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.