AI Game Review
Our model correctly predicted Essendon to win at 67% probability. The predicted margin of 12.5 was reasonable against the actual 3-point result. The game's 127 points came in 30 points lower than the predicted 157. 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
Essendon
67%
North Melbourne
33%
AI Match Overview
Essendon are clear favourites here at 67%, with our model expecting a comfortable victory over North Melbourne. The model sees Essendon ahead on 6 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Essendon carry a 75-point ELO rating advantage (1510 vs 1436). Recent form favours North Melbourne with 4 wins from their last 5 compared to 3 for Essendon. The margin model predicts Essendon by 12.5 points with a combined total of 157.
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
Essendon to Win @1.33
Winner ✓
Edge
-8.1%
Line / Spread
Essendon -20.5 @1.91
Winner ✓
Edge
-8.1%
Total Points
Under 182.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Essendon | W W W L L | 96.7 |
North Melbourne | W W W W L | 108.3 |
Avg Conceded
86.7
Essendon
69.7
North Melbourne
Avg Margin
-8.4
Essendon
4.6
North Melbourne
Disposals
354.5
Essendon
340.4
North Melbourne
Inside 50s
51.9
Essendon
47.5
North Melbourne
📊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
67%
Essendon predicted to win by 13 points
Predicted total: 157 · Line: +12.5
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
0.00
Team Effectiveness
-0.04
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.