FA Siauliai vs Suduva
A Lyga, Lithuania · 2026-08-30 · 16:00 CET
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WWLDDThe score model made a Suduva win the most likely outcome at 60%, split on goals (Over 2.5 at 51%). It finished 1:2 (HT 0:1) — 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: FA Siauliai 0.85 – 1.84 Suduva.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| FA Siauliai win | 16.2% | 14.9% | +1.3% | ✗ |
| Draw | 23.9% | 21.8% | +2.1% | ✗ |
| Suduva win | 59.9% | 63.3% | -3.4% | ✓ |
| Over 1.5 goals | 75.8% | — | — | ✓ |
| Over 2.5 goals | 50.5% | 55.5% | -5.0% | ✓ |
| Over 3.5 goals | 28.5% | 34.9% | -6.4% | ✗ |
| Both teams to score | 49.1% | 50.4% | -1.3% | ✓ |
| HT over 0.5 goals | 67.1% | — | — | ✓ |
| HT over 1.5 goals | 31.5% | 38.4% | -6.9% | ✗ |
Model dc_v2.0 · rating sample: FA Siauliai 22.4 / Suduva 49.8 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.