NRL | Round 10

alphr.com.au

SGI
Dragons
VS
NEW
Knights
WIN STADIUM, WOLLONGONG • SATURDAY 9 MAY, 3:00 PM

Win Probability

AI Game Review

Our model correctly predicted Knights to win at 67% probability. The margin model missed here — predicting 6.6 but the actual margin was 34 points. Total score prediction of 48 was close to the actual 54 — within 6 points. The model went 5/17 on this match.

Model vs actual outcomes • Post-match analysis

🏁

AI Referee Insights

Todd Smith officiated this match (103 career games). The combined score of 54 points was 8 points above Todd Smith's career average of 46.

Based on referee career statistics • Post-match analysis

AI Win Probability

67%KnightsFavourite

Dragons

33%

Knights

67%

AI Match Overview

Knights are clear favourites here at 67%, with our model expecting a comfortable victory over Dragons. Dragons are stronger on paper across 6 of 7 key factors — including ELO Difference, Forward Pack and Backline Quality — but Knights counter with Recent Win Rate which tips the scales. Dragons carry a 65-point ELO rating advantage (1500 vs 1435). Recent form favours Knights with 2 wins from their last 5 compared to 0 for Dragons. The margin model predicts Knights by 6.6 points with a combined total of 48.

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

Knights to Win @1.35

Winner ✓

Edge

-3.6%

Line / Spread

Dragons +9.5 @1.91

Lost ✗

Edge

+0.0%

Margin Band

Knights 1-12 @2.55

Lost ✗

Edge

+0.0%

Total Points

Under 52.5 @1.91

Lost ✗

Edge

+0.0%

Form & History

TeamLast 5Avg Pts
Dragons
R4L
R5L
R6L
R7L
R8L

older → newer

12.0
Knights
R5W
R6L
R7L
R8L
R9W
26.4

Avg Conceded

34.8

Dragons

34.8

Knights

Avg Margin

-22.8

Dragons

-8.4

Knights

Run Metres

1517

Dragons

1482

Knights

Line Breaks

3.0

Dragons

5.0

Knights

Referee Indicator

Balanced

Todd Smith

103 career games · since 2012

AI Analysis

Win rate when Todd Smith refs each team (vs any opponent)

Dragons
2W – 10L
17%
Knights
1W – 6L
14%

Both sides have a similar record under Todd Smith — Dragons 2W–10L (17%) and Knights 1W–6L (14%). Games average 46.1 pts — above the league norm, suggesting a free-flowing style. Small sample (7 games for Knights).

Avg Total

46.1 pts

Home Win %

54%

Home Bias

Leans home

Penalty & Discipline

Pen / Game

10.7

Sin Bins / Gm

0.49

SB Away %

50%

Avg Penalties Per Game

vs Home Teams5.3
vs Away Teams5.4

Penalty Advantage Under This Ref

Positive = opponent penalised more than your team

Dragons
-0.6
Knights
+1.4

Knights get a +1.4 penalty advantage under Todd Smith vs Dragons's -0.6.

H2H History (Last 5)Dragons lead 3-2
Jun 2025SGI 20 - 6 NEW
Apr 2024SGI 10 - 30 NEW
Sep 2023SGI 12 - 32 NEW
Apr 2022SGI 21 - 16 NEW
Mar 2021SGI 22 - 13 NEW
Prediction BreakdownPure Alpha Model

ELO–Market Disagreement

Dragons hold the ELO advantage (1500 vs 1435), but the market favours Knights (@1.35).

The model sides with the market — other factors override the ELO gap.

📊Team ELO Ratings

SGI
1500Overall1435
NEW
ELO difference: +65 in favour of Dragons

🏈Positional Matchups

Player ELO aggregated by position group — higher = stronger unit

977Forwards910
SGI +67
1016Backs955
SGI +61
1021Halves920
SGI +101
964Hooker939
SGI +26

📈Recent Form (Last 5)

SGI
Stat
NEW
0.0
Wins (Last 5)
2.0
12.0pts
Avg Score
26.4pts
34.8pts
Avg Conceded
34.8pts
-22.8pts
Avg Margin
-8.4pts
1517.2m
Run Metres
1481.8m
3.0
Line Breaks
5.0
375.2
Tackles
349.0
11.0
Errors
11.6

🔑Key Prediction Factors

What the model weighted most in this prediction

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

Model Confidence

67%

Knights predicted to win by 7 points

Predicted total: 48 · Line: -6.6

1/4 match predictions correct4/13 scorer picks correct
Scorer Markets

Anytime Try Scorer

Model probability vs Sportsbet overlay, ranked by edge.

8 Plays
Moses SuliDragons
backFair 2.602+ 9%
$3.20
+7.2% edge
Model
38%
Market
31%
Confidence
38%
Setu TuDragons
backFair 1.992+ 16%
$2.15
+3.7% edge
Model
50%
Market
47%
Confidence
50%
Greg MarzhewKnights
backFair 1.632+ 25%
$1.55
-3.1% edge
Model
61%
Market
65%
Confidence
61%
Dominic YoungKnights
backFair 1.942+ 16%
$1.58
-11.9% edge
Model
51%
Market
63%
Confidence
51%
Fletcher SharpeKnights
halfFair 3.142+ 6%
$2.20
-13.6% edge
Model
32%
Market
45%
Confidence
32%
Valentine HolmesDragons
backFair 3.872+ 4%
$2.35
-16.7% edge
Model
26%
Market
43%
Confidence
26%
Kalyn PongaKnights
backFair 5.732+ 2%
$2.08
-30.6% edge
Model
17%
Market
48%
Confidence
17%
Mathew FeagaiDragons
backFair 6.542+ 1%
$1.97
-35.5% edge
Model
15%
Market
51%
Confidence
15%
Scorer Markets

First Try Scorer

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

5 Plays
Setu TuDragons
backFair 5.492+ 16%
$13.00
+10.5% edge
Model
18%
Market
8%
Confidence
18%
Greg MarzhewKnights
backFair 4.612+ 25%
$8.50
+9.9% edge
Model
22%
Market
12%
Confidence
22%
Moses SuliDragons
backFair 7.902+ 9%
$17.00
+6.8% edge
Model
13%
Market
6%
Confidence
13%
Dominic YoungKnights
backFair 6.072+ 16%
$8.00
+4.0% edge
Model
16%
Market
13%
Confidence
16%
Fletcher SharpeKnights
halfFair 11.422+ 6%
$12.00
+0.4% edge
Model
9%
Market
8%
Confidence
9%