perceived exertion (RPE). Five principal components accounted for 68.7% of the total variance explained in the training data. Resultant equations from PCA was subdivided into: (1) explosiveness, accelerations and impacts (27.4%); (2) high-speed running (16.2%); (3) HR-based measures (10.0%); (4) baseline characteristics (8.3%); and (5) average running velocity (6.7%). Considering the highest factor in each principal component, decelerations (PCA 1), sprint distance (PCA 2), average HR (PCA 3), chronological age (PCA 4) and maximal speed (PCA 5) are the conditional dimension to be considered in TL monitoring during a standard microcycle in sub-elite youth football players. Current research provides the first composite equations to extract the most representative components during a standard in-season microcycle in sub-elite youth football players. Futures research should expand the resultant equations within training days, by considering other well-being measures, technical-tactical skills and match-related contextual factors. PeerJ Inc. 2023-08-04 /pmc/articles/PMC10405799/ /pubmed/37554335 http://dx.doi.org/10.7717/peerj.15806 Text en © 2023 Teixeira 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, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Kinesiology
Teixeira, José Eduardo
Forte, Pedro
Ferraz, Ricardo
Branquinho, Luís
Morgans, Ryland
Silva, António José
Monteiro, António Miguel
Barbosa, Tiago M.
Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
title Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
title_full Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
title_fullStr Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
title_full_unstemmed Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
title_short Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
title_sort resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach
topic Kinesiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405799/
https://www.ncbi.nlm.nih.gov/pubmed/37554335
http://dx.doi.org/10.7717/peerj.15806
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