AFL

AFL 2016 Grand Final Predictions: Data Scientists’ Predictive Model

The model and the market are identical in this Saturday's AFL Grand Final, listing Sydney Swans as comfortable favourites.

Brownlow Medal 2016 Predictions

Associate Professor Michael Bailey is back on The Hub to give his expert predictions for the 2016 Brownlow Medal. This year's predictions see a clear winner with Geelong's Patrick Dangerfield a 89% chance of taking home Charlie this year.

AFL Finals Week 3 Predictions: Data Scientists’ Predictive Model

Our Data Scientists are predicting a Geelong-GWS Giants 2016 Grand Final. Find out their prices for Week 3 of the Finals.

AFL Finals Week 2 Predictions: Data Scientists’ Predictive Model

Hawthorn and Sydney are expected to progress to Week 3 of the AFL Finals, according to the Data Scientists Predictive Model.

AFL Finals Week 1 Predictions: Data Scientists’ Predictive Model

In Week 1 of the AFL Finals Series the Data Scientists split the two Qualifying Final matches between a Neutral Venue and HGA with contrasting results.

AFL Round 23 Predictions: Data Scientists’ Predictive Model

Compare the Model’s predicted prices to the market to identify your value AFL Round 23 bets.

AFL Round 22 Predictions: Data Scientists’ Predictive Model

Compare the Model’s predicted prices to the market to identify your value AFL Round 22 bets.

AFL Round 21 Predictions: Data Scientists’ Predictive Model

Carlton and Port Adelaide have been identified as the early value BACK bets from the Predictive Model in Round 21. Compare the Model's predicted prices to the market.

AFL Round 20 Predictions: Data Scientists’ Predictive Model

Collingwood and West Coast have been identified as the early value BACK bets from the Predictive Model in Round 20. Compare the Model's predicted prices to the market

AFL Round 19 Predictions: Data Scientists’ Predictive Model

North Melbourne and West Coast have been identified as the early value BACK bets from the Predictive Model in Round 19. Compare the Model's predicted prices to the market