Development of an expected possession value model to analyse team attacking performances in rugby league

This study aimed to evaluate team attacking performances in rugby league via expected possession value (EPV) models. Location data from 59,233 plays in 180 Super League matches across the 2019 Super League season were used. Six EPV models were generated using arbitrary zone sizes (EPV-308 and EPV-77...

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Autores principales:	Thomas Sawczuk, Anna Palczewska, Ben Jones
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/970c845293f647858cd2124ad66f2b45
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spelling	oai:doaj.org-article:970c845293f647858cd2124ad66f2b452021-11-25T06:11:00ZDevelopment of an expected possession value model to analyse team attacking performances in rugby league1932-6203https://doaj.org/article/970c845293f647858cd2124ad66f2b452021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589207/?tool=EBIhttps://doaj.org/toc/1932-6203This study aimed to evaluate team attacking performances in rugby league via expected possession value (EPV) models. Location data from 59,233 plays in 180 Super League matches across the 2019 Super League season were used. Six EPV models were generated using arbitrary zone sizes (EPV-308 and EPV-77) or aggregated according to the total zone value generated during a match (EPV-37, EPV-19, EPV-13 and EPV-9). Attacking sets were considered as Markov Chains, allowing the value of each zone visited to be estimated based on the outcome of the possession. The Kullback-Leibler Divergence was used to evaluate the reproducibility of the value generated from each zone (the reward distribution) by teams between matches. Decreasing the number of zones improved the reproducibility of reward distributions between matches but reduced the variation in zone values. After six previous matches, the subsequent match’s zones had been visited on 95% or more occasions for EPV-19 (95±4%), EPV-13 (100±0%) and EPV-9 (100±0%). The KL Divergence values were infinity (EPV-308), 0.52±0.05 (EPV-77), 0.37±0.03 (EPV-37), 0.20±0.02 (EPV-19), 0.13±0.02 (EPV-13) and 0.10±0.02 (EPV-9). This study supports the use of EPV-19 and EPV-13, but not EPV-9 (too little variation in zone values), to evaluate team attacking performance in rugby league.Thomas SawczukAnna PalczewskaBen JonesPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Thomas Sawczuk Anna Palczewska Ben Jones Development of an expected possession value model to analyse team attacking performances in rugby league
description	This study aimed to evaluate team attacking performances in rugby league via expected possession value (EPV) models. Location data from 59,233 plays in 180 Super League matches across the 2019 Super League season were used. Six EPV models were generated using arbitrary zone sizes (EPV-308 and EPV-77) or aggregated according to the total zone value generated during a match (EPV-37, EPV-19, EPV-13 and EPV-9). Attacking sets were considered as Markov Chains, allowing the value of each zone visited to be estimated based on the outcome of the possession. The Kullback-Leibler Divergence was used to evaluate the reproducibility of the value generated from each zone (the reward distribution) by teams between matches. Decreasing the number of zones improved the reproducibility of reward distributions between matches but reduced the variation in zone values. After six previous matches, the subsequent match’s zones had been visited on 95% or more occasions for EPV-19 (95±4%), EPV-13 (100±0%) and EPV-9 (100±0%). The KL Divergence values were infinity (EPV-308), 0.52±0.05 (EPV-77), 0.37±0.03 (EPV-37), 0.20±0.02 (EPV-19), 0.13±0.02 (EPV-13) and 0.10±0.02 (EPV-9). This study supports the use of EPV-19 and EPV-13, but not EPV-9 (too little variation in zone values), to evaluate team attacking performance in rugby league.
format	article
author	Thomas Sawczuk Anna Palczewska Ben Jones
author_facet	Thomas Sawczuk Anna Palczewska Ben Jones
author_sort	Thomas Sawczuk
title	Development of an expected possession value model to analyse team attacking performances in rugby league
title_short	Development of an expected possession value model to analyse team attacking performances in rugby league
title_full	Development of an expected possession value model to analyse team attacking performances in rugby league
title_fullStr	Development of an expected possession value model to analyse team attacking performances in rugby league
title_full_unstemmed	Development of an expected possession value model to analyse team attacking performances in rugby league
title_sort	development of an expected possession value model to analyse team attacking performances in rugby league
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/970c845293f647858cd2124ad66f2b45
work_keys_str_mv	AT thomassawczuk developmentofanexpectedpossessionvaluemodeltoanalyseteamattackingperformancesinrugbyleague AT annapalczewska developmentofanexpectedpossessionvaluemodeltoanalyseteamattackingperformancesinrugbyleague AT benjones developmentofanexpectedpossessionvaluemodeltoanalyseteamattackingperformancesinrugbyleague
_version_	1718414057948577792

Development of an expected possession value model to analyse team attacking performances in rugby league

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