Gimhae vs Yongin
K League 2, South-Korea · 2026-08-30 · 12:30 CET
LDDLL
WDDLDThe score model made a Yongin win the most likely outcome at 50%, split on goals (Over 2.5 at 49%). It finished 0:3 (HT 0:3) — 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: Gimhae 1.03 – 1.59 Yongin.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Gimhae win | 23.8% | 31.9% | -8.1% | ✗ |
| Draw | 26.2% | 28.4% | -2.2% | ✗ |
| Yongin win | 50.0% | 39.6% | +10.3% | ✓ |
| Over 1.5 goals | 74.3% | — | — | ✓ |
| Over 2.5 goals | 48.7% | 46.7% | +2.0% | ✓ |
| Over 3.5 goals | 26.9% | 26.6% | +0.2% | ✗ |
| Both teams to score | 51.8% | 52.7% | -0.9% | ✗ |
| HT over 0.5 goals | 55.4% | — | — | ✓ |
| HT over 1.5 goals | 20.3% | 32.3% | -12.0% | ✓ |
Model dc_v2.0 · rating sample: Gimhae 17.5 / Yongin 17.4 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.