Ligue 1
Dixon-Coles model — fitted 16 Mar 2026 on 2,168 matches since 2020-01-01
Home Advantage (γ)
1.2443
>1 = home favoured
ρ (rho)
0.05641
low-score correction
Teams modelled
30
Log-likelihood
-647
Team Parameters
Attack (α) — normalised attacking strength; mean ≈ 1.0. Defense (β) — defensive weakness; lower = harder to score against.
| # | Team | Attack (α) | Defense (β) | Matches |
|---|---|---|---|---|
| 1 | Aris | 1.9062 | 0.7204 | 59 |
| 2 | Marseille | 1.7480 | 1.1230 | 224 |
| 3 | Lens | 1.5798 | 0.6847 | 211 |
| 4 | Paris SG | 1.5313 | 0.9141 | 238 |
| 5 | Rennes | 1.4868 | 1.0720 | 224 |
| 6 | Monaco | 1.4783 | 0.9684 | 223 |
| 7 | Lyon | 1.4034 | 0.9306 | 221 |
| 8 | Strasbourg | 1.3206 | 0.9159 | 220 |
| 9 | Toulouse | 1.2375 | 0.9735 | 146 |
| 10 | Lorient | 1.2101 | 1.1039 | 173 |
| 11 | Lille | 1.1959 | 0.9521 | 222 |
| 12 | Nice | 1.1896 | 1.1947 | 221 |
| 13 | Brest | 1.1483 | 1.0493 | 222 |
| 14 | Saint-Étienne | 1.1198 | 1.7192 | 34 |
| 15 | St Etienne | 1.1038 | 1.7560 | 119 |
| 16 | Bordeaux | 1.0359 | 1.7364 | 84 |
| 17 | Metz | 0.9531 | 1.6755 | 146 |
| 18 | Paris FC | 0.8838 | 1.2142 | 23 |
| 19 | Amiens | 0.8637 | 1.0008 | 10 |
| 20 | Nimes | 0.8576 | 1.4217 | 48 |
| 21 | Troyes | 0.8356 | 1.5989 | 74 |
| 22 | Nantes | 0.8190 | 1.2194 | 221 |
| 23 | Clermont | 0.7186 | 1.3259 | 108 |
| 24 | Angers | 0.6961 | 0.9188 | 189 |
| 25 | Le Havre | 0.6885 | 0.9502 | 99 |
| 26 | Reims | 0.6795 | 1.0286 | 194 |
| 27 | Auxerre | 0.6755 | 0.8969 | 105 |
| 28 | Dijon | 0.6233 | 1.6538 | 47 |
| 29 | Montpellier | 0.5602 | 1.6620 | 193 |
| 30 | Ajaccio | 0.4125 | 1.6235 | 38 |