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Preparing for an Australian Football League Women's League Season

The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes (n = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were coll...

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Autores principales: Thornton, Heidi Rose, Armstrong, Cameron R., Rigby, Alex, Minahan, Clare L., Johnston, Rich D., Duthie, Grant Malcolm
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785869/
https://www.ncbi.nlm.nih.gov/pubmed/33426520
http://dx.doi.org/10.3389/fspor.2020.608939
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author Thornton, Heidi Rose
Armstrong, Cameron R.
Rigby, Alex
Minahan, Clare L.
Johnston, Rich D.
Duthie, Grant Malcolm
author_facet Thornton, Heidi Rose
Armstrong, Cameron R.
Rigby, Alex
Minahan, Clare L.
Johnston, Rich D.
Duthie, Grant Malcolm
author_sort Thornton, Heidi Rose
collection PubMed
description The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes (n = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were collected, including total distance, high-speed distance, very high-speed distance, acceleration, and acceleration load. Using raw GNSS files, 1-min moving averages were calculated for speed (m·min(−1)) and acceleration (m·s(−2)), and were multiplied by time, specifying total distance (m), and by body mass to quantify impulse (kN·s(−1)). The distribution of distance and impulse accumulated at varied intensities relative to MMs was calculated, with percentages ranging from zero to 110%. Drills were categorized as either; warm-ups, skill drills, games (i.e., small-sided games), conditioning and matches. Linear mixed models determined if the distribution of intensity within each threshold (>50%) varied between drill types and matches, and if the distribution within drill types varied across the season. Effects were described using standardized effect sizes (ES) and 90% confidence limits (CL). Compared to matches, a higher proportion of distance was accumulated at 50% of the MM within warm-ups and conditioning (ES range 0.86–1.14). During matches a higher proportion of distance was accumulated at 60% of MM when compared to warms ups, skill drills and conditioning (0.73–1.87). Similarly, greater proportion of distance was accumulated between 70 and 100% MM in matches compared to skill drills and warm-ups (1.05–3.93). For impulse, matches had a higher proportion between 60 and 80% of the MM compared to conditioning drills (0.91–3.23). There were no other substantial differences in the proportion of impulse between matches and drill types. When comparing phases, during competition there was a higher proportion of distance accumulated at 50% MM than general preparation (1.08). A higher proportion of distance was covered at higher intensities within matches compared to drills. The proportion of impulse was higher between 60 and 80% MM within matches compared to conditioning. Practitioners can therefore ensure athletes are not only exposed to the intensities common within competition, but also the volume accumulated is comparable, which may have positive performance outcomes, but is also extremely important in the return to play process.
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spelling pubmed-77858692021-01-07 Preparing for an Australian Football League Women's League Season Thornton, Heidi Rose Armstrong, Cameron R. Rigby, Alex Minahan, Clare L. Johnston, Rich D. Duthie, Grant Malcolm Front Sports Act Living Sports and Active Living The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes (n = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were collected, including total distance, high-speed distance, very high-speed distance, acceleration, and acceleration load. Using raw GNSS files, 1-min moving averages were calculated for speed (m·min(−1)) and acceleration (m·s(−2)), and were multiplied by time, specifying total distance (m), and by body mass to quantify impulse (kN·s(−1)). The distribution of distance and impulse accumulated at varied intensities relative to MMs was calculated, with percentages ranging from zero to 110%. Drills were categorized as either; warm-ups, skill drills, games (i.e., small-sided games), conditioning and matches. Linear mixed models determined if the distribution of intensity within each threshold (>50%) varied between drill types and matches, and if the distribution within drill types varied across the season. Effects were described using standardized effect sizes (ES) and 90% confidence limits (CL). Compared to matches, a higher proportion of distance was accumulated at 50% of the MM within warm-ups and conditioning (ES range 0.86–1.14). During matches a higher proportion of distance was accumulated at 60% of MM when compared to warms ups, skill drills and conditioning (0.73–1.87). Similarly, greater proportion of distance was accumulated between 70 and 100% MM in matches compared to skill drills and warm-ups (1.05–3.93). For impulse, matches had a higher proportion between 60 and 80% of the MM compared to conditioning drills (0.91–3.23). There were no other substantial differences in the proportion of impulse between matches and drill types. When comparing phases, during competition there was a higher proportion of distance accumulated at 50% MM than general preparation (1.08). A higher proportion of distance was covered at higher intensities within matches compared to drills. The proportion of impulse was higher between 60 and 80% MM within matches compared to conditioning. Practitioners can therefore ensure athletes are not only exposed to the intensities common within competition, but also the volume accumulated is comparable, which may have positive performance outcomes, but is also extremely important in the return to play process. Frontiers Media S.A. 2020-12-23 /pmc/articles/PMC7785869/ /pubmed/33426520 http://dx.doi.org/10.3389/fspor.2020.608939 Text en Copyright © 2020 Thornton, Armstrong, Rigby, Minahan, Johnston and Duthie. http://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
Thornton, Heidi Rose
Armstrong, Cameron R.
Rigby, Alex
Minahan, Clare L.
Johnston, Rich D.
Duthie, Grant Malcolm
Preparing for an Australian Football League Women's League Season
title Preparing for an Australian Football League Women's League Season
title_full Preparing for an Australian Football League Women's League Season
title_fullStr Preparing for an Australian Football League Women's League Season
title_full_unstemmed Preparing for an Australian Football League Women's League Season
title_short Preparing for an Australian Football League Women's League Season
title_sort preparing for an australian football league women's league season
topic Sports and Active Living
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785869/
https://www.ncbi.nlm.nih.gov/pubmed/33426520
http://dx.doi.org/10.3389/fspor.2020.608939
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