NRL | Round 7

Raiders defied the model's 54% prediction for Storm, a notable result. The predicted margin of 3.9 was reasonable against the actual 4-point result. Total score prediction of 50 was close to the actual 48, within 2 points. Raiders trailed 12–16 at half-time before staging a second-half comeback to win 26–22. The model went 4/17 on this match.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Peter Gough officiated this match (178 career games). The 48-point combined total was right in line with Peter Gough's career average of 44. Raiders bucked the trend, Storm historically win 75% of games under Peter Gough, but couldn't convert that edge today. Peter Gough averaged 14.1 penalties per game heading in, a whistle-heavy referee profile. 64% 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', Raiders firmly in control (99%)

RAI26

99%80'1%

22STO

← Storm momentumMomentum -1Raiders momentum →

Next Try (within 10 min)

AI Model

87% none

RAI 6%No try 87%STO 7%

Biggest Swings

AI Win Probability

54%StormFavourite

Raiders

46%

Storm

54%

✨

AI Match Overview

Storm hold the advantage at 54% win probability, though Raiders are far from out of this at 46%. The model sees Storm ahead on 4 of 7 key factors including ELO Difference, Forward Pack and Backline Quality. Storm carry a 73-point ELO rating advantage (1506 vs 1433). The margin model predicts Storm by 3.9 points with a combined total of 50.

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 @1.75

Lost ✗

Edge

-0.8%

✗

Line / Spread

Storm -2.5 @1.91

Lost ✗

Edge

+0.0%

✗

Margin Band

Storm 1-12 @2.55

Lost ✗

Edge

+0.0%

✗

Total Points

Over 48.5 @1.91

Lost ✗

Edge

+0.0%

✗

Form & History

Team	Last 5	Avg Pts
Raiders	R2026-R2L R2026-R3L R2026-R4L R2026-R5L R2026-R6W older → newer	17.2
Storm	R2026-R2W R2026-R3L R2026-R4L R2026-R5L R2026-R6L	21.6

Avg Conceded

30.8

Raiders

30.8

Storm

Avg Margin

-13.6

Raiders

-9.2

Storm

Run Metres

1647

Raiders

1501

Storm

Line Breaks

4.2

Raiders

5.0

Storm

Referee Indicator

Favours Storm

Peter Gough

178 career games · since 2012

AI Analysis

Win rate when Peter Gough refs each team (vs any opponent)

Raiders

8W – 9L

47%

Storm

12W – 4L

75%

When Peter Gough officiates, Storm have won 12 of 16 games (75%), significantly stronger than Raiders's 8 from 17 (47%).

Avg Total

44.2 pts

Home Win %

53%

Home Bias

Neutral

Penalty & Discipline

Pen / Game

14.1

Sin Bins / Gm

0.37

SB Away %

64%

Avg Penalties Per Game

vs Home Teams6.7

vs Away Teams7.4

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Raiders

+0.5

Storm

+0.0

Peter Gough averages 14.1 penalties per game, above the league norm. Expect frequent stoppages. Penalises away teams more, 6.7 against home vs 7.4 against away. Raiders get a +0.5 penalty advantage under Peter Gough vs Storm's +0.0. 64% of his 11 career sin bins go to away teams.

H2H History (Last 5)Raiders lead 3-2

May 2025CAN 20 - 18 MEL

Jul 2024CAN 6 - 16 MEL

Aug 2023CAN 2 - 48 MEL

Sep 2022CAN 28 - 20 MEL

Jul 2022CAN 20 - 16 MEL

Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

CAN

1433Overall1506

MEL

ELO difference: -73 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

966Forwards987

MEL +21

944Backs1025

MEL +81

920Halves967

MEL +47

914Hooker1014

MEL +100

📈Recent Form (Last 5)

CAN

Stat

MEL

1.0

Wins (Last 5)

1.0

17.2pts

Avg Score

21.6pts

30.8pts

Avg Conceded

30.8pts

-13.6pts

Avg Margin

-9.2pts

1647.2m

Run Metres

1501.2m

4.2

Line Breaks

5.0

369.6

Tackles

343.2

11.8

Errors

8.0

🔑Key Prediction Factors

What the model weighted most in this prediction

ELO Difference14.0%

Storm

Forward Pack12.0%

Storm

Backline Quality10.0%

Storm

Halves Control9.0%

Storm

Recent Win Rate9.0%

—

Referee Tendency7.0%

Raiders

Venue Advantage7.0%

Raiders

Model Confidence

54%

Storm predicted to win by 4 points

Predicted total: 50 · Line: -3.9

0/4 match predictions correct4/13 scorer picks correct

Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays

Will WarbrickStorm

backFair 1.482+ 31%

$1.75

+10.3% edge

Model

67%

Market

57%

Confidence

67%

Jack HowarthStorm

backFair 2.802+ 7%

$2.85

+0.6% edge

Model

36%

Market

35%

Confidence

36%

Nick MeaneyStorm

backFair 3.342+ 5%

$2.65

-7.8% edge

Model

30%

Market

38%

Confidence

30%

Kaeo WeekesRaiders

backFair 2.662+ 8%

$2.20

-7.9% edge

Model

38%

Market

45%

Confidence

38%

Simi SasagiRaiders

backFair 3.882+ 4%

$2.55

-13.5% edge

Model

26%

Market

39%

Confidence

26%

Hudson YoungRaiders

forwardFair 7.592+ 1%

$2.85

-21.9% edge

Model

13%

Market

35%

Confidence

13%

Jed StuartRaiders

backFair 4.202+ 3%

$2.12

-23.4% edge

Model

24%

Market

47%

Confidence

24%

Sebastian KrisRaiders

backFair 5.962+ 2%

$2.12

-30.4% edge

Model

17%

Market

47%

Confidence

17%

Scorer Markets

First Try Scorer

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

5 Plays

Will WarbrickStorm

backFair 5.272+ 31%

$8.50

+7.2% edge

Model

19%

Market

12%

Confidence

19%

Kaeo WeekesRaiders

backFair 7.752+ 8%

$12.00

+4.6% edge

Model

13%

Market

Confidence

13%

Simi SasagiRaiders

backFair 12.252+ 4%

$13.00

+0.5% edge

Model

Market

Confidence

Jack HowarthStorm

backFair 13.402+ 7%

$14.00

+0.3% edge

Model

Market

Confidence

Jed StuartRaiders

backFair 13.442+ 3%

$12.00

-0.9% edge

Model

Market

Confidence