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Investigating the multivariate nature of NHL player performance with structural equation modeling

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  • Sean N Riley

Abstract

Hockey is a complex and multifaceted game, yet many of the statistical tools used to evaluate performance are univariate. To garner a better understanding of hockey’s multifaceted nature, two structural equation models (SEMs) assessing the interrelations between offense, defense, and possession were built from three seasons of NHL data. Overall, it was found that the concepts of offense, defense, and possession are best understood via a small constellation of measured variables, and that offense mediates the relationship between possession and defense such that higher levels of offense leads to poorer defensive performance. These findings are discussed within the context of ranking player performance.

Suggested Citation

  • Sean N Riley, 2017. "Investigating the multivariate nature of NHL player performance with structural equation modeling," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-29, September.
    • Handle: RePEc:plo:pone00:0184346
    DOI: 10.1371/journal.pone.0184346
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    References listed on IDEAS

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    1. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part I: General Sports Applications," Interfaces, INFORMS, vol. 42(2), pages 105-108, April.
    2. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part II: Sports Scheduling Applications," Interfaces, INFORMS, vol. 42(3), pages 229-231, June.
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