Table:
Club

Season

League

Cup

League Cup

Total

Division

Apps
Goals

Apps
Goals

Apps
Goals

Apps
Goals

Bayer Leverkusen II
1991–92
Oberliga Nordrhein

16

—

16

Wuppertaler SV
1992–93
2. Bundesliga
9
3

—
9
3

Pohang Steelers
1993
K League
0
0
—
1
0
1
0

1994
14
5
—
0
0
14
5

1995
24
11
—
2
0
26
11

1996
13
10
0
0
5
3
18
13

1997
0
0
1
0
1
0
2
0

1998
1
0
0
0
2
2
3
2

Total
52
26
1
0
11
5
64
31

Cerezo Osaka
1998
J1 League
11
6
0
0
0
0
11
6

1999
25
24
0
0
2
3
27
27

Total
36
30
0
0
2
3
38
33

Suwon Samsung
2000
K League
0
0
0
0
1
0
1
0

Kashiwa Reysol
2000
J1 League
6
1
0
0
1
0
7
1

2001
21
10
0
0
4
0
25
10

2002
7
1
0
0
0
0
7
1

Total
34
12
0
0
5
0
39
12

Chunnam Dragons
2002
K League
0
0
0
0
0
0
0
0

Germany

9
3

—
9
3

Korea Republic

52
26
1
0
12
5
65
31

Japan

70
42
0
0
7
3
77
45

Career total

131
71
0
0
19
8
151
79

Analyze the provided table and extract the contents of cells located at the specified positions, identified by row and column indices. Format each cell value as a JSON, using the structure {"row_id":"m", "column_id":"n", "cell_value":"<Corresponding Cell Value>"}.
Positions:
row 7 and column 6,
row 2 and column 6,
row 10 and column 8,
row 18 and column 11,
row 2 and column 7,
row 12 and column 1,
row 24 and column 11,
row 4 and column 8,

The target cell values are as follows:
{"row_id":"7", "column_id":"6", "cell_value":"-"}
{"row_id":"2", "column_id":"6", "cell_value":"apps"}
{"row_id":"10", "column_id":"8", "cell_value":"2"}
{"row_id":"18", "column_id":"11", "cell_value":"1"}
{"row_id":"2", "column_id":"7", "cell_value":"goals"}
{"row_id":"12", "column_id":"1", "cell_value":"cerezo osaka"}
{"row_id":"24", "column_id":"11", "cell_value":"79"}
{"row_id":"4", "column_id":"8", "cell_value":"-"}