Ljungskile vs Oster
Superettan, Sweden · 2026-08-15 · 13:00 CET
WWLDL
LWWLLThe score model makes an Oster win the most likely outcome at 39%, split on goals (Over 2.5 at 53%). The data's biggest gap to the market: Oster win — 38.9% vs 25.8% implied (+13.1 pts). 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: Ljungskile 1.37 – 1.44 Oster.
| Market | Data % | Implied | Divergence |
|---|---|---|---|
| Ljungskile win | 35.8% | 48.2% | -12.4% |
| Draw | 25.3% | 26.0% | -0.7% |
| Oster win | 38.9% | 25.8% | +13.1% |
| Over 1.5 goals | 77.0% | — | — |
| Over 2.5 goals | 53.2% | 62.4% | -9.1% |
| Over 3.5 goals | 31.0% | 42.8% | -11.8% |
| Both teams to score | 56.9% | 64.3% | -7.4% |
| HT over 0.5 goals | 66.0% | — | — |
| HT over 1.5 goals | 30.9% | 42.7% | -11.8% |
Model dc_v2.0 · rating sample: Ljungskile 15.7 / Oster 27.4 weighted matches · positive divergence means the data leans above the market — the market usually knows why.
Track your pick
My record →Flat 1u, average market odds, settled either way. Not betting advice — a record, like ours.
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.