A machine learning model that predicts the winners of AFL football matches
Correct tips
12
Accuracy
68.3%
Top percentile of AFL footy tipping
38%
Welcome to the Footy Forest. Here you’ll find predictions, details on how the model is performing, rankings of each team and occasional statistical analyses of AFL footy and other sports.
Tips based on teams selected on Thursday night | ||||||||
---|---|---|---|---|---|---|---|---|
Home | Away | Relative advantage to the home team1 | Predicted winner | Probability | Margin | |||
Power | Venue exp | Travel | Team rating | |||||
Sydney Swans | Hawthorn | -7.8 | 75.0 | 20.1 | 17.8 | Sydney Swans | 56 | 6 |
GWS Giants | Collingwood | 3.8 | 54.5 | 19.5 | 22.3 | GWS Giants | 66 | 17 |
1This is the difference between the teams where 100 is the highest since 2015 and -100 is the lowest |