Darlington vs Chester
National League North, England · 2026-08-18 · 20:45 CET
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WDLDLThe score model made a Chester win the most likely outcome at 38%, split on goals (Over 2.5 at 50%). It finished 0:1 (HT 0:0) — 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: Darlington 1.32 – 1.36 Chester.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Darlington win | 36.4% | 29.2% | +7.2% | ✗ |
| Draw | 25.6% | 26.8% | -1.2% | ✗ |
| Chester win | 38.0% | 44.0% | -6.0% | ✓ |
| Over 1.5 goals | 74.6% | — | — | ✗ |
| Over 2.5 goals | 50.2% | 52.4% | -2.2% | ✗ |
| Over 3.5 goals | 28.2% | 31.8% | -3.6% | ✗ |
| Both teams to score | 54.4% | 55.9% | -1.6% | ✗ |
| HT over 0.5 goals | 71.1% | — | — | ✗ |
| HT over 1.5 goals | 34.6% | 36.1% | -1.5% | ✗ |
Model dc_v2.0 · rating sample: Darlington 57.3 / Chester 58.5 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.