⚽ FootballData
Dixon-Coles/League One

League One

Dixon-Coles model — fitted 16 Mar 2026 on 3,281 matches since 2020-01-01

Home Advantage (γ)
1.3034
>1 = home favoured
ρ (rho)
0.08360
low-score correction
Teams modelled
52
Log-likelihood
-819

Team Parameters

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

#TeamAttack (α)Defense (β)Matches
1Ipswich
1.6680
0.5817
152
2Cardiff
1.6258
0.8631
32
3Birmingham
1.4629
0.5370
46
4Lincoln
1.4291
0.8502
275
5Sheffield Weds
1.3879
0.7292
92
6Barnsley
1.3754
1.4664
167
7Oxford
1.3065
1.0620
197
8Portsmouth
1.2881
0.8051
197
9Derby
1.2562
0.6740
92
10Peterboro
1.2456
1.1677
229
11Reading
1.2456
1.0913
124
12Charlton
1.2370
0.8385
230
13Huddersfield
1.2222
1.1229
79
14Plymouth
1.2006
1.1445
170
15Wrexham
1.1688
0.5959
46
16Sunderland
1.1264
0.9612
107
17Crawley Town
1.1181
1.4901
46
18Leyton Orient
1.0960
1.2303
123
19Stockport
1.0959
0.8685
77
20Wycombe
1.0811
0.8685
227
21Luton
1.0597
0.9958
32
22Bolton
1.0561
0.8735
231
23Blackpool
1.0539
1.1750
182
24Hull
0.9891
0.9772
46
25Mansfield
0.9796
0.9992
76
26Rochdale
0.9607
1.0326
57
27Bradford
0.9576
0.8352
31
28Coventry
0.9529
0.9979
12
29Swindon
0.9526
1.0543
46
30Southend
0.9515
1.0018
12
31Tranmere
0.9510
1.0016
12
32Doncaster
0.9440
1.3699
137
33AFC Wimbledon
0.9384
1.2213
135
34Burton
0.9098
1.1943
274
35Rotherham
0.8972
1.2082
134
36Fleetwood Town
0.8935
1.2481
198
37Exeter
0.8843
0.9265
169
38Morecambe
0.8791
1.4763
92
39Crewe
0.8485
1.2379
92
40Milton Keynes Dons
0.8451
1.1162
150
41Gillingham
0.8297
1.1010
104
42Stevenage
0.8100
0.8776
123
43Cambridge
0.8070
1.2224
184
44Cheltenham
0.7910
1.2017
138
45Northampton
0.7906
1.1435
170
46Wigan
0.7835
1.0308
215
47Bristol Rvs
0.7809
1.3898
197
48Carlisle
0.7502
1.5836
46
49Accrington
0.7189
1.4195
150
50Shrewsbury
0.7048
1.3584
242
51Port Vale
0.6828
1.2920
121
52Forest Green
0.4846
1.6440
46