NRL | Round 11

alphr.com.au

CRO
Sharks
VS
MEL
Storm
SHARKS STADIUM, SYDNEY • SATURDAY 17 MAY, 7:35 PM
🏁

AI Referee Insights

Adam Gee officiated this match (287 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.

Based on referee career statistics • Post-match analysis

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

Win Probability

AI Win Probability

60%StormFavourite

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 EDGE

Each 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

TeamLast 5Avg Pts
Sharks
WWWWL
26.8
Storm
WWWLL
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 IndicatorAI
Balanced record
Adam Gee287 games since 2013

Each team's win rate when Adam Gee refs their game (vs any opponent, all seasons)

CRO
71%29W 12L
MEL
71%29W 12L

Both sides have a similar record when Adam Gee officiates — Sharks 29W–12L (71%) and Storm 29W–12L (71%) across all their respective games. No significant bias detected. His games average 42.6 pts, sitting close to the league average. Home teams win 57% of his matches (vs ~52% league avg), which could give Sharks an additional edge at home.

Avg Total

42.6 pts

Home Win %

57%

Home Bias

Leans home

H2H History (Last 5)Storm lead 4-1
Oct 2025CRO 14 - 22 MEL
Jul 2025CRO 6 - 30 MEL
Sep 2024CRO 10 - 37 MEL
May 2024CRO 25 - 18 MEL
Jun 2023CRO 10 - 54 MEL
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

CRO
1580Overall1659
MEL
ELO difference: -79 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group — higher = stronger unit

1029Forwards1096
Best: 1266MEL +67Best: 1313
1011Backs1031
Best: 1138MEL +20Best: 1134
1294Halves1384
Best: 1294MEL +90Best: 1384
1024Hooker1088
MEL +64

📈Recent Form (Last 5)

CRO
Stat
MEL
4.0
Wins (Last 5)
3.0
26.8pts
Avg Score
34.0pts
16.8pts
Avg Conceded
18.4pts
10.0pts
Avg Margin
15.6pts
1772.0m
Run Metres
1739.4m
4.2
Line Breaks
6.4
324.2
Tackles
318.6
11.2
Errors
13.4

🔑Key Prediction Factors

What the model weighted most in this prediction

1
ELO Difference14.0%
Storm
2
Forward Pack12.0%
Storm
3
Backline Quality10.0%
Storm
4
Halves Control9.0%
Storm
5
Recent Win Rate9.0%
Sharks
6
Referee Tendency7.0%
Sharks
7
Venue Advantage7.0%

Model Confidence

60%

Storm predicted to win by 6 points

Predicted total: 44 · Line: -5.8

0/3 match predictions correct
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