Metz vs Laval
Ligue 2, France · 2026-08-22 · 14:00 CET
WDDDW
LWDLLThe score model made a Metz win the most likely outcome at 63%, split on goals (Over 2.5 at 49%). It finished 1:1 (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: Metz 1.87 – 0.78 Laval.
| Market | Data % | Implied | Divergence | Result |
|---|---|---|---|---|
| Metz win | 63.2% | 52.3% | +10.8% | ✗ |
| Draw | 21.8% | 26.7% | -4.9% | ✓ |
| Laval win | 15.0% | 21.0% | -5.9% | ✗ |
| Over 1.5 goals | 74.2% | — | — | ✓ |
| Over 2.5 goals | 49.4% | 48.1% | +1.3% | ✗ |
| Over 3.5 goals | 27.5% | 27.6% | -0.1% | ✗ |
| Both teams to score | 45.8% | 50.3% | -4.4% | ✓ |
| HT over 0.5 goals | 62.0% | — | — | ✗ |
| HT over 1.5 goals | 26.4% | 32.9% | -6.4% | ✗ |
Model dc_v2.0 · rating sample: Metz 15.8 / Laval 45.4 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.