Simulation-Based Decision Making in the NFL using NFLSimulatoR
Applications
2022-01-13 v3
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 on fourth down and investigating whether or not teams should pass more than the current standard.
Cite
@article{arxiv.2102.01846,
title = {Simulation-Based Decision Making in the NFL using NFLSimulatoR},
author = {Benjamin Williams and Will Palmquist and Ryan Elmore},
journal= {arXiv preprint arXiv:2102.01846},
year = {2022}
}