AI Game Review
Our model correctly predicted Hawthorn to win at 72% probability. The margin model was sharp — predicting Hawthorn by 9.8 vs the actual margin of 12 points. The game's 140 points came in 29 points lower than the predicted 169. The model went 2/3 on this match. The 1-39 margin band call landed.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
Hawthorn
72%
GWS GIANTS
28%
AI Match Overview
Hawthorn are clear favourites here at 72%, with our model expecting a comfortable victory over GWS GIANTS. The model sees Hawthorn ahead on 5 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Hawthorn carry a 81-point ELO rating advantage (1731 vs 1650). Recent form favours Hawthorn with 4 wins from their last 5 compared to 2 for GWS GIANTS. The margin model predicts Hawthorn by 9.8 points with a combined total of 169.
Generated from model features • Pre-kick-off analysis
Edge Analysis
2 ACTIVE EDGESEach market is predicted by an independent model — H2H, margin, and totals may occasionally disagree.
H2H Recommendation
Hawthorn to Win @1.54
Winner ✓
Edge
+6.9%
Line / Spread
Hawthorn -10.5 @1.91
Winner ✓
Edge
+6.9%
Total Points
Over 166.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Hawthorn | WWWWL | 91.6 |
GWS GIANTS | WWLLL | 84.8 |
Avg Conceded
71.6
Hawthorn
83.4
GWS GIANTS
Avg Margin
20.0
Hawthorn
1.4
GWS GIANTS
Disposals
360.8
Hawthorn
358.4
GWS GIANTS
Inside 50s
50.0
Hawthorn
50.0
GWS GIANTS
📊Team ELO Ratings
🏈Positional Matchups
Player ELO aggregated by position group — higher = stronger unit
📈Recent Form (Last 5)
🔑Key Prediction Factors
What the model weighted most in this prediction
Model Confidence
72%
Hawthorn predicted to win by 10 points
Predicted total: 169 · Line: +9.8
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.16
Team Effectiveness
0.00
Effort = pressure acts + tackles + contested possessions per minute on field, z-scored vs career avg. Effectiveness = disposal efficiency + fantasy/min + score involvements − errors, z-scored vs career avg.
Goal Scorer Predictions
AI-powered goal scorer predictions and player prop markets — built on our 6-model player stats engine.