Win Probability
AI Game Review
Sharks defied the model's 60% prediction for Storm, a notable upset. The predicted margin of 5.8 was reasonable against the actual 5-point result. A tough result for the model, all 3 picks missed on this one.
Model vs actual outcomes • Post-match analysis
AI Referee Insights
Adam Gee officiated this match (295 career games). The combined score of 57 points was 14 points above Adam Gee's career average of 43. Sharks'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
Sharks
40%
Storm
60%
AI Match Overview
Storm hold the advantage at 60% win probability, though Sharks are far from out of this at 40%. The model sees Storm ahead on 4 of 7 key factors including ELO Difference, Forward Pack and Backline Quality. Storm carry a 79-point ELO rating advantage (1659 vs 1580). Recent form favours Sharks with 4 wins from their last 5 compared to 3 for Storm. The margin model predicts Storm by 5.8 points with a combined total of 44.
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 @1.60
Lost ✗
Edge
-6.9%
Line / Spread
Storm +3.5 @1.91
Lost ✗
Edge
-6.9%
Total Points
Under 46.5 @1.91
Lost ✗
Edge
+4.9%
Form & History
| Team | Last 5 | Avg Pts |
|---|---|---|
Sharks | W W W W L | 26.8 |
Storm | W W W L L | 34.0 |
Avg Conceded
16.8
Sharks
18.4
Storm
Avg Margin
10.0
Sharks
15.6
Storm
Run Metres
1772
Sharks
1739
Storm
Line Breaks
4.2
Sharks
6.4
Storm
Referee Indicator
BalancedAdam Gee
295 career games · since 2013
Win rate when Adam Gee refs each team (vs any opponent)
Both sides have a similar record under Adam Gee, Sharks 30W–12L (71%) and Storm 30W–14L (68%). 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. Sharks get a +0.8 penalty advantage under Adam Gee vs Storm's +0.0. 69% of his 36 career sin bins go to away teams.
📊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%
Storm predicted to win by 6 points
Predicted total: 44 · Line: -5.8
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