An analysis of factors impacting team strengths in the Australian Football League using time-variant Bradley-Terry models

Abstract

Australian Rules Football is a field invasion game where two teams compete to score the most points. While complex machine learning models can predict match outcomes post-game, their lack of interpretability limits understanding of the factors influencing team performance. Using data from the male Australian Football League (2015–2023), we estimate team strengths and their determinants by fitting flexible Bradley-Terry models. We identify teams significantly stronger or weaker than average, with stronger teams placing higher in the previous season’s ladder and leading in Forward 50 activity, goal shots, and scoring. Playing at home consistently creates an advantage, regardless of strength. When used for forward prediction, models incorporating team-specific, time-variant features correctly anticipate up to 71.5% of outcomes. Our approach thus enables interpretable strength estimation and competitive forecasting, supporting data-driven strategies and training.