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int64
0
2.27k
Player
stringlengths
3
26
Nation
stringclasses
106 values
Position
stringclasses
6 values
Age
int64
15
41
Matches Played
int64
1
38
Starts
int64
0
38
Minutes
stringlengths
1
5
90s Played
float64
0
38
Goals
int64
0
29
Assists
int64
0
18
Goals + Assists
int64
0
47
Non-Penalty Goals
int64
0
24
Penalty Goals Made
int64
0
9
Penalty Attempts
int64
0
9
Yellow Cards
int64
0
15
Red Cards
int64
0
3
xG
float64
0
27.1
npxG
float64
0
24
xAG
float64
0
14.2
npxG + xAG
float64
0
32.4
Progressive Carries
int64
0
181
Progressive Passes
int64
0
360
Progressive Receives
int64
0
488
Goals Per 90
float64
0
2.43
Assists Per 90
float64
0
1.01
Goals + Assists Per 90
float64
0
2.43
Non-Penalty Goals Per 90
float64
0
2.43
Non-Penalty Goals + Assists Per 90
float64
0
2.43
xG Per 90
float64
0
3.53
xAG Per 90
float64
0
2.47
xG + xAG Per 90
float64
0
3.53
npxG Per 90
float64
0
3.53
npxG + xAG Per 90
float64
0
3.53
0
Mohamed Salah
EGY
AT
32
38
38
3,371
37.5
29
18
47
20
9
9
1
0
25.2
18.2
14.2
32.4
154
144
488
0.77
0.48
1.25
0.53
1.01
0.67
0.38
1.05
0.49
0.87
1
Virgil van Dijk
NED
DF
33
37
37
3,330
37
3
1
4
3
0
0
5
0
2.2
2.2
0.7
3
22
198
6
0.08
0.03
0.11
0.08
0.11
0.06
0.02
0.08
0.06
0.08
2
Ryan Gravenberch
NED
MT
22
37
37
3,160
35.1
0
4
4
0
0
0
6
1
1.1
1.1
3.1
4.2
70
181
55
0
0.11
0.11
0
0.11
0.03
0.09
0.12
0.03
0.12
3
Alexis Mac Allister
ARG
MT
25
35
30
2,599
28.9
5
5
10
5
0
0
6
0
2.8
2.8
4.7
7.5
36
177
80
0.17
0.17
0.35
0.17
0.35
0.1
0.16
0.26
0.1
0.26
4
Ibrahima Konaté
FRA
DF
25
31
30
2,560
28.4
1
2
3
1
0
0
5
0
1.7
1.7
1
2.7
25
115
3
0.04
0.07
0.11
0.04
0.11
0.06
0.03
0.1
0.06
0.1
5
Dominik Szoboszlai
HUN
MT
23
36
29
2,491
27.7
6
6
12
6
0
0
6
0
7.3
7.3
7.4
14.7
72
131
127
0.22
0.22
0.43
0.22
0.43
0.27
0.27
0.53
0.27
0.53
6
Andrew Robertson
SCO
DF
30
33
29
2,482
27.6
0
1
1
0
0
0
3
1
1.2
1.2
4.6
5.8
64
176
108
0
0.04
0.04
0
0.04
0.04
0.17
0.21
0.04
0.21
7
Alisson
BRA
GB
31
28
28
2,508
27.9
0
0
0
0
0
0
0
0
0
0
0.6
0.6
0
1
0
0
0
0
0
0
0
0.02
0.02
0
0.02
8
Luis Díaz
COL
AT
27
36
28
2,399
26.7
13
5
18
13
0
0
2
0
12
12
5
17.1
108
110
293
0.49
0.19
0.68
0.49
0.68
0.45
0.19
0.64
0.45
0.64
9
Trent Alexander-Arnold
ENG
DF
25
33
28
2,365
26.3
3
6
9
3
0
0
5
0
1.9
1.9
7.3
9.2
51
232
94
0.11
0.23
0.34
0.11
0.34
0.07
0.28
0.35
0.07
0.35
10
Cody Gakpo
NED
AT
25
35
23
1,935
21.5
10
4
14
10
0
0
5
0
7.1
7.1
4.4
11.5
59
52
278
0.47
0.19
0.65
0.47
0.65
0.33
0.2
0.53
0.33
0.53
11
Curtis Jones
ENG
MT,DF
23
33
19
1,712
19
3
3
6
3
0
0
3
1
4.3
4.3
1.1
5.4
30
117
79
0.16
0.16
0.32
0.16
0.32
0.23
0.06
0.29
0.23
0.29
12
Diogo Jota
POR
AT
27
26
14
1,196
13.3
6
3
9
6
0
0
2
0
7.9
7.9
1.8
9.8
37
34
88
0.45
0.23
0.68
0.45
0.68
0.6
0.14
0.74
0.6
0.74
13
Caoimhín Kelleher
IRL
GB
25
10
10
900
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
14
Kostas Tsimikas
GRE
DF
28
18
9
837
9.3
0
1
1
0
0
0
2
0
0.4
0.4
2.1
2.5
17
76
43
0
0.11
0.11
0
0.11
0.04
0.23
0.27
0.04
0.27
15
Darwin Núñez
URU
AT
25
30
8
1,133
12.6
5
2
7
5
0
0
8
0
5.8
5.8
1.3
7.1
23
27
78
0.4
0.16
0.56
0.4
0.56
0.46
0.1
0.57
0.46
0.57
16
Conor Bradley
NIR
DF
21
19
7
754
8.4
0
2
2
0
0
0
4
0
0.7
0.7
1.4
2.1
35
33
39
0
0.24
0.24
0
0.24
0.08
0.17
0.25
0.08
0.25
17
Joe Gomez
ENG
DF
27
9
6
519
5.8
0
0
0
0
0
0
1
0
0.3
0.3
0.1
0.4
5
35
2
0
0
0
0
0
0.06
0.02
0.08
0.06
0.08
18
Jarell Quansah
ENG
DF
21
13
4
495
5.5
0
0
0
0
0
0
2
0
0.1
0.1
0.1
0.2
3
19
4
0
0
0
0
0
0.02
0.02
0.04
0.02
0.04
19
Harvey Elliott
ENG
MT
21
18
2
371
4.1
1
2
3
1
0
0
1
0
1.8
1.8
1.1
2.8
10
44
30
0.24
0.49
0.73
0.24
0.73
0.43
0.26
0.69
0.43
0.69
20
Wataru Endo
JPN
MT,DF
31
20
1
273
3
0
0
0
0
0
0
0
0
0
0
0.1
0.1
1
19
8
0
0
0
0
0
0
0.02
0.02
0
0.02
21
Federico Chiesa
ITA
AT
26
6
1
108
1.2
0
0
0
0
0
0
0
0
0.3
0.3
0.2
0.5
3
3
7
0
0
0
0
0
0.28
0.15
0.43
0.28
0.43
22
Vitezslav Jaros
CZE
GB
23
1
0
12
0.1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
23
Jayden Danns
ENG
MT
18
1
0
11
0.1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
24
Mohamed Salah
EGY
AT
32
38
38
3,371
37.5
29
18
47
20
9
9
1
0
25.2
18.2
14.2
32.4
154
144
488
0.77
0.48
1.25
0.53
1.01
0.67
0.38
1.05
0.49
0.87
25
Virgil van Dijk
NED
DF
33
37
37
3,330
37
3
1
4
3
0
0
5
0
2.2
2.2
0.7
3
22
198
6
0.08
0.03
0.11
0.08
0.11
0.06
0.02
0.08
0.06
0.08
26
Ryan Gravenberch
NED
MT
22
37
37
3,160
35.1
0
4
4
0
0
0
6
1
1.1
1.1
3.1
4.2
70
181
55
0
0.11
0.11
0
0.11
0.03
0.09
0.12
0.03
0.12
27
Alexis Mac Allister
ARG
MT
25
35
30
2,599
28.9
5
5
10
5
0
0
6
0
2.8
2.8
4.7
7.5
36
177
80
0.17
0.17
0.35
0.17
0.35
0.1
0.16
0.26
0.1
0.26
28
Ibrahima Konaté
FRA
DF
25
31
30
2,560
28.4
1
2
3
1
0
0
5
0
1.7
1.7
1
2.7
25
115
3
0.04
0.07
0.11
0.04
0.11
0.06
0.03
0.1
0.06
0.1
29
Dominik Szoboszlai
HUN
MT
23
36
29
2,491
27.7
6
6
12
6
0
0
6
0
7.3
7.3
7.4
14.7
72
131
127
0.22
0.22
0.43
0.22
0.43
0.27
0.27
0.53
0.27
0.53
30
Andrew Robertson
SCO
DF
30
33
29
2,482
27.6
0
1
1
0
0
0
3
1
1.2
1.2
4.6
5.8
64
176
108
0
0.04
0.04
0
0.04
0.04
0.17
0.21
0.04
0.21
31
Alisson
BRA
GB
31
28
28
2,508
27.9
0
0
0
0
0
0
0
0
0
0
0.6
0.6
0
1
0
0
0
0
0
0
0
0.02
0.02
0
0.02
32
Luis Díaz
COL
AT
27
36
28
2,399
26.7
13
5
18
13
0
0
2
0
12
12
5
17.1
108
110
293
0.49
0.19
0.68
0.49
0.68
0.45
0.19
0.64
0.45
0.64
33
Trent Alexander-Arnold
ENG
DF
25
33
28
2,365
26.3
3
6
9
3
0
0
5
0
1.9
1.9
7.3
9.2
51
232
94
0.11
0.23
0.34
0.11
0.34
0.07
0.28
0.35
0.07
0.35
34
Cody Gakpo
NED
AT
25
35
23
1,935
21.5
10
4
14
10
0
0
5
0
7.1
7.1
4.4
11.5
59
52
278
0.47
0.19
0.65
0.47
0.65
0.33
0.2
0.53
0.33
0.53
35
Curtis Jones
ENG
MT,DF
23
33
19
1,712
19
3
3
6
3
0
0
3
1
4.3
4.3
1.1
5.4
30
117
79
0.16
0.16
0.32
0.16
0.32
0.23
0.06
0.29
0.23
0.29
36
Diogo Jota
POR
AT
27
26
14
1,196
13.3
6
3
9
6
0
0
2
0
7.9
7.9
1.8
9.8
37
34
88
0.45
0.23
0.68
0.45
0.68
0.6
0.14
0.74
0.6
0.74
37
Caoimhín Kelleher
IRL
GB
25
10
10
900
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
38
Kostas Tsimikas
GRE
DF
28
18
9
837
9.3
0
1
1
0
0
0
2
0
0.4
0.4
2.1
2.5
17
76
43
0
0.11
0.11
0
0.11
0.04
0.23
0.27
0.04
0.27
39
Darwin Núñez
URU
AT
25
30
8
1,133
12.6
5
2
7
5
0
0
8
0
5.8
5.8
1.3
7.1
23
27
78
0.4
0.16
0.56
0.4
0.56
0.46
0.1
0.57
0.46
0.57
40
Conor Bradley
NIR
DF
21
19
7
754
8.4
0
2
2
0
0
0
4
0
0.7
0.7
1.4
2.1
35
33
39
0
0.24
0.24
0
0.24
0.08
0.17
0.25
0.08
0.25
41
Joe Gomez
ENG
DF
27
9
6
519
5.8
0
0
0
0
0
0
1
0
0.3
0.3
0.1
0.4
5
35
2
0
0
0
0
0
0.06
0.02
0.08
0.06
0.08
42
Jarell Quansah
ENG
DF
21
13
4
495
5.5
0
0
0
0
0
0
2
0
0.1
0.1
0.1
0.2
3
19
4
0
0
0
0
0
0.02
0.02
0.04
0.02
0.04
43
Harvey Elliott
ENG
MT
21
18
2
371
4.1
1
2
3
1
0
0
1
0
1.8
1.8
1.1
2.8
10
44
30
0.24
0.49
0.73
0.24
0.73
0.43
0.26
0.69
0.43
0.69
44
Wataru Endo
JPN
MT,DF
31
20
1
273
3
0
0
0
0
0
0
0
0
0
0
0.1
0.1
1
19
8
0
0
0
0
0
0
0.02
0.02
0
0.02
45
Federico Chiesa
ITA
AT
26
6
1
108
1.2
0
0
0
0
0
0
0
0
0.3
0.3
0.2
0.5
3
3
7
0
0
0
0
0
0.28
0.15
0.43
0.28
0.43
46
Vitezslav Jaros
CZE
GB
23
1
0
12
0.1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
47
Jayden Danns
ENG
MT
18
1
0
11
0.1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
48
David Raya
ESP
GB
28
38
38
3,420
38
0
0
0
0
0
0
3
0
0
0
0
0
0
14
0
0
0
0
0
0
0
0
0
0
0
49
William Saliba
FRA
DF
23
35
35
3,039
33.8
2
0
2
2
0
0
2
1
2.3
2.3
0.9
3.1
16
138
6
0.06
0
0.06
0.06
0.06
0.07
0.03
0.09
0.07
0.09
50
Declan Rice
ENG
MT
25
35
33
2,825
31.4
4
7
11
4
0
0
7
1
3.5
3.5
6.6
10.1
90
192
94
0.13
0.22
0.35
0.13
0.35
0.11
0.21
0.32
0.11
0.32
51
Thomas Partey
GHA
MT,DF
31
35
31
2,797
31.1
4
2
6
4
0
0
4
0
2.3
2.3
2.1
4.3
36
185
48
0.13
0.06
0.19
0.13
0.19
0.07
0.07
0.14
0.07
0.14
52
Leandro Trossard
BEL
AT
29
38
28
2,546
28.3
8
7
15
8
0
0
4
1
7.2
7.2
6.1
13.3
80
101
226
0.28
0.25
0.53
0.28
0.53
0.25
0.22
0.47
0.25
0.47
53
Gabriel Magalhães
BRA
DF
26
28
28
2,363
26.3
3
1
4
3
0
0
4
0
2.6
2.6
0.9
3.5
10
126
11
0.11
0.04
0.15
0.11
0.15
0.1
0.03
0.13
0.1
0.13
54
Jurriën Timber
NED
DF
23
30
27
2,417
26.9
1
3
4
1
0
0
7
0
1.2
1.2
0.8
2.1
57
146
104
0.04
0.11
0.15
0.04
0.15
0.05
0.03
0.08
0.05
0.08
55
Martin Ødegaard
NOR
MT
25
30
26
2,325
25.8
3
8
11
2
1
1
4
0
4.8
4
5.4
9.5
92
258
154
0.12
0.31
0.43
0.08
0.39
0.19
0.21
0.4
0.16
0.37
56
Mikel Merino
ESP
MT,AT
28
28
17
1,586
17.6
7
2
9
7
0
0
4
1
5.9
5.9
2
7.9
11
69
94
0.4
0.11
0.51
0.4
0.51
0.34
0.11
0.45
0.34
0.45
57
Myles Lewis-Skelly
ENG
DF
17
23
15
1,369
15.2
1
0
1
1
0
0
3
2
0.2
0.2
0.4
0.6
37
71
37
0.07
0
0.07
0.07
0.07
0.01
0.03
0.04
0.01
0.04
58
Ben White
ENG
DF
26
17
13
1,198
13.3
0
2
2
0
0
0
2
0
0.5
0.5
1.4
1.8
23
59
42
0
0.15
0.15
0
0.15
0.03
0.1
0.14
0.03
0.14
59
Riccardo Calafiori
ITA
DF
22
19
11
983
10.9
2
1
3
2
0
0
4
0
0.9
0.9
0.3
1.1
22
54
29
0.18
0.09
0.27
0.18
0.27
0.08
0.03
0.11
0.08
0.11
60
Jakub Kiwior
POL
DF
24
17
10
1,122
12.5
1
0
1
1
0
0
1
0
0.2
0.2
0.3
0.5
5
48
1
0.08
0
0.08
0.08
0.08
0.01
0.03
0.04
0.01
0.04
61
Jorginho
ITA
MT
32
15
9
704
7.8
0
0
0
0
0
0
5
0
0.1
0.1
0.4
0.5
12
48
6
0
0
0
0
0
0.01
0.05
0.06
0.01
0.06
62
Gabriel Jesus
BRA
AT
27
17
6
608
6.8
3
0
3
3
0
0
4
0
3
3
0.7
3.7
15
19
57
0.44
0
0.44
0.44
0.44
0.44
0.1
0.54
0.44
0.54
63
Nathan Butler-Oyedeji
ENG
AT
21
1
0
7
0.1
0
0
0
0
0
0
0
0
0.1
0.1
0
0.1
0
0
0
0
0
0
0
0
0.94
0
0.94
0.94
0.94
64
Takehiro Tomiyasu
JPN
DF
25
1
0
7
0.1
0
0
0
0
0
0
0
0
0.2
0.2
0
0.2
0
1
0
0
0
0
0
0
2.37
0
2.37
2.37
2.37
65
Reiss Nelson
ENG
AT
24
1
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
66
Bruno Guimarães
BRA
MT
26
38
38
3,271
36.3
5
6
11
5
0
0
7
0
4.3
4.3
6.1
10.4
64
271
96
0.14
0.17
0.3
0.14
0.3
0.12
0.17
0.29
0.12
0.29
67
Dan Burn
ENG
DF
32
37
37
3,330
37
1
1
2
1
0
0
11
0
2
2
0.9
2.8
12
75
14
0.03
0.03
0.05
0.03
0.05
0.05
0.02
0.08
0.05
0.08
68
Alexander Isak
SWE
AT
24
34
34
2,756
30.6
23
6
29
19
4
4
1
0
20.3
17.2
4.3
21.6
83
88
217
0.75
0.2
0.95
0.62
0.82
0.66
0.14
0.81
0.56
0.7
69
Fabian Schär
SUI
DF
32
34
33
2,934
32.6
4
0
4
4
0
0
9
1
3.7
3.7
0.4
4.1
18
118
22
0.12
0
0.12
0.12
0.12
0.11
0.01
0.13
0.11
0.13
70
Valentino Livramento
ENG
DF
21
37
32
2,840
31.6
0
1
1
0
0
0
1
0
0.3
0.3
2.6
2.9
83
158
119
0
0.03
0.03
0
0.03
0.01
0.08
0.09
0.01
0.09
71
Jacob Murphy
ENG
AT
29
35
31
2,360
26.2
8
12
20
8
0
0
4
0
5.7
5.7
8.9
14.6
79
83
231
0.31
0.46
0.76
0.31
0.76
0.22
0.34
0.56
0.22
0.56
72
Joelinton
BRA
MT,AT
27
29
29
2,393
26.6
4
3
7
4
0
0
10
0
3.9
3.9
2.5
6.4
40
116
110
0.15
0.11
0.26
0.15
0.26
0.15
0.09
0.24
0.15
0.24
73
Sandro Tonali
ITA
MT
24
36
28
2,630
29.2
4
2
6
4
0
0
5
0
4.4
4.4
2.2
6.6
37
128
53
0.14
0.07
0.21
0.14
0.21
0.15
0.07
0.22
0.15
0.22
74
Nick Pope
ENG
GB
32
28
28
2,520
28
0
0
0
0
0
0
2
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
75
Lewis Hall
ENG
DF
19
27
24
2,189
24.3
0
4
4
0
0
0
3
0
0.4
0.4
4.3
4.7
41
123
80
0
0.16
0.16
0
0.16
0.02
0.18
0.19
0.02
0.19
76
Harvey Barnes
ENG
AT
26
33
17
1,755
19.5
9
4
13
9
0
0
0
0
7.2
7.2
4
11.2
93
83
192
0.46
0.21
0.67
0.46
0.67
0.37
0.2
0.57
0.37
0.57
77
Kieran Trippier
ENG
DF
33
25
14
1,309
14.5
0
3
3
0
0
0
1
0
0.1
0.1
1.4
1.5
26
117
58
0
0.21
0.21
0
0.21
0.01
0.1
0.1
0.01
0.1
78
Joe Willock
ENG
MT,AT
24
32
11
1,086
12.1
0
2
2
0
0
0
4
0
1.6
1.6
2.1
3.8
38
41
86
0
0.17
0.17
0
0.17
0.14
0.18
0.31
0.14
0.31
79
Martin Dúbravka
SVK
GB
35
10
10
900
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
80
Sean Longstaff
ENG
MT
26
25
8
798
8.9
0
0
0
0
0
0
2
0
0.6
0.6
0.2
0.8
4
40
22
0
0
0
0
0
0.07
0.02
0.09
0.07
0.09
81
Sven Botman
NED
DF
24
8
6
412
4.6
0
0
0
0
0
0
1
0
0.5
0.5
0.5
1.1
0
7
0
0
0
0
0
0
0.12
0.12
0.24
0.12
0.24
82
Lloyd Kelly
ENG
DF
25
10
4
303
3.4
0
1
1
0
0
0
2
0
0.4
0.4
0.5
0.9
0
9
5
0
0.3
0.3
0
0.3
0.12
0.14
0.26
0.12
0.26
83
Callum Wilson
ENG
AT
32
18
2
370
4.1
0
0
0
0
0
0
1
0
0.4
0.4
0.1
0.5
5
4
17
0
0
0
0
0
0.09
0.03
0.12
0.09
0.12
84
Emil Krafth
SWE
DF
29
12
2
342
3.8
0
0
0
0
0
0
2
0
0
0
0.1
0.1
5
8
3
0
0
0
0
0
0.01
0.02
0.03
0.01
0.03
85
Lewis Miley
ENG
MT
18
14
1
313
3.5
1
0
1
1
0
0
0
0
0.5
0.5
0
0.6
2
17
8
0.29
0
0.29
0.29
0.29
0.16
0.01
0.16
0.16
0.16
86
Miguel Almirón
PAR
AT
30
9
1
157
1.7
0
0
0
0
0
0
0
0
0.5
0.5
0.3
0.8
3
6
18
0
0
0
0
0
0.3
0.15
0.45
0.3
0.45
87
William Osula
DEN
AT
20
14
0
134
1.5
1
0
1
1
0
0
0
0
0.2
0.2
0.1
0.3
5
4
17
0.67
0
0.67
0.67
0.67
0.11
0.1
0.21
0.11
0.21
88
Matt Targett
ENG
DF
28
2
0
21
0.2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
89
Álex Remiro
ESP
GB
29
36
36
3,240
36
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
90
Martín Zubimendi
ESP
MT
25
36
33
2,962
32.9
2
1
3
2
0
0
6
0
2.6
2.6
1.1
3.7
38
195
43
0.06
0.03
0.09
0.06
0.09
0.08
0.03
0.11
0.08
0.11
91
Sergio Gómez
ESP
MT,DF
23
37
31
2,738
30.4
2
5
7
2
0
0
4
0
1.9
1.9
8.9
10.8
43
93
154
0.07
0.16
0.23
0.07
0.23
0.06
0.29
0.35
0.06
0.35
92
Jon Aramburu
VEN
DF
22
35
28
2,460
27.3
1
1
2
1
0
0
8
0
0.4
0.4
1.1
1.6
26
97
53
0.04
0.04
0.07
0.04
0.07
0.02
0.04
0.06
0.02
0.06
93
Mikel Oyarzabal
ESP
AT
27
35
28
2,250
25
9
3
12
5
4
4
4
1
9.9
6.8
2.4
9.2
31
28
133
0.36
0.12
0.48
0.2
0.32
0.4
0.1
0.5
0.27
0.37
94
Takefusa Kubo
JPN
MT,AT
23
36
27
2,372
26.4
5
0
5
5
0
0
5
0
3.6
3.6
4.5
8
133
110
218
0.19
0
0.19
0.19
0.19
0.14
0.17
0.31
0.14
0.31
95
Igor Zubeldia
ESP
DF
27
28
27
2,269
25.2
0
0
0
0
0
0
6
1
0.6
0.6
0.4
1.1
22
101
3
0
0
0
0
0
0.02
0.02
0.04
0.02
0.04
96
Javi López
ESP
DF
22
29
21
1,936
21.5
0
0
0
0
0
0
4
0
0.1
0.1
0.4
0.5
36
73
64
0
0
0
0
0
0.01
0.02
0.03
0.01
0.03
97
Luka Sučić
CRO
MT
21
29
21
1,792
19.9
1
1
2
1
0
0
4
0
3.3
3.3
2.6
5.9
30
79
56
0.05
0.05
0.1
0.05
0.1
0.17
0.13
0.3
0.17
0.3
98
Nayef Aguerd
MAR
DF
28
21
21
1,760
19.6
0
0
0
0
0
0
5
0
2.4
2.4
0.1
2.5
26
75
1
0
0
0
0
0
0.12
0.01
0.13
0.12
0.13
99
Brais Méndez
ESP
MT
27
27
19
1,531
17
3
2
5
3
0
0
4
0
3.5
3.5
2
5.5
32
91
86
0.18
0.12
0.29
0.18
0.29
0.21
0.12
0.33
0.21
0.33
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FBref Football Player Performance Dataset (2024-2025 Season)

Dataset Description

This dataset contains comprehensive performance statistics for 2273 professional football players during the 2024-2025 season. Sourced from FBref, it includes both traditional metrics (goals, assists) and advanced analytics (xG, xAG, progressive actions) across top European leagues.

  • Curated by: FBref
  • License: Publicly available football statistics (check FBref terms for redistribution)
  • Update Frequency: Seasonal
  • Dataset Size: 2273 players × 33 features

Key Features

  • Player metadata: Name, nationality, position, age
  • Match participation: Matches played, starts, minutes
  • Goal contributions: Goals, assists, non-penalty goals
  • Expected metrics: xG, xAG, npxG, npxG+xAG
  • Progressive actions: Carries, passes, receives
  • Disciplinary records: Yellow/red cards
  • Per-90-minute metrics: 16 efficiency statistics

Supported Tasks

  1. Player performance analysis
  2. Transfer market valuation
  3. Fantasy football optimization
  4. Positional comparison (Attackers vs. Midfielders vs. Defenders)
  5. Age-performance correlation studies

Dataset Structure

Data Fields

Field Name Description Type Example
Player Full player name string Mohamed Salah
Nation Nationality string EGY
Position Primary position(s) string AT (Attacker)
Age Player age int 32
Matches Played Total appearances int 38
Goals Total goals scored float 29
xG Expected goals float 25.2
Progressive Carries Ball advancement via dribbling int 154
Goals Per 90 Goals per 90 minutes float 0.77
... (33 fields total)

Data Splits

  • Single comprehensive file (PlayersFBREF.csv)
  • No predefined train/validation/test splits (recommended for exploratory analysis)

Dataset Creation

Curation Rationale

This dataset was compiled to:

  • Provide standardized player performance metrics
  • Enable quantitative comparison across leagues
  • Support data-driven football analysis
  • Facilitate academic research in sports analytics

Source Data

  • Source: FBref (https://fbref.com)
  • Coverage: Premier League, La Liga, Serie A, Bundesliga, Ligue 1
  • Time Period: 2024-2025 season
  • Player Selection: All players with significant minutes (≥ 200 mins)

Preprocessing

  1. International symbol standardization (e.g., "AT" for attacker)
  2. Minutes formatting (e.g., "3,371" → 3371)
  3. Per-90 metrics calculated from raw totals
  4. Duplicate entries consolidated (e.g., Salah appears once)

Known Limitations

  • Contains European league bias
  • Goalkeeper statistics are limited
  • Position classifications may oversimplify hybrid roles
  • Set-piece contributions not isolated

Usage Considerations

Ethical Considerations

  • Player data is publicly available professional information
  • Performance metrics shouldn't be used for personal criticism
  • Age data requires careful interpretation in analysis

Potential Biases

  • League coverage favors top 5 European competitions
  • Playing time bias (bench players underrepresented)
  • Metric weighting favors offensive contributions

Recommended Use Cases

  • Academic sports research
  • Fantasy football optimization
  • Player scouting and talent identification
  • Football analytics education

Additional Information

Citation Information

@dataset{fbref_player_performance_2025,
  author = {FBref},
  year = {2025},
  title = {European Football Player Statistics 2024-2025},
  howpublished = {https://fbref.com}
}
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