Fixture 37scheduledGW 4

Sunderland v Arsenal

Sat 12 Sept 19:00Zmarket prices held

Expected goals0.89 — 1.55

Expected points0.90 — 1.84

Over 2.543.9%fair 2.28

Both score47.0%fair 2.13

Most likely0-113.0%

Markets priced27

Ch 01 · Outcome

Match result

The bar is the model's probability; the caret on the same scale is the market's, with the margin removed. The distance between them is the disagreement.

OutcomeModel fill · market caretProbFairΔ mkt

SUN

20.9%4.79+7.7 pp

Draw

26.8%3.72+4.4 pp

ARS

52.3%1.91−12.1 pp

Ch 02 · Book

27 markets

dixon_coles xi001-20260903

Model fair prices, computed as 1 / probability from a Dixon-Coles score matrix. No bookmaker margin is included, and no bookmaker is quoting these. A real price will be shorter than every number here.

Match result

Sunderland20.9%4.79

Draw26.8%3.73

Arsenal52.3%1.91

Double chance

Sunderland or draw47.7%2.10

Sunderland or Arsenal73.2%1.37

Draw or Arsenal79.1%1.26

Draw no bet

Sunderland28.5%3.50

Arsenal71.5%1.40

A draw returns the stake, so these prices exclude it.

Win to nil

Sunderland11.8%8.46

Arsenal31.9%3.14

Clean sheet

Sunderland21.1%4.73

Arsenal41.2%2.43

Ch 03 · Reasoning

What is driving this

computed, not generated

Computed arithmetic, not generated text. Each driver is a stored quantity: the Elo difference replayed from results, points per game over the last five matches, rolling expected goals, and each absent player's share of team expected goals.

Team rating gap-215 Elo

Favours ARS. SUN 1536 against ARS 1751, computed from stored results; an Elo-driven model scores RPS around 0.2015 on this league against roughly 0.194 for de-vigged closing odds

Underlying expected goals-0.88 net xG per match

Favours ARS. SUN +0.44, ARS +1.32 across the form window — results are noisier than the chances behind them

Recent form2.00 against 3.00 points per game

Favours ARS. last 5 and 5 completed matches: WLWWD against WWWWW

Home advantage+60 Elo equivalent

Favours SUN. the football default is around 100 Elo points, but Premier League home advantage fell during the crowdless 2020/21 season and settled lower afterwards, so the ratings carry a smaller term

Unavailable players0% home against 0% away xG missing

Favours ARS. 1 out and 1 doubtful for SUN, 3 out and 0 doubtful for ARS; measured as the share of recent expected goals those players contributed

Ch 04 · Comparison

Both sides

SUN

WLWWD

9 May – 30 Aug

ARS

WWWWW

10 May – 31 Aug

2.00Points per game3.00

7Goals for8

4Goals against1

7.59Expected goals9.94

1,536Elo1,751

Head to head over 2 meetings in the seasons held (Premier League from 2021-22, Championship from 2024-25): SUN 0, drawn 1, ARS 1. Cup ties and earlier seasons are not included, so a full-history site will show more.

Ch 05 · Market

Bookmaker prices

Real bookmaker prices, collected from published market data.

Market	Selection	Best	Book	Implied	N
h2h	away	1.54	1xBet	64.9%	33
h2h	draw	4.37	1xBet	22.9%	33
h2h	home	7.80	Betfair	12.8%	33

Ch 06 · Availability

Sunderland

0.3% xG out

Share of attacking output is what moves the number, so it is shown rather than implied.

AdingraMIDinjured0%

Ankle injury - Unknown return date

DiarraMIDdoubtful75%1.1% xG

Unspecified injury - 75% chance of playing

Ch 06 · Availability

Arsenal

0.0% xG out

Share of attacking output is what moves the number, so it is shown rather than implied.

J.TimberDEFinjured0%

Groin injury - Unknown return date

NelsonMIDunavailable0%

has departed the club as a free agent.

SalibaDEFinjured0%

Back injury - Unknown return date

Ch 07 · Simulation

Re-price without a player

Removing a player scales that side's expected goals by their share of recent attacking output, then rebuilds the score matrix. Every market moves together.

Ch 09 · Divergence

Where the model differs from a price

Shown with the model's own record, because that is what decides how much these are worth.

h2h drawmodel 26.8% vs 4.37 (1xBet)+17.3 ppstake 1.3%medium confidence

Ch 10 · Calibration

How this model actually scores

Dixon-Coles bivariate Poisson fitted to Premier League results with exponential time decay. Statistical model, no language model involved.

loses to closing market2,281 out-of-sample fixtures

Metric	Model	Market	Δ
Ranked probability score	0.2047	0.1965	+0.0082
Log loss	0.9882	0.9623	+0.0259
Brier	0.5883	0.5711	+0.0172
Accuracy	52.5%	54.8%	−2.3 pp

Lower is better for the first three. These probabilities are for reading a fixture, not for expecting profit against closing prices. What these numbers mean