AI Game Review
Our model correctly predicted Port Adelaide to win at 95% probability. The margin model missed here — predicting 52.2 but the actual margin was 9 points. 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
Port Adelaide
95%
North Melbourne
5%
AI Match Overview
Port Adelaide are clear favourites here at 95%, with our model expecting a comfortable victory over North Melbourne. The model sees Port Adelaide ahead on 6 of 7 key factors including ELO Difference, Recent Win Rate and Forward Line ELO. Port Adelaide carry a 321-point ELO rating advantage (1531 vs 1209). Recent form favours Port Adelaide with 3 wins from their last 5 compared to 1 for North Melbourne. The margin model predicts Port Adelaide by 52.2 points with a combined total of 174.
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
Port Adelaide to Win @1.11
Winner ✓
Edge
+5.0%
Line / Spread
Port Adelaide -40.5 @1.91
Winner ✓
Edge
+5.0%
Total Points
Under 183.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Port Adelaide | WWWLL | 95.6 |
North Melbourne | WLLLL | 83.0 |
Avg Conceded
79.4
Port Adelaide
118.2
North Melbourne
Avg Margin
16.2
Port Adelaide
-35.2
North Melbourne
Disposals
377.4
Port Adelaide
376.4
North Melbourne
Inside 50s
50.0
Port Adelaide
50.0
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
95%
Port Adelaide predicted to win by 52 points
Predicted total: 174 · Line: +52.2
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.01
Team Effectiveness
-0.02
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.