Analyzing dependence matrices to investigate relationships between national football league combine event performances

Russell Brook T. () and Hogan Paul ()
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Russell Brook T.: Clemson University, Department of Mathematical Sciences, Clemson, SC 29634, USA, Office: +1 864-656-4571, Fax: +1 864-656-5230
Hogan Paul: Clemson University, Clemson University Football Coaching Staff, Clemson, SC 29634, USA

Journal of Quantitative Analysis in Sports, 2018, vol. 14, issue 4, 201-212

Abstract: The National Football League (NFL) Scouting Combine takes place annually for the purpose of allowing NFL teams to evaluate prospects. The battery of six physical tests receives a great deal of attention, and are a focus of team personnel as well as fans of NFL teams. Recently, some have suggested that the current battery of tests should be modified. This work aims to characterize the multivariate dependence structure between tests for Combine prospects, for both typical and elite-level performers, for the purpose of better understanding the current battery of tests before making modifications. Through analysis of two pairwise dependence matrices, one quantifying dependence in the center of the distribution and the other quantifying dependence in the tails of the distribution, this analysis finds that several events show differing levels of association, and that fewer Combine events may be sufficient going forward.

Keywords: asymptotic dependence; eigendecomposition; multivariate extremes; Simpson’s paradox; tail pairwise dependence matrix (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1515/jqas-2017-0086

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