AI Game Review
Our model correctly predicted Hawthorn to win at 81% probability. The predicted margin of 31.2 was reasonable against the actual 38-point result. The game's 136 points came in 22 points lower than the predicted 158. Hawthorn led 40–27 at the break and pulled away in the second half to win by 38. 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
Hawthorn
81%
Port Adelaide
19%
AI Match Overview
Hawthorn are clear favourites here at 81%, with our model expecting a comfortable victory over Port Adelaide. The model sees Hawthorn ahead on 6 of 7 key factors including ELO Difference, Midfield ELO and Recent Win Rate. Recent form favours Port Adelaide with 4 wins from their last 5 compared to 3 for Hawthorn. The margin model predicts Hawthorn by 31.2 points with a combined total of 158.
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
Hawthorn to Win @1.15
Winner ✓
Edge
-6.0%
Line / Spread
Hawthorn -32.5 @1.91
Winner ✓
Edge
-6.0%
Total Points
Over 150.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Hawthorn | W W W L L | 75.4 |
Port Adelaide | W W W W L | 70.0 |
Avg Conceded
66.1
Hawthorn
80.5
Port Adelaide
Avg Margin
-0.6
Hawthorn
10.9
Port Adelaide
Disposals
332.8
Hawthorn
338.0
Port Adelaide
Inside 50s
44.4
Hawthorn
42.3
Port Adelaide
📊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
81%
Hawthorn predicted to win by 31 points
Predicted total: 158 · Line: +31.2
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.66
Team Effectiveness
-0.43
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.