NRL | Round 13

alphr.com.au

GLD
Titans
VS
MEL
Storm
CBUS SUPER STADIUM, GOLD COAST • SATURDAY 31 MAY, 3:00 PM

Win Probability

AI Game Review

Our model correctly predicted Storm to win at 64% probability. The predicted margin of 6.6 was reasonable against the actual 12-point result. Total score prediction of 45 was close to the actual 44, within 1 points. A clean sweep, all 3 model picks hit for this match.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Ziggy Przeklasa-Adamski officiated this match (75 career games). The 44-point combined total was right in line with Ziggy Przeklasa-Adamski's career average of 42. Storm's victory aligns with Ziggy Przeklasa-Adamski's historical trend, Storm have a 56% 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', Storm firmly in control (99%)
TIT16
1%80'99%
28STO
HT100%50%0%0'20'40'60'80'
Storm momentumMomentum -5Titans momentum →
Next Try (within 10 min)
AI Model
82% none
TIT 9%No try 82%STO 9%
Biggest Swings

AI Win Probability

64%StormFavourite

Titans

36%

Storm

64%

AI Match Overview

Storm hold the advantage at 64% win probability, though Titans are far from out of this at 36%. The model sees Storm ahead on 4 of 7 key factors including ELO Difference, Halves Control and Recent Win Rate. Storm carry a 299-point ELO rating advantage (1630 vs 1331). Recent form favours Storm with 2 wins from their last 5 compared to 1 for Titans. The margin model predicts Storm by 6.6 points with a combined total of 45.

Generated from model features • Pre-kick-off analysis

Edge Analysis

1 ACTIVE EDGE

Each market is predicted by an independent model, H2H, margin, and totals may occasionally disagree.

H2H Recommendation

Storm to Win @1.28

Winner ✓

Edge

-18.5%

Line / Spread

Storm +10.5 @1.91

Winner ✓

Edge

-18.5%

Total Points

Under 49.5 @1.91

Winner ✓

Edge

+13.6%

Form & History

TeamLast 5Avg Pts
Titans
W
L
L
L
L
20.8
Storm
W
W
L
L
L
30.8

Avg Conceded

35.6

Titans

21.8

Storm

Avg Margin

-14.8

Titans

9.0

Storm

Run Metres

1532

Titans

1724

Storm

Line Breaks

4.2

Titans

5.6

Storm

Referee Indicator

Favours Storm

Ziggy Przeklasa-Adamski

75 career games · since 2017

AI Analysis

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

Titans
3W – 9L
25%
Storm
5W – 4L
56%

When Ziggy Przeklasa-Adamski officiates, Storm have won 5 of 9 games (56%), significantly stronger than Titans's 3 from 12 (25%).

Avg Total

41.7 pts

Home Win %

45%

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

Titans
+0.0
Storm
+1.2

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. Storm get a +1.2 penalty advantage under Ziggy Przeklasa-Adamski vs Titans's +0.0. 70% of his 37 career sin bins go to away teams.

H2H History (Last 5)Storm lead 4-1
May 2024GLD 20 - 22 MEL
Sep 2023GLD 16 - 37 MEL
Mar 2023GLD 38 - 34 MEL
Aug 2022GLD 14 - 32 MEL
Aug 2021GLD 20 - 34 MEL
Prediction BreakdownPure Alpha Model

📊Team ELO Ratings

GLD
1331Overall1630
MEL
ELO difference: -299 in favour of Storm

🏈Positional Matchups

Player ELO aggregated by position group, higher = stronger unit

1088Forwards1068
Best: 1313GLD +20Best: 1299
1126Backs999
Best: 1274GLD +127Best: 1117
905Halves1176
Best: 905MEL +272Best: 1176
1089Hooker1171
MEL +82

📈Recent Form (Last 5)

GLD
Stat
MEL
1.0
Wins (Last 5)
2.0
20.8pts
Avg Score
30.8pts
35.6pts
Avg Conceded
21.8pts
-14.8pts
Avg Margin
9.0pts
1532.0m
Run Metres
1724.0m
4.2
Line Breaks
5.6
349.4
Tackles
316.2
9.4
Errors
13.4

🔑Key Prediction Factors

What the model weighted most in this prediction

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

Model Confidence

64%

Storm predicted to win by 7 points

Predicted total: 45 · Line: -6.6

3/3 match predictions correct
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