⚽ FootballData
Dixon-Coles/Super League

Super League

Dixon-Coles model — fitted 16 Mar 2026 on 389 matches since 2020-01-01

Home Advantage (γ)
1.2132
>1 = home favoured
ρ (rho)
-0.17681
low-score correction
Teams modelled
13
Log-likelihood
-404

Team Parameters

Attack (α) — normalised attacking strength; mean ≈ 1.0. Defense (β) — defensive weakness; lower = harder to score against.

#TeamAttack (α)Defense (β)Matches
1Thun
1.4697
0.9248
29
2Luzern
1.3379
1.6336
65
3Holker Old Boys
1.2779
1.5299
64
4St. Gallen
1.1498
1.1073
65
5Servette
1.0750
1.4998
64
6Basel
1.0606
1.1743
65
7Lausanne Sport
1.0401
1.3962
65
8Lugano
0.9632
1.1137
65
9Zürich
0.8882
1.6563
65
10Sion
0.8186
1.0321
65
11Grasshopper
0.7795
1.3848
65
12Inter
0.7597
2.0832
65
13Yverdon Sport
0.7038
1.7360
36