Simulation-based decision making in the NFL using NFLSimulatoR

Benjamin Williams (), Will Palmquist () and Ryan Elmore ()
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Benjamin Williams: University of Denver
Will Palmquist: University of Denver
Ryan Elmore: University of Denver

Annals of Operations Research, 2023, vol. 325, issue 1, No 32, 742 pages

Abstract: Abstract In this paper, we introduce an R software package for simulating plays and drives using play-by-play data from the National Football League. The simulations are generated by sampling play-by-play data from previous football seasons. The sampling procedure adds statistical rigor to any decisions or inferences arising from examining the simulations. We highlight that the package is particularly useful as a data-driven tool for evaluating potential in-game strategies or rule changes within the league. We demonstrate its utility by evaluating the oft-debated strategy of “going for it” on fourth down and investigating whether or not teams should pass more than the current standard.

Keywords: Sports statistics; Analytics; National Football League (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-022-04524-7

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