| Resulta | Probability |
|---|---|
| Panama | 16.8% |
| Draw | 25.6% |
| England | 57.6% |
| Line | Over | Under |
|---|---|---|
| 0.5 | 91.9% | 8.1% |
| 1.5 | 76.5% | 23.5% |
| 2.5 | 50.6% | 49.4% |
| 3.5 | 28.6% | 71.4% |
| 4.5 | 13.7% | 86.3% |
Poisson total λ = 2.7 (Over 2.5 50.6% · Under 2.5 49.4%).
BTTS Yes 50.7% · No 49.3% — balanced BTTS split.
| Score | Probability |
|---|---|
| 0-1 | 12.2% |
| 0-2 | 11.0% |
| 1-1 | 10.8% |
| 1-2 | 9.8% |
| 0-0 | 6.7% |
Top Poisson cell: 0-1 sa 12.2% (mataas ang exact-score variance).
1X2 mula sa Elo λ (0.89 / 1.81): home 16.8%, draw 25.6%, away 57.6%. Source: Dixon–Coles Poisson — hindi bookmaker odds.
Qualitative clarity ng 1X2 — hindi calibrated confidence interval.
- Lead outcome 57.6% na may 32.0 pp over 2nd.
Paano kinakalkula ang win probabilities?
Home at away λ mula sa Elo ratings at tournament parameters, papasok sa Dixon–Coles Poisson grid para sa 1X2, goal lines at scorelines sa page na ito.
Betting advice ba ang page na ito?
Hindi. Nagpapakita lang ang OddsGPT ng model probabilities para sa impormasyon. Hindi kami nagrerekomenda ng taya o stake sizes.
Ano ang ibig sabihin ng xG / λ dito?
Ang λ ay pre-match expected goals bago i-simulate ang variance. Input sa Poisson matrix, hindi post-match xG stat.
Bakit mababa ang exact score probabilities?
Kahit ang pinaka-malamang na scoreline ay madalas below 15% dahil maraming kombinasyon ang naghahati sa mass — normal sa Poisson.
