Pohang vs Gimcheon Sangmu
K League 1, South-Korea · 2026-08-01 · 12:30 CET
WDLDD
DDLDDThe score model made a Pohang win the most likely outcome at 37%, split on goals (Over 2.5 at 46%). It finished 0:1 (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: Pohang 1.28 – 1.25 Gimcheon Sangmu.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Pohang win | 36.5% | 44.0% | -7.5% | ✗ |
| Draw | 28.3% | 29.0% | -0.7% | ✗ |
| Gimcheon Sangmu win | 35.2% | 27.0% | +8.2% | ✓ |
| Over 1.5 goals | 72.5% | — | — | ✗ |
| Over 2.5 goals | 46.2% | 43.8% | +2.4% | ✗ |
| Over 3.5 goals | 24.7% | 24.3% | +0.5% | ✗ |
| Both teams to score | 52.1% | 49.6% | +2.5% | ✗ |
| HT over 0.5 goals | 65.0% | — | — | ✗ |
| HT over 1.5 goals | 30.5% | 30.5% | +0.0% | ✗ |
Model dc_v2.0 · rating sample: Pohang 44.2 / Gimcheon Sangmu 40.4 weighted matches · positive divergence means the data leans above the market — 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.