Gimcheon Sangmu vs Seoul
K League 1, South-Korea · 2026-08-08 · 13:00 CET
LDDDW
WWWLWThe score model made a Seoul win the most likely outcome at 40%, split on goals (Over 2.5 at 49%). It finished 0:0 (HT 0:0) — 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: Gimcheon Sangmu 1.23 – 1.41 Seoul.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Gimcheon Sangmu win | 32.2% | 25.2% | +7.0% | ✗ |
| Draw | 27.3% | 26.7% | +0.6% | ✓ |
| Seoul win | 40.5% | 48.1% | -7.6% | ✗ |
| Over 1.5 goals | 74.8% | — | — | ✗ |
| Over 2.5 goals | 49.3% | 51.9% | -2.6% | ✗ |
| Over 3.5 goals | 27.4% | 31.2% | -3.8% | ✗ |
| Both teams to score | 54.3% | 55.2% | -0.9% | ✗ |
| HT over 0.5 goals | 64.9% | — | — | ✗ |
| HT over 1.5 goals | 30.4% | 35.2% | -4.8% | ✗ |
Model dc_v2.0 · rating sample: Gimcheon Sangmu 40.7 / Seoul 44.5 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.