Feeling the Pressure: A Unified Framework for Automating Pass Rushing Statistics in NFL Games

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Sungmin Hong, Laura Kulowski, Dan Volk, Henry Wang, Keegan Abdoo, Conor McQuiston, Kyeong Hoon (Jonathan) Jung, Mike Band, Diego Socolinsky


In spite of the importance of the pass rush in professional football, pass rushing statistics only include the final outcomes of a play, e.g., sack and pass-made. They do not capture the dynamics of the pass rush or fine-grained insights throughout a play on how much pressure a rusher generates during the rush. In this paper, we propose a unified framework that enables the estimation of defensive pressure scores throughout a play with high accuracy and performance for rusher and blocker identification, rusher-blocker match-up and pressure score estimation and show the real-world applications of our framework including enriched analytics.