AI Game Review
Our model correctly predicted North Melbourne to win at 90% probability. The predicted margin of 37.2 was reasonable against the actual 48-point result. The game's 222 points came in 47 points higher than the predicted 176. North Melbourne led 47–39 at the break and pulled away in the second half to win by 48. 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
North Melbourne
90%
Richmond
10%
AI Match Overview
North Melbourne are clear favourites here at 90%, with our model expecting a comfortable victory over Richmond. The model sees North Melbourne ahead on 6 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Recent form favours Richmond with 4 wins from their last 5 compared to 3 for North Melbourne. The margin model predicts North Melbourne by 37.2 points with a combined total of 176.
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
North Melbourne to Win @1.72
Winner ✓
Edge
+31.7%
Line / Spread
North Melbourne -5.5 @1.91
Winner ✓
Edge
+31.7%
Total Points
Over 164.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
North Melbourne | W W W L L | 106.4 |
Richmond | W W W W L | 72.1 |
Avg Conceded
65.3
North Melbourne
90.8
Richmond
Avg Margin
6.0
North Melbourne
-7.4
Richmond
Disposals
363.1
North Melbourne
361.9
Richmond
Inside 50s
57.2
North Melbourne
48.9
Richmond
📊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
90%
North Melbourne predicted to win by 37 points
Predicted total: 176 · Line: +37.2
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.18
Team Effectiveness
+0.32
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.