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Fixture 22scheduledGW 3

Newcastle v Bournemouth

market prices held
Expected goals1.80 — 1.24
Expected points1.74 — 1.02
Over 2.558.6%fair 1.71
Both score60.0%fair 1.67
Most likely1-111.3%
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
NEW49.8%2.01+5.6 pp
Draw24.4%4.10−0.9 pp
BOU25.8%3.88−4.7 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
Newcastle49.8%2.01
Draw24.4%4.10
Bournemouth25.8%3.88
Double chance
Newcastle or draw74.2%1.35
Newcastle or Bournemouth75.6%1.32
Draw or Bournemouth50.2%1.99
Draw no bet
Newcastle65.9%1.52
Bournemouth34.1%2.93
A draw returns the stake, so these prices exclude it.
Win to nil
Newcastle23.5%4.26
Bournemouth11.1%8.98
Clean sheet
Newcastle28.9%3.46
Bournemouth16.5%6.05
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.

Home advantage+60 Elo equivalent
Favours NEW. 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
Recent form1.60 against 1.20 points per game
Favours NEW. last 5 and 5 completed matches: WDLWD against DLDDW
Team rating gap-31 Elo
Favours BOU. NEW 1555 against BOU 1586, 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
Unavailable players3% home against 0% away xG missing
Favours BOU. 4 out and 0 doubtful for NEW, 4 out and 0 doubtful for BOU; measured as the share of recent expected goals those players contributed
Underlying expected goals-0.02 net xG per match
Favours BOU. NEW -0.35, BOU -0.34 across the form window — results are noisier than the chances behind them
Ch 04 · Comparison

Both sides

NEW
WDLWD
10 May – 29 Aug
BOU
WDDLD
9 May – 29 Aug
1.60Points per game1.20
8Goals for5
6Goals against5
6.63Expected goals7.02
1,555Elo1,586

Head to head over 8 meetings in the seasons held (Premier League from 2021-22, Championship from 2024-25): NEW 0, drawn 5, BOU 3. 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.

MarketSelectionBestBookImpliedN
h2haway3.25Smarkets30.8%43
h2hdraw3.901xBet25.6%43
h2hhome2.27GTbets44.1%43
Ch 06 · Availability

Newcastle

2.6% xG out

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

OsulaFWDinjured0%2.6% xG
Foot injury - Unknown return date
BurnDEFinjured0%
Ankle injury - Expected back 14 Sep
JoelintonMIDinjured0%
Unspecified injury - Unknown return date
LivramentoDEFinjured0%
Calf injury - Unknown return date
Ch 06 · Availability

Bournemouth

0.0% xG out

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

AdliMIDinjured0%
Unspecified injury - Unknown return date
J.AraujoDEFinjured0%
Thigh injury - Unknown return date
Kroupi.JrMIDinjured0%
Foot injury - Unknown return date
MilosavljevićDEFinjured0%
Unspecified 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 homemodel 49.8% vs 2.27 (GTbets)+13.1 ppstake 2.0%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
MetricModelMarketΔ
Ranked probability score0.20470.1965+0.0082
Log loss0.98820.9623+0.0259
Brier0.58830.5711+0.0172
Accuracy52.5%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