NRL | Round 4

alphr.com.au

SGI
Dragons
VS
MEL
Storm
JUBILEE STADIUM, SYDNEY • SATURDAY 29 MAR, 3:00 PM
🏁

AI Referee Insights

Peter Gough officiated this match (176 career games). The combined score of 22 points was 22 points below Peter Gough's career average of 44. Dragons bucked the trend — Storm historically win 80% of games under Peter Gough, but couldn't convert that edge today.

Based on referee career statistics • Post-match analysis

AI Game Review

Dragons defied the model's 52% prediction for Storm — a notable result. The predicted margin of 4.2 was reasonable against the actual 6-point result. The game's 22 points came in 24 points lower than the predicted 46. Dragons trailed 6–8 at half-time before staging a second-half comeback to win 14–8. A tough result for the model — all 3 picks missed on this one.

Model vs actual outcomes • Post-match analysis

Win Probability

AI Win Probability

52%StormFavourite

Dragons

48%

Storm

52%

AI Match Overview

This shapes up as one of the tightest matchups of the round. Our model gives Storm a marginal 52% edge, making this essentially a coin-flip contest. Both sides are evenly matched across the key prediction factors, which explains the tight margin between them. Storm carry a 310-point ELO rating advantage (1698 vs 1388). Recent form favours Storm with 5 wins from their last 5 compared to 0 for Dragons. The margin model predicts Storm by 4.2 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 @1.42

Lost ✗

Edge

-21.6%

Line / Spread

Storm +7.5 @1.91

Lost ✗

Edge

-21.6%

Total Points

Over 45.5 @1.91

Lost ✗

Edge

-1.4%

Form & History

TeamLast 5Avg Pts
Dragons
LLLLL
23.6
Storm
WWWWW
44.2

Avg Conceded

32.2

Dragons

16.4

Storm

Avg Margin

-8.6

Dragons

27.8

Storm

Run Metres

1667

Dragons

1848

Storm

Line Breaks

5.2

Dragons

7.8

Storm

Referee IndicatorAI
Favours Storm
Peter Gough176 games since 2016

Each team's win rate when Peter Gough refs their game (vs any opponent, all seasons)

SGI
50%13W 13L
MEL
80%12W 3L

When Peter Gough officiates, Storm have won 12 of 15 games (80%) vs any opponent — significantly stronger than Dragons's 13 from 26 (50%). That's a 30‑point gap across all seasons. His games average 44.3 pts, sitting close to the league average.

Avg Total

44.3 pts

Home Win %

53%

Home Bias

Neutral

H2H History (Last 5)Storm lead 4-1
Mar 2026SGI 20 - 46 MEL
Aug 2024SGI 18 - 16 MEL
Sep 2023SGI 28 - 38 MEL
May 2022SGI 6 - 42 MEL
May 2021SGI 18 - 44 MEL
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

SGI
1388Overall1698
MEL
ELO difference: -310 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group — higher = stronger unit

1119Forwards1051
Best: 1325SGI +68Best: 1233
1143Backs1012
Best: 1214SGI +131Best: 1042
1124Halves1000
Best: 1124SGI +124Best: 1000
1123Hooker898
SGI +225

📈Recent Form (Last 5)

SGI
Stat
MEL
0.0
Wins (Last 5)
5.0
23.6pts
Avg Score
44.2pts
32.2pts
Avg Conceded
16.4pts
-8.6pts
Avg Margin
27.8pts
1667.0m
Run Metres
1848.0m
5.2
Line Breaks
7.8
358.6
Tackles
289.8
12.0
Errors
10.2

🔑Key Prediction Factors

What the model weighted most in this prediction

1
ELO Difference14.0%
Storm
2
Forward Pack12.0%
Dragons
3
Backline Quality10.0%
Dragons
4
Halves Control9.0%
Dragons
5
Recent Win Rate9.0%
Storm
6
Referee Tendency7.0%
7
Venue Advantage7.0%
Storm

Model Confidence

52%

Storm predicted to win by 4 points

Predicted total: 46 · Line: -4.2

0/3 match predictions correct
Coming Soon

Try Scorer Predictions

AI-powered try scorer predictions and player prop markets — built on our 6-model player stats engine.

First / Anytime / Last ScorerPlayer Props