Open AccessDynamically scheduling NFL games to reduce strength of schedule variability
Author(s) -
Elizabeth L. Bouzarth,
Andrew W. Cromer,
William J. Fravel,
Benjamin C. Grannan,
Kevin R. Hutson
Publication year - 2021
Publication title -
journal of sports analytics
Language(s) - English
Resource type - Journals
eISSN - 2215-0218
pISSN - 2215-020X
DOI - 10.3233/jsa-200428
Subject(s) - schedule , league , scheduling (production processes) , football , computer science , pairwise comparison , operations research , operations management , engineering , artificial intelligence , political science , physics , astronomy , law , operating system
The National Football League (NFL) schedules regular season games so that some matchups are based on the previous year’s results. Since team composition changes from year to year, this scheduling policy creates variation in teams’ strength of schedules and sometimes benefits teams unfairly, allowing some an easier path to the playoffs than others. This paper proposes methods to produce an NFL schedule that combine some of its traditional elements with dynamically scheduled games aimed at optimizing different objectives, such as reducing the variability of teams’ strength of schedule or minimizing the number of pairwise comparisons needed to differentiate team quality so as to make each teams’ regular season schedule as fair as possible.