Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball

Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome...

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Autores principales: Francis, John, Owen, Alun, Peters, Derek. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6626905/
https://www.ncbi.nlm.nih.gov/pubmed/31338046
http://dx.doi.org/10.3389/fpsyg.2019.01431
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author Francis, John
Owen, Alun
Peters, Derek. M.
author_facet Francis, John
Owen, Alun
Peters, Derek. M.
author_sort Francis, John
collection PubMed
description Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men’s wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modeling. The valid and reliable template developed Francis et al. (2019) was used to analyze video footage in SportsCode from 31 games at the men’s 2015 European Wheelchair Basketball Championships. The 31 games resulted in 6,126 rows of data which were exported and converted into a CSV file, analyzed using R (R Core Team, 2015) and subjected to a data modeling process. Chi-square analyses identified significant (p < 0.05) relationships between Game Outcome and 19 Categorical Predictor Variables. Automated stepwise binary regression model building was completed using 70% of the data (4,282 possessions) and produced a model that included 12 Categorical Predictor Variables. The accuracy of the developed model was deemed to be acceptable at accurately predicting the remaining 30% of the data (1,844 possessions) and produced an area under the receiver operating characteristic curve value of 0.759. The model identified the odds of winning are more than double when the team in possession are in a state of winning at the start of the possession are increased five-fold when the offensive team do not use a 1.0 or 1.5 classified player, but are increased six-fold when the offensive team use three or more 3.0 or 3.5 players. The final model can be used by coaches, players and support staff to devise training and game strategies that involve selecting the most appropriate offensive and defensive approaches when performing ball possessions to enhance the likelihood of winning in elite men’s wheelchair basketball.
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spelling pubmed-66269052019-07-23 Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball Francis, John Owen, Alun Peters, Derek. M. Front Psychol Psychology Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men’s wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modeling. The valid and reliable template developed Francis et al. (2019) was used to analyze video footage in SportsCode from 31 games at the men’s 2015 European Wheelchair Basketball Championships. The 31 games resulted in 6,126 rows of data which were exported and converted into a CSV file, analyzed using R (R Core Team, 2015) and subjected to a data modeling process. Chi-square analyses identified significant (p < 0.05) relationships between Game Outcome and 19 Categorical Predictor Variables. Automated stepwise binary regression model building was completed using 70% of the data (4,282 possessions) and produced a model that included 12 Categorical Predictor Variables. The accuracy of the developed model was deemed to be acceptable at accurately predicting the remaining 30% of the data (1,844 possessions) and produced an area under the receiver operating characteristic curve value of 0.759. The model identified the odds of winning are more than double when the team in possession are in a state of winning at the start of the possession are increased five-fold when the offensive team do not use a 1.0 or 1.5 classified player, but are increased six-fold when the offensive team use three or more 3.0 or 3.5 players. The final model can be used by coaches, players and support staff to devise training and game strategies that involve selecting the most appropriate offensive and defensive approaches when performing ball possessions to enhance the likelihood of winning in elite men’s wheelchair basketball. Frontiers Media S.A. 2019-07-02 /pmc/articles/PMC6626905/ /pubmed/31338046 http://dx.doi.org/10.3389/fpsyg.2019.01431 Text en Copyright © 2019 Francis, Owen and Peters. 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 Psychology
Francis, John
Owen, Alun
Peters, Derek. M.
Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
title Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
title_full Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
title_fullStr Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
title_full_unstemmed Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
title_short Making Every “Point” Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
title_sort making every “point” count: identifying the key determinants of team success in elite men’s wheelchair basketball
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6626905/
https://www.ncbi.nlm.nih.gov/pubmed/31338046
http://dx.doi.org/10.3389/fpsyg.2019.01431
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