AI Game Review
Our model correctly predicted Hawthorn to win at 87% probability. The margin model missed here — predicting 6.1 but the actual margin was 64 points. Hawthorn led 63–24 at the break and pulled away in the second half to win by 64. 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
87%
Collingwood
13%
AI Match Overview
Hawthorn are clear favourites here at 87%, with our model expecting a comfortable victory over Collingwood. The model sees Hawthorn ahead on 3 of 7 key factors including Recent Win Rate, Forward Line ELO and Defensive ELO. Collingwood carry a 53-point ELO rating advantage (1718 vs 1666). Recent form favours Hawthorn with 3 wins from their last 5 compared to 2 for Collingwood. The margin model predicts Hawthorn by 6.1 points with a combined total of 165.
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 @2.30
Winner ✓
Edge
+43.7%
Line / Spread
Hawthorn +7.5 @1.91
Winner ✓
Edge
+43.7%
Total Points
Over 162.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Hawthorn | WWWLL | 83.4 |
Collingwood | WWLLL | 82.8 |
Avg Conceded
72.4
Hawthorn
71.2
Collingwood
Avg Margin
11.0
Hawthorn
11.6
Collingwood
Disposals
368.0
Hawthorn
356.8
Collingwood
Inside 50s
50.0
Hawthorn
50.0
Collingwood
📊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
87%
Hawthorn predicted to win by 6 points
Predicted total: 165 · Line: +6.1
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-1.24
Team Effectiveness
+0.27
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.