| Score | Likelihood | Prob | Fair odds | |
|---|---|---|---|---|
| 2–1MODE | 9.5% | 10.57 | ||
| 1–1 | 8.3% | 12.10 | ||
| 3–1 | 7.2% | 13.85 | ||
| 2–0 | 7.2% | 13.91 | ||
| 1–0 | 6.3% | 15.92 | ||
| 2–2 | 6.2% | 16.06 | ||
| 3–0 | 5.5% | 18.23 | ||
| 1–2 | 5.4% | 18.38 |
Qatar scores shown first. Bivariate Poisson with team xG from recent form — most-likely score ≠ most-likely winner.
Probabilities derived from a Poisson model on expected goals. Edge % shown only when the book posts both sides of a market.
| Combo | Joint prob | Naïve (book) | Corr. | Fair odds |
|---|---|---|---|---|
Home win + BTTS home + btts | 34.8% | 38.8% | -10% | 2.87 |
Home win + Over 2.5 home + total_goals_2.5 | 45.4% | 41.1% | +10% | 2.20 |
Away win + BTTS away + btts | 13.8% | 14.0% | -1% | 7.23 |
Away win + Over 2.5 away + total_goals_2.5 | 15.3% | 14.9% | +3% | 6.53 |
Joint probability comes from the score grid (the truth). Naïve is what a book gets by multiplying legs — they undershoot correlated positive legs like "home + BTTS" and overshoot anti-correlated ones like "draw + over 2.5". Buy positive correlation; avoid negative.
Model probabilities Qatar 47.8% · Draw 26.0% · Switzerland 26.2% Why Qatar is favoured Elo essentially level (1500 vs 1500) — winner depends on context. But — counter-arguments Elo confidence is low (30%) — ratings are based on a thin sample, so the prediction itself is wider than the headline number suggests. Confidence note Elo data on these teams is thin (30% sample-size confidence); this is a low-conviction match overall — bet only with strong reason from outside the model.