AI Game Review
Our model correctly predicted Collingwood to win at 94% probability. The margin model missed here — predicting 30.1 but the actual margin was 51 points. Collingwood led 63–39 at the break and pulled away in the second half to win by 51. 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
Collingwood
94%
Hawthorn
6%
AI Match Overview
Collingwood are clear favourites here at 94%, with our model expecting a comfortable victory over Hawthorn. The model sees Collingwood ahead on 4 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Collingwood carry a 210-point ELO rating advantage (1801 vs 1591). Recent form favours Collingwood with 4 wins from their last 5 compared to 3 for Hawthorn. The margin model predicts Collingwood by 30.1 points with a combined total of 176.
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
Collingwood to Win @1.63
Winner ✓
Edge
+32.2%
Line / Spread
Collingwood -8.5 @1.91
Winner ✓
Edge
+32.2%
Total Points
Over 168.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Collingwood | WWWWL | 95.4 |
Hawthorn | WWWLL | 96.0 |
Avg Conceded
74.0
Collingwood
74.2
Hawthorn
Avg Margin
21.4
Collingwood
21.8
Hawthorn
Disposals
343.2
Collingwood
380.8
Hawthorn
Inside 50s
50.0
Collingwood
50.0
Hawthorn
📊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
94%
Collingwood predicted to win by 30 points
Predicted total: 176 · Line: +30.1
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.18
Team Effectiveness
+0.30
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.