NRL | Round 21

alphr.com.au

SYD
Roosters
VS
MEL
Storm
ALLIANZ STADIUM, SYDNEY • THURSDAY 24 JULY, 7:50 PM

Win Probability

AI Game Review

Our model correctly predicted Storm to win at 65% probability. The margin model was sharp, predicting Storm by 6.6 vs the actual margin of 4 points. The game's 64 points came in 18 points higher than the predicted 46. Storm trailed 18–16 at half-time before staging a second-half comeback to win 30–34. The model went 2/3 on this match. The 1-12 margin band call landed.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Adam Gee officiated this match (295 career games). The combined score of 64 points was 21 points above Adam Gee's career average of 43. Despite Adam Gee's 57% career home-team win rate, the away side Storm prevailed. 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

Momentum Replay
Beta
80', Storm firmly in control (99%)
ROO30
1%80'99%
34STO
HT100%50%0%0'20'40'60'80'
Storm momentumMomentum -4Roosters momentum →
Next Try (within 10 min)
AI Model
86% none
ROO 8%No try 86%STO 6%
Biggest Swings

AI Win Probability

65%StormFavourite

Roosters

35%

Storm

65%

AI Match Overview

Storm are clear favourites here at 65%, with our model expecting a comfortable victory over Roosters. Roosters are stronger on paper across 4 of 7 key factors, including Forward Pack, Backline Quality and Referee Tendency, but Storm counter with ELO Difference and Halves Control which tips the scales. Storm carry a 160-point ELO rating advantage (1673 vs 1513). Recent form favours Storm with 4 wins from their last 5 compared to 3 for Roosters. The margin model predicts Storm by 6.6 points with a combined total of 46.

Generated from model features • Pre-kick-off analysis

Edge Analysis

2 ACTIVE EDGES

Each market is predicted by an independent model, H2H, margin, and totals may occasionally disagree.

H2H Recommendation

Storm to Win @1.50

Winner ✓

Edge

+3.2%

Line / Spread

Storm +6.5 @1.91

Winner ✓

Edge

+3.2%

Total Points

Under 46.5 @1.91

Lost ✗

Edge

-0.6%

Form & History

TeamLast 5Avg Pts
Roosters
W
W
W
L
L
26.2
Storm
W
W
W
W
L
25.8

Avg Conceded

20.2

Roosters

16.4

Storm

Avg Margin

6.0

Roosters

9.4

Storm

Run Metres

1675

Roosters

1852

Storm

Line Breaks

4.2

Roosters

3.8

Storm

Referee Indicator

Balanced

Adam Gee

295 career games · since 2013

AI Analysis

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

Roosters
26W – 14L
65%
Storm
30W – 14L
68%

Both sides have a similar record under Adam Gee, Roosters 26W–14L (65%) 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

Penalty & Discipline

Pen / Game

13.7

Sin Bins / Gm

0.24

SB Away %

69%

Avg Penalties Per Game

vs Home Teams6.3
vs Away Teams7.4

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Roosters
-1.4
Storm
+0.0

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. Storm get a +0.0 penalty advantage under Adam Gee vs Roosters's -1.4. 69% of his 36 career sin bins go to away teams.

H2H History (Last 5)Storm lead 4-1
Sep 2025SYD 40 - 10 MEL
Oct 2024SYD 18 - 48 MEL
Jul 2024SYD 8 - 24 MEL
Apr 2024SYD 12 - 18 MEL
Oct 2023SYD 13 - 18 MEL
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

SYD
1513Overall1673
MEL
ELO difference: -160 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

1092Forwards1059
Best: 1267SYD +33Best: 1222
1036Backs995
Best: 1101SYD +41Best: 1107
1158Halves1131
Best: 1158SYD +27Best: 1131
1062Hooker1108
MEL +46

📈Recent Form (Last 5)

SYD
Stat
MEL
3.0
Wins (Last 5)
4.0
26.2pts
Avg Score
25.8pts
20.2pts
Avg Conceded
16.4pts
6.0pts
Avg Margin
9.4pts
1675.2m
Run Metres
1852.0m
4.2
Line Breaks
3.8
383.8
Tackles
342.0
12.0
Errors
11.6

🔑Key Prediction Factors

What the model weighted most in this prediction

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

Model Confidence

65%

Storm predicted to win by 7 points

Predicted total: 46 · Line: -6.6

2/3 match predictions correct
Coming Soon

Try Scorer Predictions

AI-powered try scorer predictions and player prop markets, built on our 6-model player stats engine.

First / Anytime / Last ScorerPlayer Props