NRL | Round 6

alphr.com.au

MEL
Storm
VS
NZL
Warriors
AAMI PARK, MELBOURNE • SATURDAY 11 APR, 7:35 PM

Win Probability

AI Game Review

Warriors defied the model's 60% prediction for Storm, a notable upset. The margin model missed here, predicting 5.8 but the actual margin was 24 points. Warriors led 14–18 at the break and pulled away in the second half to win by 24. The model went 1/17 on this match. The 1-12 margin band call landed.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Grant Atkins officiated this match (313 career games). The combined score of 52 points was 9 points above Grant Atkins's career average of 43. Warriors bucked the trend, Storm historically win 67% of games under Grant Atkins, but couldn't convert that edge today. Grant Atkins averaged 14.4 penalties per game heading in, a whistle-heavy referee profile.

Based on referee career statistics • Post-match analysis

Momentum Replay
Beta
80', Warriors firmly in control (99%)
STO14
1%80'99%
38WAR
HT100%50%0%0'20'40'60'80'
Warriors momentumMomentum -4Storm momentum →
Next Try (within 10 min)
AI Model
87% none
STO 7%No try 87%WAR 6%
Biggest Swings

AI Win Probability

60%StormFavourite

Storm

60%

Warriors

40%

AI Match Overview

Storm hold the advantage at 60% win probability, though Warriors are far from out of this at 40%. The model sees Storm ahead on 6 of 7 key factors including ELO Difference, Forward Pack and Backline Quality. Storm carry a 49-point ELO rating advantage (1552 vs 1502). Recent form favours Warriors with 3 wins from their last 5 compared to 2 for Storm. The margin model predicts Storm by 5.8 points with a combined total of 46.

Generated from model features • Pre-kick-off analysis

Edge Analysis

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

H2H Recommendation

Storm to Win @1.36

Lost ✗

Edge

-9.9%

Line / Spread

Warriors +9.5 @1.91

Winner ✓

Edge

+0.0%

Margin Band

Storm 1-12 @2.55

Lost ✗

Edge

+0.0%

Total Points

Under 47.5 @1.91

Lost ✗

Edge

+0.0%

Form & History

TeamLast 5Avg Pts
Storm
R2026-R1W
R2026-R2W
R2026-R3L
R2026-R4L
R2026-R5L

older → newer

29.2
Warriors
R2026-R1W
R2026-R2W
R2026-R3W
R2026-R4L
R2026-R5L
31.2

Avg Conceded

24.0

Storm

20.8

Warriors

Avg Margin

5.2

Storm

10.4

Warriors

Run Metres

1688

Storm

1701

Warriors

Line Breaks

7.0

Storm

4.6

Warriors

Referee Indicator

Favours Storm

Grant Atkins

313 career games · since 2012

AI Analysis

Win rate when Grant Atkins refs each team (vs any opponent)

Storm
34W – 17L
67%
Warriors
12W – 18L
40%

When Grant Atkins officiates, Storm have won 34 of 51 games (67%), significantly stronger than Warriors's 12 from 30 (40%).

Avg Total

42.9 pts

Home Win %

55%

Home Bias

Leans home

Penalty & Discipline

Pen / Game

14.4

Sin Bins / Gm

0.29

SB Away %

56%

Avg Penalties Per Game

vs Home Teams6.8
vs Away Teams7.6

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Storm
+0.9
Warriors
-0.1

Grant Atkins averages 14.4 penalties per game, above the league norm. Expect frequent stoppages. Penalises away teams more, 6.8 against home vs 7.6 against away. Storm get a +0.9 penalty advantage under Grant Atkins vs Warriors's -0.1.

H2H History (Last 5)Storm lead 5-0
Apr 2025MEL 42 - 14 NZL
Jun 2024MEL 38 - 24 NZL
Mar 2024MEL 30 - 26 NZL
Apr 2023MEL 30 - 22 NZL
Jul 2022MEL 24 - 12 NZL
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

MEL
1552Overall1502
NZL
ELO difference: +49 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

1022Forwards994
MEL +28
1018Backs1009
Even
1047Halves1036
MEL +11
1074Hooker1022
MEL +52

📈Recent Form (Last 5)

MEL
Stat
NZL
2.0
Wins (Last 5)
3.0
29.2pts
Avg Score
31.2pts
24.0pts
Avg Conceded
20.8pts
5.2pts
Avg Margin
10.4pts
1688.4m
Run Metres
1700.6m
7.0
Line Breaks
4.6
329.8
Tackles
310.6
7.8
Errors
10.2

🔑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%
Warriors
6
Referee Tendency7.0%
Storm
7
Venue Advantage7.0%
Storm

Model Confidence

60%

Storm predicted to win by 6 points

Predicted total: 46 · Line: +5.8

1/4 match predictions correct0/13 scorer picks correct
Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays
Adam Pompey
backFair 2.312+ 11%
$4.25
+19.8% edge
Model
43%
Market
24%
Confidence
43%
Harry GrantStorm
hookerFair 2.032+ 15%
$2.85
+14.2% edge
Model
49%
Market
35%
Confidence
49%
Tyran WishartStorm
benchFair 3.792+ 4%
$4.90
+6.0% edge
Model
26%
Market
20%
Confidence
26%
Chanel Harris-TavitaWarriors
halfFair 3.762+ 4%
$4.50
+4.4% edge
Model
27%
Market
22%
Confidence
27%
Leka HalasimaWarriors
forwardFair 2.482+ 10%
$2.65
+2.6% edge
Model
40%
Market
38%
Confidence
40%
Josh KingStorm
forwardFair 7.902+ 1%
$9.50
+2.1% edge
Model
13%
Market
11%
Confidence
13%
Jahrome HughesStorm
halfFair 2.832+ 7%
$2.95
+1.4% edge
Model
35%
Market
34%
Confidence
35%
Trent LoieroStorm
forwardFair 8.312+ 1%
$9.25
+1.2% edge
Model
12%
Market
11%
Confidence
12%
Scorer Markets

First Try Scorer

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

5 Plays
Adam Pompey
backFair 5.952+ 11%
$20.00
+11.8% edge
Model
17%
Market
5%
Confidence
17%
Roger Tuivasa-SheckWarriors
backFair 6.292+ 10%
$13.00
+8.2% edge
Model
16%
Market
8%
Confidence
16%
Leka HalasimaWarriors
forwardFair 6.562+ 10%
$13.00
+7.6% edge
Model
15%
Market
8%
Confidence
15%
Harry GrantStorm
hookerFair 7.762+ 15%
$13.00
+5.2% edge
Model
13%
Market
8%
Confidence
13%
Will WarbrickStorm
backFair 5.922+ 22%
$8.00
+4.4% edge
Model
17%
Market
13%
Confidence
17%