⚽ FootballData
Dixon-Coles/Premier League

Premier League

Dixon-Coles model — fitted 16 Mar 2026 on 392 matches since 2020-01-01

Home Advantage (γ)
1.0382
>1 = home favoured
ρ (rho)
-0.02943
low-score correction
Teams modelled
20
Log-likelihood
-301

Team Parameters

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

#TeamAttack (α)Defense (β)Matches
1Shakhtar Donetsk
2.1353
0.5773
49
2Loughborough Dynamo
1.9085
0.8677
50
3Polissya Zhytomyr
1.5304
0.6879
49
4Kryvbas
1.3676
0.9723
49
5Epitsentr Dunayivtsi
1.2496
1.3908
19
6Zorya Luhansk
1.2255
1.1128
49
7LNZ Cherkasy
1.1790
0.6196
49
8Kudrivka
1.1000
1.4408
19
9Karpaty
1.0728
1.1124
49
10Kharkiv
1.0714
0.4935
19
11Oleksandria
0.8931
1.0922
48
12Veres
0.8708
1.1343
49
13Kolos Kovalivka
0.8486
0.8638
49
14Poltava
0.7694
2.1815
19
15Vorskla
0.7253
1.0839
30
16Rukh Vynnyky
0.7138
1.0893
49
17Obolon'
0.6861
1.1745
49
18Inhulets
0.6770
1.3034
30
19Chornomorets
0.6734
1.3635
30
20Livyi Bereh
0.6247
1.2528
30