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
BHA
48.2%2.07−2.3 pp
Draw
25.6%3.91−0.6 pp
LEE
26.2%3.82+2.9 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
Brighton48.2%2.07
Draw25.6%3.91
Leeds26.2%3.81
Double chance
Brighton or draw73.8%1.35
Brighton or Leeds74.4%1.34
Draw or Leeds51.8%1.93
Draw no bet
Brighton64.8%1.54
Leeds35.2%2.84
A draw returns the stake, so these prices exclude it.
Win to nil
Brighton24.3%4.12
Leeds12.3%8.15
Clean sheet
Brighton30.8%3.25
Leeds18.8%5.33
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.
Underlying expected goals+1.16 net xG per match
Favours BHA. BHA +0.65, LEE -0.51 across the form window — results are noisier than the chances behind them
Unavailable players14% home against 1% away xG missing
Favours LEE. 4 out and 3 doubtful for BHA, 1 out and 2 doubtful for LEE; measured as the share of recent expected goals those players contributed
Home advantage+60 Elo equivalent
Favours BHA. 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
Team rating gap+56 Elo
Favours BHA. BHA 1562 against LEE 1506, 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
Recent form1.20 against 1.60 points per game
Favours LEE. last 5 and 5 completed matches: LWLLW against DWLWD
Ch 04 · Comparison
Both sides
BHA
LWLLW
9 May – 30 Aug
LEE
DWLWD
11 May – 30 Aug
1.20Points per game1.60
10Goals for4
8Goals against5
10.95Expected goals6.18
1,562Elo1,506
Head to head over 6 meetings in the seasons held (Premier League from 2021-22, Championship from 2024-25): BHA 2, drawn 3, LEE 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
4.30
Smarkets
23.3%
43
h2h
draw
3.75
Betfred (UK)
26.7%
43
h2h
home
1.98
Betfair
50.5%
43
Ch 06 · Availability
Brighton
14.4% xG out
Share of attacking output is what moves the number, so it is shown rather than implied.
FergusonFWDinjured0%
Ankle injury - Expected back 10 Oct
MintehMIDinjured0%
Leg injury - Expected back 28 Nov
MitomaMIDinjured0%
Hamstring injury - Unknown return date
TzimasFWDinjured0%
Knee injury - Unknown return date
HinshelwoodMIDdoubtful50%27.0% xG
Unspecified injury - 50% chance of playing
AyariMIDdoubtful75%2.1% xG
Ankle injury - 75% chance of playing
GeorginioFWDdoubtful75%1.5% xG
Unspecified injury - 75% chance of playing
Ch 06 · Availability
Leeds
0.8% xG out
Share of attacking output is what moves the number, so it is shown rather than implied.
Mateo JosephFWDinjured0%
Knee injury - Unknown return date
RodonDEFdoubtful50%1.6% xG
Hamstring injury - 50% chance of playing
GruevMIDdoubtful25%
Knee injury - 25% chance of playing
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 awaymodel 26.2% vs 4.30 (Smarkets)+12.7 ppstake 1.0%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
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