NRL | Round 5

alphr.com.au

Sun 5 Apr2:00pm

CROCRO

NZLNZL

CRO

Sharks

NZL

Warriors

OCEAN PROTECT STADIUM, SYDNEY • SUNDAY 5 APR, 2:00 PM

Win Probability

AI Game Review

Our model correctly predicted Sharks to win at 60% probability. The predicted margin of 4.0 was reasonable against the actual 14-point result. The model went 4/17 on this match.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Ziggy Przeklasa-Adamski officiated this match (72 career games). The combined score of 58 points was 17 points above Ziggy Przeklasa-Adamski's career average of 41. Sharks's victory aligns with Ziggy Przeklasa-Adamski's historical trend, Sharks have a 58% win rate under this referee. Ziggy Przeklasa-Adamski averaged 13.5 penalties per game heading in, a whistle-heavy referee profile. 70% 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', Sharks firmly in control (99%)

SHA36

99%80'1%

22WAR

← Warriors momentumMomentum -15Sharks momentum →

Next Try (within 10 min)

AI Model

85% none

SHA 7%No try 85%WAR 8%

Biggest Swings

AI Win Probability

60%SharksFavourite

Sharks

60%

Warriors

40%

✨

AI Match Overview

Sharks hold the advantage at 60% win probability, though Warriors are far from out of this at 40%. The model sees Sharks ahead on 6 of 7 key factors including ELO Difference, Forward Pack and Backline Quality. Recent form favours Warriors with 3 wins from their last 5 compared to 2 for Sharks. The margin model predicts Sharks by 4.0 points with a combined total of 47.

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

Sharks to Win @1.57

Winner ✓

Edge

-0.9%

✓

Line / Spread

Warriors +4.5 @1.91

Lost ✗

Edge

+0.0%

✗

Margin Band

Sharks 1-12 @2.55

Lost ✗

Edge

+0.0%

✗

Total Points

Under 47.5 @1.91

Lost ✗

Edge

+0.0%

✗

Form & History

Team	Last 5	Avg Pts
Sharks	R2025-R30L R2026-R1W R2026-R2L R2026-R3L R2026-R4W older → newer	22.8
Warriors	R2025-R28L R2026-R1W R2026-R2W R2026-R3W R2026-R4L	28.4

Avg Conceded

23.6

Sharks

18.4

Warriors

Avg Margin

-0.8

Sharks

10.0

Warriors

Run Metres

1575

Sharks

1649

Warriors

Line Breaks

4.2

Sharks

4.6

Warriors

Referee Indicator

Favours Sharks

Ziggy Przeklasa-Adamski

72 career games · since 2012

AI Analysis

Win rate when Ziggy Przeklasa-Adamski refs each team (vs any opponent)

Sharks

7W – 5L

58%

Warriors

5W – 5L

50%

Sharks hold a 8-point edge: 7W–5L (58%) vs Warriors's 5W–5L (50%). Away teams perform well, home sides win just 44%, below ~52% league avg.

Avg Total

41.1 pts

Home Win %

44%

Home Bias

Leans away

Penalty & Discipline

Pen / Game

13.5

Sin Bins / Gm

0.49

SB Away %

70%

Avg Penalties Per Game

vs Home Teams6.4

vs Away Teams7.1

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Sharks

+0.1

Warriors

+0.6

Ziggy Przeklasa-Adamski averages 13.5 penalties per game, above the league norm. Expect frequent stoppages. Penalises away teams more, 6.4 against home vs 7.1 against away. Warriors get a +0.6 penalty advantage under Ziggy Przeklasa-Adamski vs Sharks's +0.1. 70% of his 37 career sin bins go to away teams.

H2H History (Last 5)Warriors lead 4-1

Jun 2025CRO 10 - 40 NZL

Sep 2024CRO 28 - 30 NZL

Mar 2024CRO 16 - 12 NZL

Jul 2023CRO 12 - 44 NZL

Apr 2023CRO 30 - 32 NZL

Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

CRO

1539Overall1533

NZL

ELO difference: +6 in favour of Sharks

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

1013Forwards998

CRO +14

1062Backs1036

CRO +27

1045Halves1025

CRO +21

1032Hooker1016

CRO +16

📈Recent Form (Last 5)

CRO

Stat

NZL

2.0

Wins (Last 5)

3.0

22.8pts

Avg Score

28.4pts

23.6pts

Avg Conceded

18.4pts

-0.8pts

Avg Margin

10.0pts

1574.6m

Run Metres

1649.2m

4.2

Line Breaks

4.6

356.6

Tackles

331.2

10.0

Errors

11.0

🔑Key Prediction Factors

What the model weighted most in this prediction

ELO Difference14.0%

Sharks

Forward Pack12.0%

Sharks

Backline Quality10.0%

Sharks

Halves Control9.0%

Sharks

Recent Win Rate9.0%

Warriors

Referee Tendency7.0%

Sharks

Venue Advantage7.0%

Sharks

Model Confidence

60%

Sharks predicted to win by 4 points

Predicted total: 47 · Line: +4.0

1/4 match predictions correct3/13 scorer picks correct

Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays

Jesse RamienSharks

backFair 2.562+ 9%

$2.40

-2.7% edge

Model

39%

Market

42%

Confidence

39%

KL IroSharks

backFair 2.272+ 12%

$2.05

-4.7% edge

Model

44%

Market

49%

Confidence

44%

Leka HalasimaWarriors

forwardFair 2.602+ 9%

$2.30

-5.1% edge

Model

38%

Market

43%

Confidence

38%

Sione KatoaSharks

backFair 2.182+ 13%

$1.74

-11.5% edge

Model

46%

Market

57%

Confidence

46%

Roger Tuivasa-SheckWarriors

backFair 3.062+ 6%

$2.20

-12.7% edge

Model

33%

Market

45%

Confidence

33%

Charnze Nicoll-KlokstadWarriors

backFair 5.552+ 2%

$3.10

-14.2% edge

Model

18%

Market

32%

Confidence

18%

William KennedySharks

backFair 4.672+ 2%

$2.75

-14.9% edge

Model

21%

Market

36%

Confidence

21%

Dallin Watene-ZelezniakWarriors

backFair 4.142+ 3%

$2.03

-25.1% edge

Model

24%

Market

49%

Confidence

24%

Scorer Markets

First Try Scorer

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

5 Plays

Leka HalasimaWarriors

forwardFair 7.592+ 9%

$12.00

+4.8% edge

Model

13%

Market

Confidence

13%

Roger Tuivasa-SheckWarriors

backFair 9.282+ 6%

$12.00

+2.5% edge

Model

11%

Market

Confidence

11%

Jesse RamienSharks

backFair 12.692+ 9%

$13.00

+0.2% edge

Model

Market

Confidence

KL IroSharks

backFair 10.812+ 12%

$10.00

-0.8% edge

Model

Market

10%

Confidence

Charnze Nicoll-KlokstadWarriors

backFair 18.482+ 2%

$15.00

-1.3% edge

Model

Market

Confidence