AI Game Review
Our model correctly predicted Collingwood to win at 92% probability. The predicted margin of 36.0 was reasonable against the actual 41-point result. Total score prediction of 178 was close to the actual 173, within 5 points. Collingwood led 41–33 at the break and pulled away in the second half to win by 41. A clean sweep, all 3 model picks hit for this match.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
Collingwood
92%
Essendon
8%
AI Match Overview
Collingwood are clear favourites here at 92%, with our model expecting a comfortable victory over Essendon. The model sees Collingwood ahead on 5 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Collingwood carry a 49-point ELO rating advantage (1547 vs 1498). The margin model predicts Collingwood by 36.0 points with a combined total of 178.
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 @1.25
Winner ✓
Edge
+12.0%
Line / Spread
Collingwood -24.5 @1.91
Winner ✓
Edge
+12.0%
Total Points
Over 155.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Collingwood | W W L L L | 77.0 |
Essendon | W W L L L | 105.7 |
Avg Conceded
88.0
Collingwood
73.2
Essendon
Avg Margin
23.4
Collingwood
15.3
Essendon
Disposals
359.5
Collingwood
348.6
Essendon
Inside 50s
55.8
Collingwood
51.5
Essendon
📊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
92%
Collingwood predicted to win by 36 points
Predicted total: 178 · Line: +36.0
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.10
Team Effectiveness
+0.02
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.