AI Game Review
Our model correctly predicted GWS GIANTS to win at 63% probability. The margin model missed here — predicting 3.4 but the actual margin was 59 points. GWS GIANTS led 19–54 at the break and pulled away in the second half to win by 59. A clean sweep — all 3 model picks hit for this match.
Model vs actual outcomes • Post-match analysis
Quarter-by-Quarter Win Probability
AI Win Probability
West Coast Eagles
37%
GWS GIANTS
63%
AI Match Overview
GWS GIANTS hold the advantage at 63% win probability, though West Coast Eagles are far from out of this at 37%. Both sides are evenly matched across the key prediction factors, which explains the tight margin between them. Recent form favours GWS GIANTS with 4 wins from their last 5 compared to 3 for West Coast Eagles. The margin model predicts GWS GIANTS by 3.4 points with a combined total of 152.
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
GWS GIANTS to Win @1.36
Winner ✓
Edge
-10.9%
Line / Spread
GWS GIANTS +18.5 @1.91
Winner ✓
Edge
-10.9%
Total Points
Under 167.5 @1.91
Winner ✓
Edge
+2.6%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
West Coast Eagles | WWWLL | 89.9 |
GWS GIANTS | WWWWL | 83.8 |
Avg Conceded
78.1
West Coast Eagles
98.0
GWS GIANTS
Avg Margin
6.0
West Coast Eagles
24.5
GWS GIANTS
Disposals
369.8
West Coast Eagles
377.1
GWS GIANTS
Inside 50s
48.6
West Coast Eagles
44.0
GWS GIANTS
📊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
63%
GWS GIANTS predicted to win by 3 points
Predicted total: 152 · Line: -3.4
Player Work Effort
Per-minute effort vs effectiveness (vs personal average)Team Effort
-0.04
Team Effectiveness
-0.08
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.