Opava vs Dukla Prague
ChNL, Czech-Republic · 2026-09-05 · 18:00 CET
DLDWW
LWWWDThe score model made an Opava win the most likely outcome at 38%, split on goals (Over 2.5 at 51%). It finished 1:2 (HT 1:0) — the most likely outcome did not come in. Generated from the data — the market usually knows why it disagrees.
Scoreline probabilities
Priced from the same score distribution as every market below.
First goal · head-to-head
Full Market Baseline (Dixon-Coles)
One statistical model of the final score — every probability below derives from the same score distribution, so they can never contradict each other. Expected goals: Opava 1.36 – 1.34 Dukla Prague.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Opava win | 37.7% | 32.8% | +4.9% | ✗ |
| Draw | 25.3% | 28.5% | -3.2% | ✗ |
| Dukla Prague win | 37.0% | 38.7% | -1.7% | ✓ |
| Over 1.5 goals | 74.8% | — | — | ✓ |
| Over 2.5 goals | 50.6% | 52.4% | -1.8% | ✓ |
| Over 3.5 goals | 28.5% | 31.4% | -2.8% | ✗ |
| Both teams to score | 54.5% | 57.0% | -2.5% | ✓ |
| HT over 0.5 goals | 72.8% | — | — | ✓ |
| HT over 1.5 goals | 37.0% | 35.7% | +1.4% | ✗ |
Model dc_v2.0 · rating sample: Opava 40.7 / Dukla Prague 12.4 weighted matches · positive divergence means the model sits above the market — descriptive, not a recommendation; the market usually knows why.
How to read this page: probabilities are what this league's historical first-goal-time and scoring data alone imply — they know nothing about injuries, motivation or weather, and the market usually does. We publish every output, including when the data and the market agree. Statistics, not betting advice — never bet more than you can afford to lose.