AI Game Review
Hawthorn defied the model's 80% prediction for Adelaide Crows — a notable upset. The margin model missed here — predicting 10.7 but the actual margin was 34 points. Hawthorn led 24–43 at the break and pulled away in the second half to win by 34. The model went 1/3 on this match. The over 164.5 total call was correct.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
Adelaide Crows
80%
Hawthorn
20%
AI Match Overview
Adelaide Crows are clear favourites here at 80%, with our model expecting a comfortable victory over Hawthorn. The model sees Adelaide Crows ahead on 4 of 7 key factors including ELO Difference, Recent Win Rate and Forward Line ELO. Recent form favours Adelaide Crows with 4 wins from their last 5 compared to 3 for Hawthorn. The margin model predicts Adelaide Crows by 10.7 points with a combined total of 175.
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
Adelaide Crows to Win @1.75
Lost ✗
Edge
+23.0%
Line / Spread
Adelaide Crows -4.5 @1.91
Lost ✗
Edge
+23.0%
Total Points
Over 164.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Adelaide Crows | WWWWL | 83.0 |
Hawthorn | WWWLL | 95.0 |
Avg Conceded
80.0
Adelaide Crows
76.0
Hawthorn
Avg Margin
3.0
Adelaide Crows
19.0
Hawthorn
Disposals
322.8
Adelaide Crows
376.4
Hawthorn
Inside 50s
50.0
Adelaide Crows
50.0
Hawthorn
📊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
80%
Adelaide Crows predicted to win by 11 points
Predicted total: 175 · Line: +10.7
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.21
Team Effectiveness
+0.01
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.