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

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  • Thomas Sawczuk
  • Anna Palczewska
  • Ben Jones

Abstract

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.

Suggested Citation

  • Thomas Sawczuk & Anna Palczewska & Ben Jones, 2021. "Development of an expected possession value model to analyse team attacking performances in rugby league," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-14, November.
    • Handle: RePEc:plo:pone00:0259536
    DOI: 10.1371/journal.pone.0259536
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    References listed on IDEAS

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    1. Nimai Parmar & Nic James & Gary Hearne & Ben Jones, 2018. "Using principal component analysis to develop performance indicators in professional rugby league," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 18(6), pages 938-949, November.
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