Win Probability
AI Game Review
Our model correctly predicted Storm to win at 73% probability. The margin model missed here — predicting 2.1 but the actual margin was 28 points. The game's 60 points came in 15 points higher than the predicted 45. The model went 5/16 on this match.
Model vs actual outcomes • Post-match analysis
AI Referee Insights
Adam Gee officiated this match (293 career games). The combined score of 60 points was 17 points above Adam Gee's career average of 43. Storm's victory aligns with Adam Gee's historical trend — Storm have a 67% win rate under this referee. Storm's home victory fits Adam Gee's profile — home teams win 57% of the time under this referee. Adam Gee averaged 13.7 penalties per game heading in — a whistle-heavy referee profile. 69% of his career sin bins go against away teams — a statistically significant away-team bias.
Based on referee career statistics • Post-match analysis
AI Win Probability
Storm
73%
Wests Tigers
27%
AI Match Overview
Storm are clear favourites here at 73%, with our model expecting a comfortable victory over Wests Tigers. Wests Tigers are stronger on paper across 5 of 7 key factors — including ELO Difference, Forward Pack and Backline Quality — but Storm counter with Referee Tendency and Venue Advantage which tips the scales. Wests Tigers carry a 86-point ELO rating advantage (1474 vs 1387). Recent form favours Wests Tigers with 3 wins from their last 5 compared to 0 for Storm. The margin model predicts Storm by 2.1 points with a combined total of 45.
Generated from model features • Pre-kick-off analysis
Edge Analysis
1 ACTIVE EDGEEach market is predicted by an independent model — H2H, margin, and totals may occasionally disagree.
H2H Recommendation
Storm to Win @1.62
Winner ✓
Edge
+14.2%
Line / Spread
Wests Tigers +4.5 @1.91
Lost ✗
Edge
+0.0%
Margin Band
Storm 1-12 @2.55
Lost ✗
Edge
+0.0%
Total Points
Under 55.5 @1.91
Lost ✗
Edge
+0.0%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Storm | R5L R6L R7L R8L R9L older → newer | 12.4 |
Wests Tigers | R5W R6W R7L R8W R9L | 25.4 |
Avg Conceded
38.0
Storm
25.8
Wests Tigers
Avg Margin
-25.6
Storm
-0.4
Wests Tigers
Run Metres
1371
Storm
1827
Wests Tigers
Line Breaks
2.8
Storm
5.8
Wests Tigers
Referee Indicator
Favours StormAdam Gee
293 career games · since 2012
Win rate when Adam Gee refs each team (vs any opponent)
When Adam Gee officiates, Storm have won 29 of 43 games (67%) — significantly stronger than Wests Tigers's 18 from 39 (46%). Home teams win 57% of his matches (vs ~52% league avg).
Avg Total
42.8 pts
Home Win %
57%
Home Bias
Leans home
Pen / Game
13.7
Sin Bins / Gm
0.24
SB Away %
69%
Avg Penalties Per Game
Penalty Advantage Under This Ref
Positive = opponent penalised more than your team
Adam Gee averages 13.7 penalties per game — above the league norm. Expect frequent stoppages. Penalises away teams more — 6.3 against home vs 7.4 against away. 69% of his 36 career sin bins go to away teams.
ELO–Market Disagreement
Wests Tigers hold the ELO advantage (1474 vs 1387), but the market favours Storm (@1.62).
The model sides with the market — other factors override the ELO gap.
📊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
73%
Storm predicted to win by 2 points
Predicted total: 45 · Line: +2.1
Anytime Try Scorer
Model probability vs Sportsbet overlay, ranked by edge.
First Try Scorer
Team-normalised first-try share using the current lineups and opposition defence profile.