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NRL | Round 8

alphr.com.au

MEL
Storm
VS
SOU
Rabbitohs
AAMI PARK, MELBOURNE • SATURDAY 25 APR, 8:10 PM AEST

Win Probability

AI Game Review

Rabbitohs defied the model's 63% prediction for Storm, a notable upset. The margin model missed here, predicting 6.2 but the actual margin was 42 points. Rabbitohs led 0–24 at the break and pulled away in the second half to win by 42. The model went 3/17 on this match.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Adam Gee officiated this match (291 career games). The combined score of 54 points was 11 points above Adam Gee's career average of 43. Rabbitohs bucked the trend, Storm historically win 69% of games under Adam Gee, but couldn't convert that edge today. Despite Adam Gee's 57% career home-team win rate, the away side Rabbitohs prevailed. Adam Gee averaged 14 penalties per game heading in, a whistle-heavy referee profile.

Based on referee career statistics • Post-match analysis

Momentum Replay
Beta
80', Rabbitohs firmly in control (99%)
STO6
1%80'99%
48RAB
HT100%50%0%0'20'40'60'80'
Rabbitohs momentumMomentum -27Storm momentum →
Biggest Swings

AI Win Probability

63%StormFavourite

Storm

63%

Rabbitohs

37%

AI Match Overview

Storm hold the advantage at 63% win probability, though Rabbitohs are far from out of this at 37%. The model sees Storm ahead on 3 of 7 key factors including ELO Difference, Referee Tendency and Venue Advantage. Recent form favours Rabbitohs with 3 wins from their last 5 compared to 0 for Storm. The margin model predicts Storm by 6.2 points with a combined total of 47.

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 @1.64

Lost ✗

Edge

+5.4%

Line / Spread

Storm -2.5 @1.91

Lost ✗

Edge

+0.0%

Margin Band

Storm 1-12 @2.55

Lost ✗

Edge

+0.0%

Total Points

Under 50.5 @1.91

Lost ✗

Edge

+0.0%

Form & History

TeamLast 5Avg Pts
Storm
R2026-R3L
R2026-R4L
R2026-R5L
R2026-R6L
R2026-R7L

older → newer

16.8
Rabbitohs
R2026-R2L
R2026-R3W
R2026-R5W
R2026-R6L
R2026-R7W
26.8

Avg Conceded

32.0

Storm

22.8

Rabbitohs

Avg Margin

-15.2

Storm

4.0

Rabbitohs

Run Metres

1501

Storm

1674

Rabbitohs

Line Breaks

4.6

Storm

5.4

Rabbitohs

Referee Indicator

Favours Storm

Adam Gee

291 career games · since 2012

AI Analysis

Win rate when Adam Gee refs each team (vs any opponent)

Storm
29W – 13L
69%
Rabbitohs
14W – 17L
45%

When Adam Gee officiates, Storm have won 29 of 42 games (69%), significantly stronger than Rabbitohs's 14 from 31 (45%). Home teams win 57% of his matches (vs ~52% league avg).

Avg Total

42.7 pts

Home Win %

57%

Home Bias

Leans home

Penalty & Discipline

Pen / Game

14.0

Sin Bins / Gm

0.13

SB Away %

25%

Avg Penalties Per Game

vs Home Teams6.5
vs Away Teams7.6

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Storm
+1.3
Rabbitohs
-4.0

Adam Gee averages 14 penalties per game, above the league norm. Expect frequent stoppages. Penalises away teams more, 6.5 against home vs 7.6 against away. Storm get a +1.3 penalty advantage under Adam Gee vs Rabbitohs's -4.0.

H2H History (Last 5)Storm lead 4-1
Jun 2025MEL 25 - 24 SOU
Apr 2025MEL 24 - 16 SOU
Aug 2024MEL 28 - 16 SOU
Apr 2024MEL 54 - 20 SOU
May 2023MEL 12 - 28 SOU
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

MEL
1478Overall1474
SOU
ELO difference: +4 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

1008Forwards1011
Even
1016Backs945
MEL +71
1008Halves954
MEL +54
963Hooker1001
SOU +38

📈Recent Form (Last 5)

MEL
Stat
SOU
0.0
Wins (Last 5)
3.0
16.8pts
Avg Score
26.8pts
32.0pts
Avg Conceded
22.8pts
-15.2pts
Avg Margin
4.0pts
1500.8m
Run Metres
1673.6m
4.6
Line Breaks
5.4
348.0
Tackles
306.4
9.2
Errors
10.8

🔑Key Prediction Factors

What the model weighted most in this prediction

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

Model Confidence

63%

Storm predicted to win by 6 points

Predicted total: 47 · Line: +6.2

0/4 match predictions correct3/13 scorer picks correct
Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays
Latrell MitchellRabbitohs
backFair 1.212+ 53%
$1.83
+28.3% edge
Model
83%
Market
55%
Confidence
83%
Alex JohnstonRabbitohs
backFair 1.262+ 47%
$1.51
+12.9% edge
Model
79%
Market
66%
Confidence
79%
Jack WightonRabbitohs
backFair 2.622+ 8%
$3.70
+11.1% edge
Model
38%
Market
27%
Confidence
38%
Will WarbrickStorm
backFair 1.402+ 35%
$1.58
+8.0% edge
Model
71%
Market
63%
Confidence
71%
Campbell GrahamRabbitohs
backFair 2.192+ 13%
$1.93
-6.2% edge
Model
46%
Market
52%
Confidence
46%
Jack HowarthStorm
backFair 2.712+ 8%
$2.30
-6.5% edge
Model
37%
Market
43%
Confidence
37%
Nick MeaneyStorm
backFair 2.722+ 8%
$1.96
-14.3% edge
Model
37%
Market
51%
Confidence
37%
Manaia WaitereStorm
backFair 5.202+ 2%
$2.30
-24.2% edge
Model
19%
Market
43%
Confidence
19%
Scorer Markets

First Try Scorer

Team-normalised first-try share using the current lineups and opposition defence profile.

5 Plays
Latrell MitchellRabbitohs
backFair 4.032+ 53%
$10.00
+14.8% edge
Model
25%
Market
10%
Confidence
25%
Will WarbrickStorm
backFair 3.922+ 35%
$8.00
+13.0% edge
Model
26%
Market
13%
Confidence
26%
Alex JohnstonRabbitohs
backFair 4.552+ 47%
$7.50
+8.7% edge
Model
22%
Market
13%
Confidence
22%
Jack HowarthStorm
backFair 10.582+ 8%
$13.00
+1.8% edge
Model
9%
Market
8%
Confidence
9%
Jack WightonRabbitohs
backFair 14.882+ 8%
$19.00
+1.5% edge
Model
7%
Market
5%
Confidence
7%