Bournemouth v Leeds

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.

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.

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.

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.

Written by gpt-5.6-terra from the numbers above, which it cannot add to or override.

The model gives Bournemouth a 38.1% win probability, with the draw at 33.9% and Leeds at 27.9%. Expected goals are 1.06 for Bournemouth and 0.87 for Leeds. The 30.5% probability of over 2.5 goals and 38.9% probability of both teams scoring point to a low-scoring profile. Model fair odds are 2.62 for Bournemouth, 2.95 for the draw and 3.58 for Leeds. The market rates Bournemouth higher, at 45.2%, than the model does. It rates the draw at 28.3% and Leeds at 26.5%, both below the model’s numbers. The scorecard says this model does not beat the market. Across 5 matches, Bournemouth have 12.1 xG for and 4.4 against, despite scoring 8 and conceding 8. Leeds have 7.0 xG for and 6.3 against, with 6 goals scored and 4 conceded. The last 4 meetings produced 1 win each and 2 draws. There are no listed missing players, but 7 Bournemouth and 10 Leeds absentees have unmeasured output shares.

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

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