NRL | Round 26

alphr.com.au

MEL
Storm
VS
SYD
Roosters
AAMI PARK, MELBOURNE • FRIDAY 29 AUG, 8:00 PM

Win Probability

AI Game Review

Roosters defied the model's 63% prediction for Storm, a notable upset. The margin model missed here, predicting 1.4 but the actual margin was 30 points. Roosters trailed 10–0 at half-time before staging a second-half comeback to win 10–40. A tough result for the model, all 3 picks missed on this one.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Todd Smith officiated this match (105 career games). The 50-point combined total was right in line with Todd Smith's career average of 46. Roosters bucked the trend, Storm historically win 69% of games under Todd Smith, but couldn't convert that edge today.

Based on referee career statistics • Post-match analysis

Momentum Replay
Beta
80', Roosters firmly in control (99%)
STO10
1%80'99%
40ROO
HT100%50%0%0'20'40'60'80'
Roosters momentumMomentum -51Storm momentum →
Next Try (within 10 min)
AI Model
79% none
14%
STO 7%No try 79%ROO 14%
Biggest Swings

AI Win Probability

63%StormFavourite

Storm

63%

Roosters

37%

AI Match Overview

Storm hold the advantage at 63% win probability, though Roosters are far from out of this at 37%. The model sees Storm ahead on 4 of 7 key factors including ELO Difference, Halves Control and Recent Win Rate. Storm carry a 169-point ELO rating advantage (1743 vs 1574). Recent form favours Storm with 5 wins from their last 5 compared to 3 for Roosters. The margin model predicts Storm by 1.4 points with a combined total of 41.

Generated from model features • Pre-kick-off analysis

Edge Analysis

3 ACTIVE EDGES

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

H2H Recommendation

Storm to Win @1.48

Lost ✗

Edge

+7.7%

Line / Spread

Storm -6.5 @1.91

Lost ✗

Edge

+7.7%

Total Points

Under 44.5 @1.91

Lost ✗

Edge

+7.8%

Form & History

TeamLast 5Avg Pts
Storm
W
W
W
W
W
22.8
Roosters
W
W
W
L
L
31.2

Avg Conceded

14.8

Storm

18.4

Roosters

Avg Margin

8.0

Storm

12.8

Roosters

Run Metres

1606

Storm

1473

Roosters

Line Breaks

3.2

Storm

3.8

Roosters

Referee Indicator

Favours Storm

Todd Smith

105 career games · since 2019

AI Analysis

Win rate when Todd Smith refs each team (vs any opponent)

Storm
9W – 4L
69%
Roosters
8W – 6L
57%

Storm hold a 12-point edge: 9W–4L (69%) vs Roosters's 8W–6L (57%). Games average 46.1 pts, above the league norm, suggesting a free-flowing style.

Avg Total

46.1 pts

Home Win %

53%

Home Bias

Leans home

Penalty & Discipline

Pen / Game

10.7

Sin Bins / Gm

0.50

SB Away %

52%

Avg Penalties Per Game

vs Home Teams5.3
vs Away Teams5.4

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Storm
+0.5
Roosters
+0.0
H2H History (Last 5)Storm lead 5-0
Aug 2025MEL 34 - 30 SYD
Oct 2024MEL 48 - 18 SYD
Jul 2024MEL 24 - 8 SYD
Apr 2024MEL 18 - 12 SYD
Oct 2023MEL 18 - 13 SYD
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

MEL
1743Overall1574
SYD
ELO difference: +169 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

954Forwards1063
Best: 1197SYD +109Best: 1202
856Backs1106
Best: 990SYD +249Best: 1188
1329Halves1052
Best: 1329MEL +278Best: 1052
690Hooker1161
SYD +471

📈Recent Form (Last 5)

MEL
Stat
SYD
5.0
Wins (Last 5)
3.0
22.8pts
Avg Score
31.2pts
14.8pts
Avg Conceded
18.4pts
8.0pts
Avg Margin
12.8pts
1606.0m
Run Metres
1473.4m
3.2
Line Breaks
3.8
351.2
Tackles
317.6
8.6
Errors
13.4

🔑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%
7
Venue Advantage7.0%
Storm

Model Confidence

63%

Storm predicted to win by 1 points

Predicted total: 41 · Line: +1.4

0/3 match predictions correct
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