Jelgava vs Super Nova
Virsliga, Latvia · 2026-09-05 · 16:00 CET
WWLDL
WWLLWThe score model made a Jelgava win the most likely outcome at 44%, with under 2.5 goals more likely than not (Over 2.5 at 43%). It finished 0:1 (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: Jelgava 1.36 – 1.03 Super Nova.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Jelgava win | 44.4% | 50.6% | -6.2% | ✗ |
| Draw | 27.4% | 25.7% | +1.7% | ✗ |
| Super Nova win | 28.2% | 23.7% | +4.5% | ✓ |
| Over 1.5 goals | 69.0% | — | — | ✗ |
| Over 2.5 goals | 42.7% | 52.8% | -10.1% | ✗ |
| Over 3.5 goals | 21.9% | 31.8% | -9.9% | ✗ |
| Both teams to score | 47.8% | 54.6% | -6.8% | ✗ |
| HT over 0.5 goals | 70.2% | — | — | ✗ |
| HT over 1.5 goals | 33.0% | 35.6% | -2.6% | ✗ |
Model dc_v2.0 · rating sample: Jelgava 51.1 / Super Nova 42 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.