Zurich vs Servette
Super League, Switzerland · 2026-08-01 · 18:00 CET
LLWLD
LWDLLThe score model made a Servette win the most likely outcome at 44%, leaning to goals (Over 2.5 at 57%). It finished 2:1 (HT 1:0) — 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: Zurich 1.33 – 1.62 Servette.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Zurich win | 30.9% | 28.1% | +2.9% | ✓ |
| Draw | 25.2% | 24.4% | +0.8% | ✗ |
| Servette win | 43.8% | 47.5% | -3.7% | ✗ |
| Over 1.5 goals | 79.8% | — | — | ✓ |
| Over 2.5 goals | 56.5% | 60.4% | -3.9% | ✓ |
| Over 3.5 goals | 34.1% | 39.4% | -5.3% | ✗ |
| Both teams to score | 59.5% | 61.6% | -2.2% | ✓ |
| HT over 0.5 goals | 73.9% | — | — | ✓ |
| HT over 1.5 goals | 39.2% | 41.3% | -2.1% | ✗ |
Model dc_v2.0 · rating sample: Zurich 45.7 / Servette 45.7 weighted matches · positive divergence means the data leans above the market — 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.