AI Game Review
Our model correctly predicted Geelong Cats to win at 95% probability. The margin model missed here, predicting 54.5 but the actual margin was 101 points. The game's 199 points came in 42 points higher than the predicted 157. Geelong Cats led 22–76 at the break and pulled away in the second half to win by 101. The model went 2/3 on this match. The 40+ margin band call landed.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
North Melbourne
5%
Geelong Cats
95%
AI Match Overview
Geelong Cats are clear favourites here at 95%, with our model expecting a comfortable victory over North Melbourne. The model sees Geelong Cats ahead on 4 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Geelong Cats carry a 25-point ELO rating advantage (1494 vs 1469). The margin model predicts Geelong Cats by 54.5 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
Geelong Cats to Win @1.06
Winner ✓
Edge
+0.5%
Line / Spread
Geelong Cats +46.5 @1.91
Winner ✓
Edge
+0.5%
Total Points
Under 180.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
North Melbourne | W W L L L | 105.7 |
Geelong Cats | W W L L L | 85.8 |
Avg Conceded
82.3
North Melbourne
72.3
Geelong Cats
Avg Margin
-6.7
North Melbourne
-2.6
Geelong Cats
Disposals
368.6
North Melbourne
360.8
Geelong Cats
Inside 50s
50.5
North Melbourne
51.1
Geelong Cats
📊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
95%
Geelong Cats predicted to win by 54 points
Predicted total: 157 · Line: -54.5
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.01
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.