AI Game Review
Our model correctly predicted Carlton to win at 61% probability. The margin model missed here, predicting 21.2 but the actual margin was 82 points. The game's 224 points came in 60 points higher than the predicted 164. Carlton led 39–59 at the break and pulled away in the second half to win by 82. The model went 2/3 on this match. The 1-39 margin band call landed.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
North Melbourne
39%
Carlton
61%
AI Match Overview
Carlton hold the advantage at 61% win probability, though North Melbourne are far from out of this at 39%. The model sees Carlton ahead on 5 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Carlton carry a 117-point ELO rating advantage (1562 vs 1445). Recent form favours Carlton with 4 wins from their last 5 compared to 2 for North Melbourne. The margin model predicts Carlton by 21.2 points with a combined total of 164.
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 @1.40
Winner ✓
Edge
-10.1%
Line / Spread
Carlton +17.5 @1.91
Winner ✓
Edge
-10.1%
Total Points
Under 179.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
North Melbourne | W W L L L | 86.4 |
Carlton | W W W W L | 99.9 |
Avg Conceded
73.1
North Melbourne
96.4
Carlton
Avg Margin
-9.1
North Melbourne
10.8
Carlton
Disposals
337.4
North Melbourne
331.9
Carlton
Inside 50s
47.7
North Melbourne
56.1
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 21 points
Predicted total: 164 · Line: -21.2
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.19
Team Effectiveness
-0.19
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.