Gyor vs Zalaegerszegi
NB I., Hungary · 2026-08-23 · 17:30 CET
WDLWW
LLLWLThe score model made a Gyor win the most likely outcome at 62%, split on goals (Over 2.5 at 51%). It finished 3:0 (HT 1:0) — the most likely outcome came 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: Gyor 1.89 – 0.81 Zalaegerszegi.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Gyor win | 61.7% | 58.2% | +3.5% | ✓ |
| Draw | 24.0% | 22.3% | +1.8% | ✗ |
| Zalaegerszegi win | 14.3% | 19.6% | -5.2% | ✗ |
| Over 1.5 goals | 76.4% | — | — | ✓ |
| Over 2.5 goals | 50.8% | 61.6% | -10.9% | ✓ |
| Over 3.5 goals | 28.7% | 40.9% | -12.2% | ✗ |
| Both teams to score | 48.4% | 58.6% | -10.2% | ✗ |
| HT over 0.5 goals | 64.4% | — | — | ✓ |
| HT over 1.5 goals | 29.4% | 42.3% | -12.8% | ✗ |
Model dc_v2.0 · rating sample: Gyor 34.7 / Zalaegerszegi 43.5 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.