Title
Here Comes the STRAIN: Analyzing Defensive Pass Rush in American Football with Player Tracking Data
Document Type
Article
Publication Date
7-25-2023
Publication Title
The American Statistician
Publisher Name
Taylor & Francis
Abstract
In American football, a pass rush is an attempt by the defensive team to disrupt the offense and prevent the quarterback (QB) from completing a pass. Existing metrics for assessing pass rush performance are either discrete-time quantities or based on subjective judgment. Using player tracking data, we propose STRAIN, a novel metric for evaluating pass rushers in the National Football League (NFL) at the continuous-time within-play level. Inspired by the concept of strain rate in materials science, STRAIN is a simple and interpretable means for measuring defensive pressure in football. It is a directly-observed statistic as a function of two features: the distance between the pass rusher and QB, and the rate at which this distance is being reduced. Our metric possesses great predictability of pressure and stability over time. We also fit a multilevel model for STRAIN to understand the defensive pressure contribution of every pass rusher at the play-level. We apply our approach to NFL data and present results for the first eight weeks of the 2021 regular season. In particular, we provide comparisons of STRAIN for different defensive positions and play outcomes, and rankings of the NFL’s best pass rushers according to our metric.
Recommended Citation
Nguyen, Quang; Yurko, Ronald; and Matthews, Gregory J.. Here Comes the STRAIN: Analyzing Defensive Pass Rush in American Football with Player Tracking Data. The American Statistician, , : , 2023. Retrieved from Loyola eCommons, Mathematics and Statistics: Faculty Publications and Other Works, http://dx.doi.org/10.1080/00031305.2023.2242442
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Copyright Statement
© Taylor & Francis, 2023.
Comments
Author Posting © Taylor & Francis, 2023. This is an Accepted Manuscript version of the following article, accepted for publication in The American Statistician, https://doi.org/10.1080/00031305.2023.2242442. It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.