⚽ FootballData
Dixon-Coles/League Two

League Two

Dixon-Coles model — fitted 16 Mar 2026 on 3,299 matches since 2020-01-01

Home Advantage (γ)
1.1535
>1 = home favoured
ρ (rho)
0.03954
low-score correction
Teams modelled
46
Log-likelihood
-811

Team Parameters

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

#TeamAttack (α)Defense (β)Matches
1Stockport
1.6595
0.8806
92
2Wrexham
1.5771
0.8450
46
3Mansfield
1.5578
0.9867
196
4Doncaster
1.3682
0.9717
138
5Bromley
1.3435
1.0036
78
6Swindon
1.3006
1.1044
229
7Milton Keynes Dons
1.2926
1.0622
124
8Chesterfield
1.2446
1.1412
78
9Port Vale
1.1983
0.8894
151
10Cambridge
1.1969
0.7537
91
11Bradford
1.1612
0.9180
244
12Notts County
1.1378
0.9288
124
13Salford
1.1168
1.1653
273
14Sutton
1.0990
1.4502
138
15Exeter
1.0756
0.8246
105
16Walsall
1.0477
1.0925
273
17Tranmere
1.0459
1.4706
262
18Crewe
1.0432
1.0637
185
19Colchester
1.0385
0.9415
275
20Grimsby
1.0351
1.0434
230
21Leyton Orient
1.0295
0.7742
150
22Fleetwood Town
1.0258
1.1601
77
23Northampton
1.0105
0.7778
105
24Stevenage
1.0069
0.8275
151
25Barnet
0.9723
0.9430
32
26Hartlepool
0.9627
1.4080
92
27Bolton
0.9480
0.9864
46
28Accrington
0.9263
0.9719
123
29Rochdale
0.9219
1.3134
92
30Gillingham
0.9218
1.1084
169
31AFC Wimbledon
0.9169
0.7269
138
32Plymouth
0.9149
0.9993
15
33Macclesfield
0.9013
1.0077
15
34Cheltenham
0.9008
1.4627
136
35Carlisle
0.8778
1.3302
197
36Oldham
0.8467
1.0168
136
37Barrow
0.8445
1.3448
261
38Newport County
0.8350
1.5649
276
39Southend
0.8053
1.0183
46
40Forest Green
0.7964
1.3507
150
41Morecambe
0.7805
1.4242
151
42Crawley Town
0.7738
1.3891
230
43Bristol Rvs
0.7670
1.5469
78
44Shrewsbury
0.7610
1.4106
32
45Harrogate
0.6241
1.3454
263
46Scunthorpe
0.5489
1.8988
105