Using Random Forests to Estimate Win Probability Before Each Play of an NFL Football Game

• Activity Number: 539
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Sports
• Author(s): Dennis Lock*+ and Dan Nettleton
• Companies: Iowa State University and Iowa State University
• Keywords: Random Forest ; NFL ; Win Probability ; play-by-play ; Regression Tree

Abstract

Before any play of a National Football League (NFL) game, the probability that a team will win depends on many in-game variables (such as time remaining, down and distance, yard line and current score) as well as many game-level variables (such as home team, team win-loss record and opponent win-loss record). We use random forest methodology to combine in-game and game-level variables to estimate Win Probability before any play of an NFL game. Our methodology is applied to play-by-play data from the national football league for the 12 season from 2000 to 2011. To illustrate the performance of our method, we show plots of win probability vs. time remaining for a few interesting NFL games from past seasons.