AI Game Review
Adelaide Crows defied the model's 60% prediction for Brisbane Lions, a notable upset. The margin model was sharp, predicting Adelaide Crows by 4.5 vs the actual margin of 5 points. Adelaide Crows trailed 25–33 at half-time before staging a second-half comeback to win 68–63. The model went 2/3 on this match. The 1-39 margin band call landed. The under 152.5 total call was correct.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
Adelaide Crows
40%
Brisbane Lions
60%
AI Match Overview
Brisbane Lions hold the advantage at 60% win probability, though Adelaide Crows are far from out of this at 40%. Both sides are evenly matched across the key prediction factors, which explains the tight margin between them. The margin model predicts Adelaide Crows by 4.5 points with a combined total of 146.
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
Brisbane Lions to Win @2.62
Lost ✗
Edge
+21.6%
Line / Spread
Adelaide Crows -10.5 @1.91
Winner ✓
Edge
+21.6%
Total Points
Under 152.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Adelaide Crows | W W L L L | 90.3 |
Brisbane Lions | W W L L L | 88.5 |
Avg Conceded
65.7
Adelaide Crows
65.8
Brisbane Lions
Avg Margin
-3.8
Adelaide Crows
-3.3
Brisbane Lions
Disposals
354.0
Adelaide Crows
331.9
Brisbane Lions
Inside 50s
54.6
Adelaide Crows
49.8
Brisbane Lions
📊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
60%
Brisbane Lions predicted to win by 5 points
Predicted total: 146 · Line: +4.5
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
+0.27
Team Effectiveness
-0.36
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.
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