Cheongju vs Gyeongnam
K League 2, South-Korea · 2026-08-23 · 12:30 CET
DLLWW
DDWWDThe score model made a Gyeongnam win the most likely outcome at 38%, with under 2.5 goals more likely than not (Over 2.5 at 41%). It finished 1:1 (HT 1:1) — 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: Cheongju 1.09 – 1.22 Gyeongnam.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Cheongju win | 32.0% | 35.7% | -3.7% | ✗ |
| Draw | 29.5% | 28.4% | +1.1% | ✓ |
| Gyeongnam win | 38.5% | 35.9% | +2.6% | ✗ |
| Over 1.5 goals | 68.0% | — | — | ✓ |
| Over 2.5 goals | 40.9% | 47.1% | -6.2% | ✗ |
| Over 3.5 goals | 20.4% | 26.8% | -6.3% | ✗ |
| Both teams to score | 47.6% | 52.7% | -5.1% | ✓ |
| HT over 0.5 goals | 61.9% | — | — | ✓ |
| HT over 1.5 goals | 26.5% | 32.0% | -5.5% | ✓ |
Model dc_v2.0 · rating sample: Cheongju 48.2 / Gyeongnam 49 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.