AI Game Review
Our model correctly predicted Collingwood to win at 95% probability. The margin model missed here, predicting 54.3 but the actual margin was 36 points. Collingwood led 28–48 at the break and pulled away in the second half to win by 36. 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
Richmond
5%
Collingwood
95%
AI Match Overview
Collingwood are clear favourites here at 95%, with our model expecting a comfortable victory over Richmond. The model sees Collingwood ahead on 5 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Collingwood carry a 42-point ELO rating advantage (1525 vs 1483). Recent form favours Richmond with 2 wins from their last 5 compared to 1 for Collingwood. The margin model predicts Collingwood by 54.3 points with a combined total of 143.
Generated from model features • Pre-kick-off analysis
Edge Analysis
Each market is predicted by an independent model, H2H, margin, and totals may occasionally disagree.
H2H Recommendation
Collingwood to Win @1.04
Winner ✓
Edge
-1.4%
Line / Spread
Collingwood +52.5 @1.91
Winner ✓
Edge
-1.4%
Total Points
Under 155.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Richmond | W W L L L | 95.4 |
Collingwood | W L L L L | 104.1 |
Avg Conceded
95.3
Richmond
98.9
Collingwood
Avg Margin
20.4
Richmond
20.4
Collingwood
Disposals
370.8
Richmond
367.2
Collingwood
Inside 50s
55.0
Richmond
50.1
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
95%
Collingwood predicted to win by 54 points
Predicted total: 143 · Line: -54.3
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.05
Team Effectiveness
+0.15
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.