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
BOU
31.2%3.21–
Draw
24.8%4.04–
LIV
44.0%2.27–
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
Bournemouth31.2%3.21
Draw24.8%4.04
Liverpool44.0%2.27
Double chance
Bournemouth or draw56.0%1.79
Bournemouth or Liverpool75.2%1.33
Draw or Liverpool68.8%1.45
Draw no bet
Bournemouth41.5%2.41
Liverpool58.5%1.71
A draw returns the stake, so these prices exclude it.
Win to nil
Bournemouth13.1%7.64
Liverpool19.4%5.15
Clean sheet
Bournemouth18.2%5.51
Liverpool24.5%4.08
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-0.44 net xG per match
Favours LIV. BOU -0.34, LIV +0.10 across the form window — results are noisier than the chances behind them
Home advantage+60 Elo equivalent
Favours BOU. 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 form1.20 against 0.80 points per game
Favours BOU. last 5 and 5 completed matches: DLDDW against DDDLD
Team rating gap-38 Elo
Favours LIV. BOU 1586 against LIV 1624, 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 players0% home against 0% away xG missing
4 out and 0 doubtful for BOU, 7 out and 0 doubtful for LIV; measured as the share of recent expected goals those players contributed
Ch 04 · Comparison
Both sides
BOU
DLDDW
9 May – 29 Aug
LIV
DLDDD
9 May – 29 Aug
1.20Points per game0.80
5Goals for8
5Goals against10
7.02Expected goals9.58
1,586Elo1,624
Head to head over 8 meetings in the seasons held (Premier League from 2021-22, Championship from 2024-25): BOU 2, drawn 0, LIV 6. Cup ties and earlier seasons are not included, so a full-history site will show more.
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
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 06 · Availability
Liverpool
0.0% xG out
Share of attacking output is what moves the number, so it is shown rather than implied.
BradleyDEFinjured0%
Knee injury - Unknown return date
ChiesaMIDinjured0%
Back injury - Unknown return date
DannsFWDinjured0%
Unspecified injury - Unknown return date
EkitikéFWDinjured0%
Achilles injury - Unknown return date
GomezDEFinjured0%
Muscular injury - Unknown return date
JarosGKPinjured0%
Knee injury - Unknown return date
LeoniDEFinjured0%
Knee 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 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