The Bradley-Terry Model in Binary Outcome Driven Rankings: An Application in Amateur Hockey

Ranking systems serve critical roles in sport settings, most notably in determining playoff participants and seeding. Many ranking methodologies exist that are flexible enough to incorporate many input measures and produce models that are highly predictive of game outcomes. However, there are circumstances—especially for amateur sport leagues—in which more complex inputs are either unavailable or not desirable, as they may lead to adverse performance incentives. Therefore, the goal of this paper is to highlight a ranking methodology that only considers binary game outcomes, i.e., wins and losses. Specifically, we consider the efficacy of the Bradley-Terry Model to efficiently rank sport teams for playoff consideration. We apply this method as a case study to the New England Prep School Ice Hockey Association (NEPSIHA), and compare the accuracy of their current ranking system to the Bradley-Terry model using simulation methods. We show that Bradley-Terry significantly outperforms NEPSIHA’s current method, especially when teams face unbalanced strengths of schedule. This result holds under various league competitive balance distributions.