AI Game Review
Richmond defied the model's 61% prediction for Carlton — a notable upset. The margin model was sharp — predicting Richmond by 9.8 vs the actual margin of 13 points. Richmond trailed 25–50 at half-time before staging a second-half comeback to win 82–69. The model went 2/3 on this match. The 1-39 margin band call landed. The under 177.5 total call was correct.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
Richmond
39%
Carlton
61%
AI Match Overview
Carlton hold the advantage at 61% win probability, though Richmond are far from out of this at 39%. The model sees Carlton ahead on 4 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Carlton carry a 264-point ELO rating advantage (1496 vs 1232). Recent form favours Carlton with 1 wins from their last 5 compared to 0 for Richmond. The margin model predicts Richmond by 9.8 points with a combined total of 158.
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
Carlton to Win @1.05
Lost ✗
Edge
-33.8%
Line / Spread
Richmond +48.5 @1.91
Winner ✓
Edge
-33.8%
Total Points
Under 177.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Richmond | LLLLL | 65.8 |
Carlton | WLLLL | 72.6 |
Avg Conceded
101.4
Richmond
81.0
Carlton
Avg Margin
-35.6
Richmond
-8.4
Carlton
Disposals
360.4
Richmond
371.2
Carlton
Inside 50s
50.0
Richmond
50.0
Carlton
📊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
61%
Carlton predicted to win by 10 points
Predicted total: 158 · Line: +9.8
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.49
Team Effectiveness
+0.06
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.