NRL | Round 13

Our model correctly predicted Wests Tigers to win at 61% probability. The margin model was sharp, predicting Wests Tigers by 6.7 vs the actual margin of 6 points. The model went 10/17 on this match. The 1-12 margin band call landed. The under 48.5 total call was correct.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Peter Gough officiated this match (183 career games). The combined score of 38 points was 6 points below Peter Gough's career average of 44. 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', Wests Tigers firmly in control (99%)

WES22

99%80'1%

16BUL

← Bulldogs momentumMomentum -12Wests Tigers momentum →

Biggest Swings

AI Win Probability

61%Wests TigersFavourite

Wests Tigers

61%

Bulldogs

39%

✨

AI Match Overview

Wests Tigers hold the advantage at 61% win probability, though Bulldogs are far from out of this at 39%. The model sees Wests Tigers ahead on 6 of 7 key factors including ELO Difference, Forward Pack and Backline Quality. Wests Tigers carry a 63-point ELO rating advantage (1418 vs 1354). The margin model predicts Wests Tigers by 6.7 points with a combined total of 44.

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

Wests Tigers to Win @1.56

Winner ✓

Edge

+0.4%

✓

Line / Spread

Wests Tigers -4.5 @1.91

Winner ✓

Edge

+0.0%

✓

Margin Band

Wests Tigers 1-12 @2.55

Winner ✓

Edge

+0.0%

✓

Total Points

Under 48.5 @1.91

Winner ✓

Edge

+0.0%

✓

Form & History

Team	Last 5	Avg Pts
Wests Tigers	W L L L L	19.4
Bulldogs	W L L L L	16.4

Avg Conceded

35.4

Wests Tigers

32.4

Bulldogs

Avg Margin

-16.0

Wests Tigers

-16.0

Bulldogs

Run Metres

1640

Wests Tigers

1682

Bulldogs

Line Breaks

4.8

Wests Tigers

4.0

Bulldogs

Referee Indicator

Balanced

Peter Gough

183 career games · since 2012

AI Analysis

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

Wests Tigers

9W – 16L

36%

Bulldogs

10W – 19L

34%

Both sides have a similar record under Peter Gough, Wests Tigers 9W–16L (36%) and Bulldogs 10W–19L (34%).

Avg Total

44.2 pts

Home Win %

53%

Home Bias

Leans home

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

Wests Tigers

+2.0

Bulldogs

+1.2

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. Wests Tigers get a +2.0 penalty advantage under Peter Gough vs Bulldogs's +1.2. 64% of his 11 career sin bins go to away teams.

H2H History (Last 5)Bulldogs lead 3-2

Aug 2025WST 28 - 14 CBY

May 2024WST 14 - 22 CBY

Mar 2023WST 22 - 26 CBY

Jun 2022WST 12 - 36 CBY

May 2022WST 36 - 22 CBY

Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

WST

1418Overall1354

CBY

ELO difference: +63 in favour of Wests Tigers

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

921Forwards886

WST +34

937Backs822

WST +115

886Halves855

WST +31

940Hooker891

WST +50

📈Recent Form (Last 5)

WST

Stat

CBY

1.0

Wins (Last 5)

1.0

19.4pts

Avg Score

16.4pts

35.4pts

Avg Conceded

32.4pts

-16.0pts

Avg Margin

-16.0pts

1640.0m

Run Metres

1681.6m

4.8

Line Breaks

4.0

300.0

Tackles

300.0

12.0

Errors

12.0

🔑Key Prediction Factors

What the model weighted most in this prediction

ELO Difference14.0%

Tigers

Forward Pack12.0%

Tigers

Backline Quality10.0%

Tigers

Halves Control9.0%

Tigers

Recent Win Rate9.0%

—

Referee Tendency7.0%

Tigers

Venue Advantage7.0%

Tigers

Model Confidence

61%

Wests Tigers predicted to win by 7 points

Predicted total: 44 · Line: +6.7

4/4 match predictions correct6/13 scorer picks correct

Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays

Jacob KirazBulldogs

backFair 1.602+ 26%

$2.45

+21.8% edge

Model

63%

Market

41%

Confidence

63%

Jahream BulaWests Tigers

backFair 1.392+ 37%

$1.81

+16.9% edge

Model

72%

Market

55%

Confidence

72%

Faaletino TavanaWests Tigers

backFair 1.502+ 30%

$1.88

+13.4% edge

Model

67%

Market

53%

Confidence

67%

Lachlan GalvinBulldogs

halfFair 2.562+ 9%

$3.10

+6.8% edge

Model

39%

Market

32%

Confidence

39%

Jeral SkeltonWests Tigers

backFair 1.872+ 18%

$1.82

-1.5% edge

Model

53%

Market

55%

Confidence

53%

Jethro RinakamaBulldogs

backFair 2.662+ 8%

$2.05

-11.2% edge

Model

38%

Market

49%

Confidence

38%

Bronson XerriBulldogs

backFair 3.952+ 4%

$2.60

-13.2% edge

Model

25%

Market

38%

Confidence

25%

Sunia TuruvaWests Tigers

backFair 3.852+ 4%

$2.45

-14.8% edge

Model

26%

Market

41%

Confidence

26%

Scorer Markets

First Try Scorer

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

5 Plays

Jacob KirazBulldogs

backFair 4.482+ 26%

$13.00

+14.6% edge

Model

22%

Market

Confidence

22%

Jahream BulaWests Tigers

backFair 4.062+ 37%

$9.00

+13.5% edge

Model

25%

Market

11%

Confidence

25%

Faaletino TavanaWests Tigers

backFair 4.742+ 30%

$10.00

+11.1% edge

Model

21%

Market

10%

Confidence

21%

Lachlan GalvinBulldogs

halfFair 8.902+ 9%

$15.00

+4.6% edge

Model

11%

Market

Confidence

11%

Jeral SkeltonWests Tigers

backFair 6.812+ 18%

$9.50

+4.2% edge

Model

15%

Market

11%

Confidence

15%