Gwangju FC vs Seoul
K League 1, South-Korea · 2026-08-30 · 12:30 CET
LDLDD
WWLWLThe score model made a Seoul win the most likely outcome at 63%, split on goals (Over 2.5 at 50%). It finished 2:5 (HT 1:3) — 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: Gwangju FC 0.80 – 1.90 Seoul.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Gwangju FC win | 14.3% | 14.9% | -0.6% | ✗ |
| Draw | 23.1% | 22.0% | +1.2% | ✗ |
| Seoul win | 62.5% | 63.2% | -0.6% | ✓ |
| Over 1.5 goals | 75.8% | — | — | ✓ |
| Over 2.5 goals | 50.5% | 52.3% | -1.8% | ✓ |
| Over 3.5 goals | 28.5% | 31.2% | -2.7% | ✓ |
| Both teams to score | 47.5% | 48.6% | -1.2% | ✓ |
| HT over 0.5 goals | 63.0% | — | — | ✓ |
| HT over 1.5 goals | 28.6% | 37.0% | -8.4% | ✓ |
Model dc_v2.0 · rating sample: Gwangju FC 46 / Seoul 46.4 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.