Avispa Fukuoka vs Mito
J1 League, Japan · 2026-09-05 · 12:00 CET
LDLLW
DWDLLThe score model made an Avispa Fukuoka win the most likely outcome at 44%, split on goals (Over 2.5 at 51%). 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: Avispa Fukuoka 1.47 – 1.25 Mito.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Avispa Fukuoka win | 43.8% | 46.6% | -2.8% | ✗ |
| Draw | 22.5% | 28.7% | -6.2% | ✓ |
| Mito win | 33.7% | 24.7% | +9.0% | ✗ |
| Over 1.5 goals | 74.1% | — | — | ✓ |
| Over 2.5 goals | 51.2% | 44.5% | +6.7% | ✗ |
| Over 3.5 goals | 29.1% | 24.2% | +4.9% | ✗ |
| Both teams to score | 53.6% | 50.0% | +3.6% | ✓ |
| HT over 0.5 goals | 71.4% | — | — | ✗ |
| HT over 1.5 goals | 41.0% | 30.6% | +10.4% | ✗ |
Model dc_v2.0 · rating sample: Avispa Fukuoka 40.8 / Mito 10.8 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.