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Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball

The purposes of this study were to (i) develop a field-goal shooting performance analysis template and (ii) explore the impact of each identified variable upon the likely outcome of a field-goal attempt using binary logistic regression modelling in elite men’s wheelchair basketball. First, a field-g...

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Detalles Bibliográficos
Autores principales: Francis, John W., Owen, Alun J., Peters, Derek M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790280/
https://www.ncbi.nlm.nih.gov/pubmed/33411713
http://dx.doi.org/10.1371/journal.pone.0244257
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author Francis, John W.
Owen, Alun J.
Peters, Derek M.
author_facet Francis, John W.
Owen, Alun J.
Peters, Derek M.
author_sort Francis, John W.
collection PubMed
description The purposes of this study were to (i) develop a field-goal shooting performance analysis template and (ii) explore the impact of each identified variable upon the likely outcome of a field-goal attempt using binary logistic regression modelling in elite men’s wheelchair basketball. First, a field-goal shooting performance analysis template was developed that included 71 Action Variables (AV) grouped within 22 Categorical Predictor Variables (CPV) representing offensive, defensive and game context variables. Second, footage of all 5,105 field-goal attempts from 12 teams during the men’s 2016 Rio De Janeiro Paralympic Games wheelchair basketball competition were analysed using the template. Pearson’s chi-square analyses found that 18 of the CPV were significantly associated with field-goal attempt outcome (p < 0.05), with seven of them reaching moderate association (Cramer’s V: 0.1–0.3). Third, using 70% of the dataset (3,574 field-goal attempts), binary logistic regression analyses identified that five offensive variables (classification category of the player, the action leading up to the field-goal attempt, the time left on the clock, the location of the shot, and the movement of the player), two defensive variables (the pressure being exerted by the defence, and the number of defenders within a 1-meter radius) and 1 context variable (the finishing position of the team in the competition) affected the probability of a successful field-goal attempt. The quality of the developed model was determined acceptable (greater than 65%), producing an area under the curve value of 68.5% when the model was run against the remaining 30% of the dataset (1,531 field-goal attempts). The development of the model from such a large sample of objective data is unique. As such it offers robust empirical evidence to enable coaches, performance analysts and players to move beyond anecdote, in order to appreciate the potential effect of various and varying offensive, defensive and contextual variables on field-goal success.
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spelling pubmed-77902802021-01-14 Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball Francis, John W. Owen, Alun J. Peters, Derek M. PLoS One Research Article The purposes of this study were to (i) develop a field-goal shooting performance analysis template and (ii) explore the impact of each identified variable upon the likely outcome of a field-goal attempt using binary logistic regression modelling in elite men’s wheelchair basketball. First, a field-goal shooting performance analysis template was developed that included 71 Action Variables (AV) grouped within 22 Categorical Predictor Variables (CPV) representing offensive, defensive and game context variables. Second, footage of all 5,105 field-goal attempts from 12 teams during the men’s 2016 Rio De Janeiro Paralympic Games wheelchair basketball competition were analysed using the template. Pearson’s chi-square analyses found that 18 of the CPV were significantly associated with field-goal attempt outcome (p < 0.05), with seven of them reaching moderate association (Cramer’s V: 0.1–0.3). Third, using 70% of the dataset (3,574 field-goal attempts), binary logistic regression analyses identified that five offensive variables (classification category of the player, the action leading up to the field-goal attempt, the time left on the clock, the location of the shot, and the movement of the player), two defensive variables (the pressure being exerted by the defence, and the number of defenders within a 1-meter radius) and 1 context variable (the finishing position of the team in the competition) affected the probability of a successful field-goal attempt. The quality of the developed model was determined acceptable (greater than 65%), producing an area under the curve value of 68.5% when the model was run against the remaining 30% of the dataset (1,531 field-goal attempts). The development of the model from such a large sample of objective data is unique. As such it offers robust empirical evidence to enable coaches, performance analysts and players to move beyond anecdote, in order to appreciate the potential effect of various and varying offensive, defensive and contextual variables on field-goal success. Public Library of Science 2021-01-07 /pmc/articles/PMC7790280/ /pubmed/33411713 http://dx.doi.org/10.1371/journal.pone.0244257 Text en © 2021 Francis et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Francis, John W.
Owen, Alun J.
Peters, Derek M.
Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
title Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
title_full Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
title_fullStr Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
title_full_unstemmed Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
title_short Predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
title_sort predicting field-goal success according to offensive, defensive and contextual variables in elite men’s wheelchair basketball
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790280/
https://www.ncbi.nlm.nih.gov/pubmed/33411713
http://dx.doi.org/10.1371/journal.pone.0244257
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