A GNSS-based method to define athlete manoeuvrability in field-based team sports.

This study presented a method of quantifying the manoeuvrability of two field-based team sport athletes and investigated its relationship with running velocity during competition. Across a season, 10 Hz Global navigation satellite system (GNSS) devices were worn during matches by 62 athletes (Austra...

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Autores principales: Grant Malcolm Duthie, Sam Robertson, Heidi Rose Thornton
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Publicado: Public Library of Science (PLoS) 2021
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Acceso en línea:https://doaj.org/article/ca1f481c34ff4d15807a541529a20e59
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spelling oai:doaj.org-article:ca1f481c34ff4d15807a541529a20e592021-12-02T20:12:34ZA GNSS-based method to define athlete manoeuvrability in field-based team sports.1932-620310.1371/journal.pone.0260363https://doaj.org/article/ca1f481c34ff4d15807a541529a20e592021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0260363https://doaj.org/toc/1932-6203This study presented a method of quantifying the manoeuvrability of two field-based team sport athletes and investigated its relationship with running velocity during competition. Across a season, 10 Hz Global navigation satellite system (GNSS) devices were worn during matches by 62 athletes (Australian Football League [AFL]; n = 36, 17 matches, National Rugby League [NRL]; n = 26, 21 matches). To quantify manoeuvrability, tortuosity was calculated from the X and Y coordinates from match GNSS files (converted from latitude and longitude). Tortuosity was calculated as 100 x natural logarithm of the chord distance (distance travelled between X and Y coordinates), divided by the straight-line distance. The maximal tortuosity was then quantified for each 0.5 m∙s-1 speed increment, ranging from 0 to the highest value for each game file. A quadratic model was fitted for each match file, controlling for the curvilinear relationship between tortuosity and velocity. A comparison of the quadratic coefficients between sports, and within sport between positions was investigated using linear mixed models. Resulting standard deviations (SDs) and mean differences were then assessed to establish standardized effect sizes (ES) and 90% confidence intervals (CI). A curvilinear relationship exists between maximal tortuosity and running speed, reflecting that as speed increases, athletes' ability to deviate from a linear path is compromised (i.e., run in a more linear path). Compared to AFL, NRL had a greater negative quadratic coefficient (a) (ES = 0.70; 0.47 to 0.93) for the 5 second analysis, meaning that as speed increased, NRL athletes' manoeuvrability reduced at a faster rate than when compared to AFL. There were no positional differences within each sport. GNSS derived information can be used to provide a measure of manoeuvrability tortuosity during NRL and AFL matches. The curvilinear relationship between tortuosity and speed demonstrated that as speed increased, manoeuvrability was compromised.Grant Malcolm DuthieSam RobertsonHeidi Rose ThorntonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0260363 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Grant Malcolm Duthie
Sam Robertson
Heidi Rose Thornton
A GNSS-based method to define athlete manoeuvrability in field-based team sports.
description This study presented a method of quantifying the manoeuvrability of two field-based team sport athletes and investigated its relationship with running velocity during competition. Across a season, 10 Hz Global navigation satellite system (GNSS) devices were worn during matches by 62 athletes (Australian Football League [AFL]; n = 36, 17 matches, National Rugby League [NRL]; n = 26, 21 matches). To quantify manoeuvrability, tortuosity was calculated from the X and Y coordinates from match GNSS files (converted from latitude and longitude). Tortuosity was calculated as 100 x natural logarithm of the chord distance (distance travelled between X and Y coordinates), divided by the straight-line distance. The maximal tortuosity was then quantified for each 0.5 m∙s-1 speed increment, ranging from 0 to the highest value for each game file. A quadratic model was fitted for each match file, controlling for the curvilinear relationship between tortuosity and velocity. A comparison of the quadratic coefficients between sports, and within sport between positions was investigated using linear mixed models. Resulting standard deviations (SDs) and mean differences were then assessed to establish standardized effect sizes (ES) and 90% confidence intervals (CI). A curvilinear relationship exists between maximal tortuosity and running speed, reflecting that as speed increases, athletes' ability to deviate from a linear path is compromised (i.e., run in a more linear path). Compared to AFL, NRL had a greater negative quadratic coefficient (a) (ES = 0.70; 0.47 to 0.93) for the 5 second analysis, meaning that as speed increased, NRL athletes' manoeuvrability reduced at a faster rate than when compared to AFL. There were no positional differences within each sport. GNSS derived information can be used to provide a measure of manoeuvrability tortuosity during NRL and AFL matches. The curvilinear relationship between tortuosity and speed demonstrated that as speed increased, manoeuvrability was compromised.
format article
author Grant Malcolm Duthie
Sam Robertson
Heidi Rose Thornton
author_facet Grant Malcolm Duthie
Sam Robertson
Heidi Rose Thornton
author_sort Grant Malcolm Duthie
title A GNSS-based method to define athlete manoeuvrability in field-based team sports.
title_short A GNSS-based method to define athlete manoeuvrability in field-based team sports.
title_full A GNSS-based method to define athlete manoeuvrability in field-based team sports.
title_fullStr A GNSS-based method to define athlete manoeuvrability in field-based team sports.
title_full_unstemmed A GNSS-based method to define athlete manoeuvrability in field-based team sports.
title_sort gnss-based method to define athlete manoeuvrability in field-based team sports.
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/ca1f481c34ff4d15807a541529a20e59
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