Ostersund vs Ljungskile
Superettan, Sweden · 2026-08-24 · 19:00 CET
DWDWD
LDWLLThe score model made an Ostersund win the most likely outcome at 43%, split on goals (Over 2.5 at 50%). It finished 0:0 (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: Ostersund 1.48 – 1.19 Ljungskile.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Ostersund win | 43.3% | 48.3% | -5.0% | ✗ |
| Draw | 26.4% | 25.9% | +0.5% | ✓ |
| Ljungskile win | 30.3% | 25.8% | +4.5% | ✗ |
| Over 1.5 goals | 75.0% | — | — | ✗ |
| Over 2.5 goals | 49.9% | 55.4% | -5.5% | ✗ |
| Over 3.5 goals | 27.9% | 34.4% | -6.5% | ✗ |
| Both teams to score | 54.1% | 58.0% | -3.9% | ✗ |
| HT over 0.5 goals | 62.9% | — | — | ✗ |
| HT over 1.5 goals | 27.5% | 36.9% | -9.5% | ✗ |
Model dc_v2.0 · rating sample: Ostersund 41.7 / Ljungskile 16.4 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.