NRL | Round 5

Our model correctly predicted Panthers to win at 56% probability. The margin model missed here, predicting 4.6 but the actual margin was 40 points. The game's 60 points came in 18 points higher than the predicted 43. Panthers led 26–6 at the break and pulled away in the second half to win by 40. The model went 5/17 on this match.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Ashley Klein officiated this match (379 career games). The combined score of 60 points was 17 points above Ashley Klein's career average of 43. Panthers bucked the trend, Storm historically win 63% of games under Ashley Klein, but couldn't convert that edge today. Panthers's home victory fits Ashley Klein's profile, home teams win 60% of the time under this referee.

Based on referee career statistics • Post-match analysis

Momentum Replay

Beta

80', Panthers firmly in control (99%)

PAN50

99%80'1%

10STO

← Storm momentumMomentum +18Panthers momentum →

Next Try (within 10 min)

AI Model

84% none

PAN 11%No try 84%STO 5%

Biggest Swings

AI Win Probability

56%PanthersFavourite

Panthers

56%

Storm

44%

✨

AI Match Overview

Panthers hold the advantage at 56% win probability, though Storm are far from out of this at 44%. The model sees Panthers ahead on 7 of 7 key factors including ELO Difference, Forward Pack and Backline Quality. Panthers carry a 106-point ELO rating advantage (1694 vs 1588). Recent form favours Panthers with 4 wins from their last 5 compared to 3 for Storm. The margin model predicts Panthers by 4.6 points with a combined total of 43.

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

Panthers to Win @1.42

Winner ✓

Edge

-11.1%

✓

Line / Spread

Storm +8.5 @1.91

Lost ✗

Edge

+0.0%

✗

Margin Band

Panthers 1-12 @2.55

Lost ✗

Edge

+0.0%

✗

Total Points

Under 43.5 @1.91

Lost ✗

Edge

+0.0%

✗

Form & History

Team	Last 5	Avg Pts
Panthers	R2025-R30L R2026-R1W R2026-R2W R2026-R3W R2026-R4W older → newer	30.8
Storm	R2025-R30W R2026-R1W R2026-R2W R2026-R3L R2026-R4L	31.6

Avg Conceded

9.2

Panthers

16.8

Storm

Avg Margin

21.6

Panthers

14.8

Storm

Run Metres

1786

Panthers

1802

Storm

Line Breaks

4.8

Panthers

7.4

Storm

Referee Indicator

Favours Storm

Ashley Klein

379 career games · since 2012

AI Analysis

Win rate when Ashley Klein refs each team (vs any opponent)

Panthers

27W – 28L

49%

Storm

40W – 23L

63%

Storm hold a 14-point edge: 40W–23L (63%) vs Panthers's 27W–28L (49%). Home teams win 60% of his matches (vs ~52% league avg).

Avg Total

43.4 pts

Home Win %

60%

Home Bias

Leans home

Penalty & Discipline

Pen / Game

8.9

Sin Bins / Gm

0.16

SB Away %

42%

Avg Penalties Per Game

vs Home Teams4.3

vs Away Teams4.6

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Panthers

+0.0

Storm

-0.4

Ashley Klein averages just 8.9 penalties per game, well below average. He lets the game flow.

H2H History (Last 5)Storm lead 4-1

Aug 2025PEN 18 - 22 MEL

Mar 2025PEN 24 - 30 MEL

Aug 2024PEN 22 - 24 MEL

Mar 2024PEN 0 - 8 MEL

Oct 2023PEN 38 - 4 MEL

Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

PEN

1694Overall1588

MEL

ELO difference: +106 in favour of Panthers

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

1219Forwards1084

PEN +135

1160Backs1111

PEN +49

1161Halves1085

PEN +76

1167Hooker1125

PEN +42

📈Recent Form (Last 5)

PEN

Stat

MEL

4.0

Wins (Last 5)

3.0

30.8pts

Avg Score

31.6pts

9.2pts

Avg Conceded

16.8pts

21.6pts

Avg Margin

14.8pts

1785.8m

Run Metres

1802.0m

4.8

Line Breaks

7.4

323.0

Tackles

316.6

10.6

Errors

8.2

🔑Key Prediction Factors

What the model weighted most in this prediction

ELO Difference14.0%

Panthers

Forward Pack12.0%

Panthers

Backline Quality10.0%

Panthers

Halves Control9.0%

Panthers

Recent Win Rate9.0%

Panthers

Referee Tendency7.0%

Panthers

Venue Advantage7.0%

Panthers

Model Confidence

56%

Panthers predicted to win by 5 points

Predicted total: 43 · Line: +4.6

1/4 match predictions correct4/13 scorer picks correct

Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays

Paul AlamotiPanthers

backFair 1.332+ 40%

$2.45

+34.2% edge

Model

75%

Market

41%

Confidence

75%

Harry GrantStorm

hookerFair 2.572+ 9%

$4.10

+14.6% edge

Model

39%

Market

24%

Confidence

39%

Casey McLeanPanthers

backFair 1.682+ 23%

$2.12

+12.3% edge

Model

60%

Market

47%

Confidence

60%

Jahrome HughesStorm

halfFair 3.682+ 4%

$4.10

+2.7% edge

Model

27%

Market

24%

Confidence

27%

Will WarbrickStorm

backFair 2.022+ 15%

$2.03

+0.2% edge

Model

49%

Market

49%

Confidence

49%

Thomas JenkinsPanthers

backFair 1.782+ 20%

$1.54

-8.7% edge

Model

56%

Market

65%

Confidence

56%

Brian To'oPanthers

backFair 2.062+ 14%

$1.75

-8.7% edge

Model

48%

Market

57%

Confidence

48%

Dylan EdwardsPanthers

backFair 3.552+ 4%

$2.60

-10.3% edge

Model

28%

Market

38%

Confidence

28%

Scorer Markets

First Try Scorer

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

5 Plays

Paul AlamotiPanthers

backFair 4.122+ 40%

$12.00

+15.9% edge

Model

24%

Market

Confidence

24%

Will WarbrickStorm

backFair 5.492+ 15%

$10.00

+8.2% edge

Model

18%

Market

10%

Confidence

18%

Harry GrantStorm

hookerFair 7.582+ 9%

$18.00

+7.6% edge

Model

13%

Market

Confidence

13%

Casey McLeanPanthers

backFair 6.332+ 23%

$10.00

+5.8% edge

Model

16%

Market

10%

Confidence

16%

Jahrome HughesStorm

halfFair 11.812+ 4%

$20.00

+3.5% edge

Model

Market

Confidence