Table:
Club

Season

Division

League

FA Cup

Other

Total

Apps
Goals
Apps
Goals
Apps
Goals
Apps
Goals

Wigan Athletic (loan)

1982–83

Third Division

5
1
0
0
0
0
5
1

Rotherham United (loan)

1982–83

Second Division

4
0
0
0
0
0
4
0

Everton

1980–81

First Division

11
0
0
0
0
0
11
0

1981–82

First Division

13
0
1
0
2
0
16
0

1982–83

First Division

0
0
0
0
0
0
0
0

Total

24
0
1
0
2
0
27
0

Preston North End

1982–83

Third Division

19
0
0
0
0
0
19
0

1983–84

Third Division

19
0
1
0
5
0
25
0

Total

38
0
1
0
5
0
44
0

Port Vale (loan)

1984–85

Fourth Division

3
0
0
0
0
0
3
0

Bolton Wanderers

1984–85

Third Division

4
0
0
0
1
0
5
0

Stockport County

1984–85

Fourth Division

12
2
0
0
0
0
12
2

1985–86

Fourth Division

1
0
0
0
1
0
2
0

Total

13
2
0
0
1
0
14
2

Southport

1985–86[10]

Northern Premier League

11
1
0
0
2
0
13
1

1986–87[11]

Northern Premier League

37
4
9
1
17
0
63
5

1987–88[12]

Northern Premier League

21
0
1
0
4
0
26
0

Total

69
5
10
1
23
0
102
6

Macclesfield Town

1987–88[13]

Conference

12
0
0
0
3
1
15
1

1988–89[14]

Conference

2
0
0
0
0
0
2
0

Total

14
0
0
0
3
1
17
1

Southport

1993–94[15]

Conference

26
1
0
0
10
0
36
1

1994–95[16]

Conference

38
1
2
0
6
0
46
1

1995–96[17]

Conference

36
1
1
0
10
0
47
1

Total

100
3
3
0
26
0
129
3

Career total

274
11
15
1
61
1
350
13

Based on the table image, your task is to extract the cells' values in row 22. Output the cell values in a row as JSON in the format {"row_id":"<row index>", "cell_list":"<a list of cells in this row>"}, e.g., {"row_id":"3", "cell_list": ["123.89", "News gathering", "selected tools"]}.

The target cell values of row 22: {"row_id": "22", "cell_list": ['', '1988-89', 'conference', '2', '0', '0', '0', '0', '0', '2', '0']}