AI Game Review
GWS GIANTS defied the model's 55% prediction for Geelong Cats — a notable result. The margin model missed here — predicting 7.2 but the actual margin was 26 points. The game's 196 points came in 29 points higher than the predicted 167. GWS GIANTS led 47–41 at the break and pulled away in the second half to win by 26. A tough result for the model — all 3 picks missed on this one.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
GWS GIANTS
45%
Geelong Cats
55%
AI Match Overview
Geelong Cats hold the advantage at 55% win probability, though GWS GIANTS are far from out of this at 45%. Both sides are evenly matched across the key prediction factors, which explains the tight margin between them. Geelong Cats carry a 132-point ELO rating advantage (1713 vs 1581). The margin model predicts Geelong Cats by 7.2 points with a combined total of 167.
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 @1.72
Lost ✗
Edge
-3.1%
Line / Spread
Geelong Cats +5.5 @1.91
Lost ✗
Edge
-3.1%
Total Points
Under 179.5 @1.91
Lost ✗
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
GWS GIANTS | WWWWL | 90.8 |
Geelong Cats | WWWWL | 100.6 |
Avg Conceded
78.0
GWS GIANTS
62.0
Geelong Cats
Avg Margin
12.8
GWS GIANTS
38.6
Geelong Cats
Disposals
364.0
GWS GIANTS
361.6
Geelong Cats
Inside 50s
50.0
GWS GIANTS
50.0
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
55%
Geelong Cats predicted to win by 7 points
Predicted total: 167 · Line: -7.2
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.24
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.