Cheongju vs Seoul E-Land
K League 2, South-Korea · 2026-09-04 · 12:30 CET
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DWLWWThe score model made a Seoul E-Land win the most likely outcome at 56%, split on goals (Over 2.5 at 51%). It finished 0:2 (HT 0:2) — 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: Cheongju 0.95 – 1.76 Seoul E-Land.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Cheongju win | 19.6% | 23.2% | -3.7% | ✗ |
| Draw | 24.5% | 25.2% | -0.7% | ✗ |
| Seoul E-Land win | 56.0% | 51.6% | +4.4% | ✓ |
| Over 1.5 goals | 75.8% | — | — | ✓ |
| Over 2.5 goals | 50.8% | 55.8% | -5.0% | ✗ |
| Over 3.5 goals | 28.8% | 35.3% | -6.5% | ✗ |
| Both teams to score | 51.2% | 57.4% | -6.2% | ✗ |
| HT over 0.5 goals | 57.4% | — | — | ✓ |
| HT over 1.5 goals | 22.3% | 38.3% | -16.0% | ✓ |
Model dc_v2.0 · rating sample: Cheongju 49 / Seoul E-Land 49.6 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.