A Markov Model of Football: Using Stochastic Processes to Model a Football Drive : Journal of Quantitative Analysis in Sports

www.degruyter.com uses cookies, tags, and tracking settings to store information that help give you the very best browsing experience.
To understand more about cookies, tags, and tracking, see our Privacy Statement
I accept all cookies for the De Gruyter Online site

Jump to ContentJump to Main Navigation

Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Mark Glickman PhD


SCImago Journal Rank (SJR) 2014: 0.265
Source Normalized Impact per Paper (SNIP) 2014: 0.513
Impact per Publication (IPP) 2014: 0.452

VolumeIssuePage

30,00 € / $42.00 / £23.00

Get Access to Full Text

A Markov Model of Football: Using Stochastic Processes to Model a Football Drive

Keith Goldner1

1Northwestern University

Citation Information: Journal of Quantitative Analysis in Sports. Volume 8, Issue 1, ISSN (Online) 1559-0410, DOI: 10.1515/1559-0410.1400, March 2012

Publication History

Published Online:
2012-03-12

A team is backed into a 4th-and-26 from their own 25, down 3 points. What are the odds that drive ends in a field goal? In the 2003 playoffs, Donovan McNabb and the Eagles scoffed at such a probability as they converted and ultimately kicked a field goal to send the game into overtime. This study creates a mathematical model of a football drive that can calculate such probabilities, labeling down, distance, and yard line into states in an absorbing Markov chain. The Markov model provides a basic framework for evaluating play in football. With all the details of the model—absorption probabilities, expected time until absorption, expected points—we gain a much greater situational understanding for in-game analysis.

Keywords: stochastic processes; football; markov chain

Comments (0)

Please log in or register to comment.