Table:
Club

Season

League

League

FA Cup

League Cup

Other

Total

Apps
Goals
Apps
Goals
Apps
Goals
Apps
Goals
Apps
Goals

Port Vale
1992–93
Division 2
41
15
4
1
2
1
9[a][b]
2[a]
56
18

1993–94
Division 2
42
13
2
0
2
1
4[a]
2[a]
50
16

Total

83
28
6
1
4
2
13
4
106
35

Sheffield Wednesday
1994–95
Premier League
14
1
0
0
4
1
—
18
2

Aston Villa
1994–95
Premier League
22
1
2
0
0
0
—
24
1

1995–96
Premier League
25
3
3
1
6
1
—
34
5

1996–97
Premier League
34
2
0
0
3
1
—
37
3

1997–98[14]
Premier League
32
6
3
0
1
0
8[c]
3[c]
44
9

1998–99[15]
Premier League
33
4
1
0
1
0
3[c]
0
38
4

1999–2000[16]
Premier League
29
5
5
0
8
5
—
42
10

2000–01[17]
Premier League
29
4
1
0
1
0
4[d]
1[d]
35
5

2001–02[18]
Premier League
16
3
1
1
1
0
—
18
4

2002–03[19]
Premier League
13
0
1
0
2
1
3[d]
1[d]
19
2

Total

233
28
17
2
23
8
18
5
291
43

Derby County
2003–04[20]
Division 1
42
11
1
0
1
1
—
44
12

2004–05[21]
Championship
39
3
2
0
1
0
2[b]
0
44
3

Total

81
14
3
0
2
1
2
0
88
15

Northampton Town
2005–06[22]
League Two
33
7
3
0
1
0
1[a]
0
38
7

2006–07[23]
League One
33
1
3
0
0
0
—
36
1

Total

66
8
6
0
1
0
1
0
74
8

Career total

477
79
32
3
34
12
34
9
577
103

This image illustrates a table. Find the cells in column 9, return their values. Output the cell values in a column as JSON in the format {"column_id":"<column index>", "cell_list":"<a list of cells in this column>"}, e.g., {"column_id":"3", "cell_list": ["123.89", "News gathering", "selected tools"]}.

The target cell values of column 9: {"column_id": "9", "cell_list": ['', 'goals', '1', '1', '2', '1', '0', '1', '1', '0', '0', '5', '0', '0', '1', '8', '1', '0', '1', '0', '0', '0', '12']}