No bookmaker prices are held for this fixture, so there is no caret to compare against. Fair price is 1 / probability with no margin, and is not a price anyone is offering.
OutcomeModel probabilityProbFairΔ
NEW
55.3%1.81–
Draw
23.8%4.21–
HUL
21.0%4.77–
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.
Thin sample
Hull City has only 2 completed matches in the training window, so its fitted strength is imprecise. Treat the long prices in this book as arithmetic rather than information: a real bookmaker would quote a much shorter price on the outsider.
Matches behind each fit: Newcastle 149 · Hull City 2
Match result
Newcastle55.3%1.81
Draw23.8%4.21
Hull City21.0%4.77
Double chance
Newcastle or draw79.0%1.26
Newcastle or Hull City76.2%1.31
Draw or Hull City44.7%2.23
Draw no bet
Newcastle72.5%1.38
Hull City27.5%3.63
A draw returns the stake, so these prices exclude it.
Win to nil
Newcastle29.4%3.40
Hull City10.3%9.71
Clean sheet
Newcastle35.5%2.82
Hull City16.4%6.11
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 2.00 points per game
Favours HUL. last 5 and 5 completed matches: WDLWD against WWWLD
Team rating gap+31 Elo
Favours NEW. NEW 1555 against HUL 1523, 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 HUL. 4 out and 0 doubtful for NEW, 6 out and 2 doubtful for HUL; measured as the share of recent expected goals those players contributed
Underlying expected goals-0.15 net xG per match
Favours HUL. NEW -0.35, HUL -0.20 across the form window — results are noisier than the chances behind them
Ch 04 · Comparison
Both sides
NEW
WDLWD
10 May – 29 Aug
HUL · incl. Championship
DLWWW
21 Apr – 29 Aug
1.60Points per game2.00
8Goals for8
6Goals against5
6.63Expected goals (2 of 5)1.96
1,555Elo1,523
Ch 05 · Market
Bookmaker prices
No bookmaker prices held for this fixture. Every price shown is the model's own fair price, meaning 1 / probability with no margin. Nobody is offering these.
Nothing held. football-data.co.uk publishes weekend Premier League prices on Friday afternoon, and The Odds API needs a key. Historical fixtures already carry closing odds, so the comparison works there.
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
Hull City
0.0% xG out
Share of attacking output is what moves the number, so it is shown rather than implied.
ButlandGKPinjured0%
Arm injury - Unknown return date
GelhardtMIDinjured0%
Ankle injury - Expected back 5 Sep
GyabiMIDinjured0%
Thigh injury - Unknown return date
HughesDEFinjured0%
Groin injury - Unknown return date
MatazoMIDinjured0%
Knee injury - Unknown return date
ZambranoMIDinjured0%
Thigh injury - Unknown return date
CoyleDEFdoubtful75%
Unspecified injury - 75% chance of playing
CrooksMIDdoubtful75%
Thigh injury - 75% 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 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