AI Game Review
North Melbourne defied the model's 79% prediction for Richmond, a notable upset. The predicted margin of 3.0 was reasonable against the actual 4-point result. The model went 1/3 on this match. The under 171.5 total call was correct.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
Richmond
79%
North Melbourne
21%
AI Match Overview
Richmond are clear favourites here at 79%, with our model expecting a comfortable victory over North Melbourne. The model sees Richmond ahead on 6 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Richmond carry a 63-point ELO rating advantage (1475 vs 1412). The margin model predicts Richmond by 3.0 points with a combined total of 161.
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
Richmond to Win @2.50
Lost ✗
Edge
+38.6%
Line / Spread
Richmond +10.5 @1.91
Lost ✗
Edge
+38.6%
Total Points
Under 171.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Richmond | W W W L L | 107.8 |
North Melbourne | W W W L L | 100.9 |
Avg Conceded
88.8
Richmond
86.2
North Melbourne
Avg Margin
16.0
Richmond
8.0
North Melbourne
Disposals
349.4
Richmond
362.3
North Melbourne
Inside 50s
46.2
Richmond
44.9
North Melbourne
ELO–Market Disagreement
Richmond hold the ELO advantage (1475 vs 1412), but the market favours North Melbourne (@1.67).
The model sides with ELO, Richmond predicted to win despite longer odds.
📊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
79%
Richmond predicted to win by 3 points
Predicted total: 161 · Line: +3.0
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.28
Team Effectiveness
+0.20
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.