Chiba vs Okayama
J1 League, Japan · 2026-09-02 · 12:00 CET
LLWDL
LWWWLThe score model made an Okayama win the most likely outcome at 44%, split on goals (Over 2.5 at 45%). It finished 1:2 (HT 1:1) — 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: Chiba 1.12 – 1.36 Okayama.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Chiba win | 32.4% | 24.2% | +8.2% | ✗ |
| Draw | 23.5% | 26.9% | -3.4% | ✗ |
| Okayama win | 44.1% | 49.0% | -4.9% | ✓ |
| Over 1.5 goals | 69.2% | — | — | ✓ |
| Over 2.5 goals | 45.1% | 48.7% | -3.5% | ✓ |
| Over 3.5 goals | 23.8% | 27.9% | -4.1% | ✗ |
| Both teams to score | 48.4% | 52.3% | -3.9% | ✓ |
| HT over 0.5 goals | 64.7% | — | — | ✓ |
| HT over 1.5 goals | 31.9% | 33.3% | -1.3% | ✓ |
Model dc_v2.0 · rating sample: Chiba 13.6 / Okayama 28.3 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.