Real time prediction of match outcomes in Australian football.

This study aimed to determine whether machine learning models based on technical performance and not score margin could be used to predict end-of-match outcome of Australian football matches in real-time. If efficacious, these models could be used to generate insights about team performance and support the decision-making of coaches during matches. A database of 168 team technical performance indicators from 829 Australian Football League matches played between 2017 and 2021 was used.

A framework to explain the in-match decision-making of elite Australian football coaches.

The ability to make effective decisions is an important function of any football coach, whether during training, team selection, match-day performance or post-match player evaluation. It is not yet known how elite Australian football coaches make decisions during matches, in time-constrained but well-resourced environments. This study is the first to explore the decision-making of elite Australian football coaches during matches, in pursuit of identifying opportunities to improve the translation and implementation of research findings into the competitive match environment.

The effect of team formation on defensive performance in Australian football.

Objectives: Understanding the successful characteristics of team formation during different scenarios in Australian Football matches can assist coaches in making important tactical match-day and training decisions. The aims of this study were to explore the outcomes of entries inside 50 m of the goal, in Australian Football and to determine whether there was an association between team formation and team defensive performance after a turnover.

Design: Observational.