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Women's Rugby League: Positional Groups and Peak Locomotor Demands
The aims of this study were to (a) use a data-based approach to identify positional groups within National Rugby League Women's (NRLW) match-play and (b) quantify the peak locomotor demands of NRLW match-play by positional groups. Microtechnology (Global Navigational Satellite System [GNSS] and...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276862/ https://www.ncbi.nlm.nih.gov/pubmed/34268492 http://dx.doi.org/10.3389/fspor.2021.648126 |
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author | Cummins, Cloe Charlton, Glen Paul, David Shorter, Kath Buxton, Simon Caia, Johnpaul Murphy, Aron |
author_facet | Cummins, Cloe Charlton, Glen Paul, David Shorter, Kath Buxton, Simon Caia, Johnpaul Murphy, Aron |
author_sort | Cummins, Cloe |
collection | PubMed |
description | The aims of this study were to (a) use a data-based approach to identify positional groups within National Rugby League Women's (NRLW) match-play and (b) quantify the peak locomotor demands of NRLW match-play by positional groups. Microtechnology (Global Navigational Satellite System [GNSS] and integrated inertial sensors; n = 142 files; n = 76 players) and match statistics (n = 238 files; n = 80 players) were collected from all NRLW teams across the 2019 season. Data-based clustering of match statistics was utilized to identify positional clusters through classifying individual playing positions into distinct positional groups. Moving averages (0.5, 1, 2, 3, 5, and 10 min) of peak running and average acceleration/deceleration demands were calculated via microtechnology data for each player per match. All analysis was undertaken in R (R Foundation for Statistical Computing) with positional differences determined via a linear mixed model and effect sizes (ES). Data-based clustering suggested that, when informed by match statistics, individual playing positions can be clustered into one of three positional groups. Based on the clustering of the individual positions, these groups could be broadly defined as backs (fullback, wing, and center), adjustables (halfback, five-eighth, and hooker), and forwards (prop, second-row, and lock). Backs and adjustables demonstrated greater running (backs: ES 0.51–1.00; p < 0.05; adjustables: ES 0.51–0.74, p < 0.05) and average acceleration/deceleration (backs: ES 0.48–0.87; p < 0.05; adjustables: ES 0.60–0.85, p < 0.05) demands than forwards across all durations. Smaller differences (small to trivial) were noted between backs and adjustables across peak running and average acceleration/deceleration demands. Such findings suggest an emerging need to delineate training programs in situations in which individual playing positions train in positional group based settings. Collectively, this work informs the positional groupings that could be applied when examining NRLW data and supports the development of a framework for specifically training female rugby league players for the demands of the NRLW competition. |
format | Online Article Text |
id | pubmed-8276862 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82768622021-07-14 Women's Rugby League: Positional Groups and Peak Locomotor Demands Cummins, Cloe Charlton, Glen Paul, David Shorter, Kath Buxton, Simon Caia, Johnpaul Murphy, Aron Front Sports Act Living Sports and Active Living The aims of this study were to (a) use a data-based approach to identify positional groups within National Rugby League Women's (NRLW) match-play and (b) quantify the peak locomotor demands of NRLW match-play by positional groups. Microtechnology (Global Navigational Satellite System [GNSS] and integrated inertial sensors; n = 142 files; n = 76 players) and match statistics (n = 238 files; n = 80 players) were collected from all NRLW teams across the 2019 season. Data-based clustering of match statistics was utilized to identify positional clusters through classifying individual playing positions into distinct positional groups. Moving averages (0.5, 1, 2, 3, 5, and 10 min) of peak running and average acceleration/deceleration demands were calculated via microtechnology data for each player per match. All analysis was undertaken in R (R Foundation for Statistical Computing) with positional differences determined via a linear mixed model and effect sizes (ES). Data-based clustering suggested that, when informed by match statistics, individual playing positions can be clustered into one of three positional groups. Based on the clustering of the individual positions, these groups could be broadly defined as backs (fullback, wing, and center), adjustables (halfback, five-eighth, and hooker), and forwards (prop, second-row, and lock). Backs and adjustables demonstrated greater running (backs: ES 0.51–1.00; p < 0.05; adjustables: ES 0.51–0.74, p < 0.05) and average acceleration/deceleration (backs: ES 0.48–0.87; p < 0.05; adjustables: ES 0.60–0.85, p < 0.05) demands than forwards across all durations. Smaller differences (small to trivial) were noted between backs and adjustables across peak running and average acceleration/deceleration demands. Such findings suggest an emerging need to delineate training programs in situations in which individual playing positions train in positional group based settings. Collectively, this work informs the positional groupings that could be applied when examining NRLW data and supports the development of a framework for specifically training female rugby league players for the demands of the NRLW competition. Frontiers Media S.A. 2021-06-29 /pmc/articles/PMC8276862/ /pubmed/34268492 http://dx.doi.org/10.3389/fspor.2021.648126 Text en Copyright © 2021 Cummins, Charlton, Paul, Shorter, Buxton, Caia and Murphy. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Sports and Active Living Cummins, Cloe Charlton, Glen Paul, David Shorter, Kath Buxton, Simon Caia, Johnpaul Murphy, Aron Women's Rugby League: Positional Groups and Peak Locomotor Demands |
title | Women's Rugby League: Positional Groups and Peak Locomotor Demands |
title_full | Women's Rugby League: Positional Groups and Peak Locomotor Demands |
title_fullStr | Women's Rugby League: Positional Groups and Peak Locomotor Demands |
title_full_unstemmed | Women's Rugby League: Positional Groups and Peak Locomotor Demands |
title_short | Women's Rugby League: Positional Groups and Peak Locomotor Demands |
title_sort | women's rugby league: positional groups and peak locomotor demands |
topic | Sports and Active Living |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276862/ https://www.ncbi.nlm.nih.gov/pubmed/34268492 http://dx.doi.org/10.3389/fspor.2021.648126 |
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