Gimhae vs Gyeongnam
K League 2, South-Korea · 2026-08-15 · 12:30 CET
LDDLL
DDWWDThe score model made a Gyeongnam win the most likely outcome at 49%, split on goals (Over 2.5 at 48%). It finished 1:1 (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: Gimhae 1.04 – 1.55 Gyeongnam.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Gimhae win | 25.1% | 27.4% | -2.3% | ✗ |
| Draw | 26.3% | 28.1% | -1.8% | ✓ |
| Gyeongnam win | 48.6% | 44.5% | +4.1% | ✗ |
| Over 1.5 goals | 73.5% | — | — | ✓ |
| Over 2.5 goals | 48.0% | 46.4% | +1.6% | ✗ |
| Over 3.5 goals | 26.2% | 26.3% | -0.0% | ✗ |
| Both teams to score | 51.4% | 51.4% | +0.1% | ✓ |
| HT over 0.5 goals | 63.0% | — | — | ✗ |
| HT over 1.5 goals | 26.9% | 31.5% | -4.6% | ✗ |
Model dc_v2.0 · rating sample: Gimhae 16 / Gyeongnam 48.8 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.