Table:
Year

Team

Games

Passing

Rushing

Sacked

Fumbles

G
GS
Att
Comp
Pct
Yds
Avg
Long
TD
Int
Rtg
Att
Yds
Avg
TD
Sack
Yds
Fum
Lost

2004
NYG

9
7
197
95
48.2
1,043
5.3
52
6
9
55.4
6
35
5.8
0
13
83
3
1

2005
NYG

16
16
557
294
52.8
3,762
6.8
78
24
17
75.9
29
80
2.8
1
28
184
9
2

2006
NYG

16
16
522
301
57.7
3,244
6.2
55
24
18
77.0
25
21
0.8
0
25
186
9
2

2007
NYG

16
16
529
297
56.1
3,336
6.3
60
23
20
73.9
29
69
2.4
1
27
217
13
7

2008
NYG

16
16
479
289
60.3
3,238
6.8
48
21
10
86.4
20
10
0.5
1
27
174
5
2

2009
NYG

16
16
509
317
62.3
4,021
7.9
74
27
14
93.1
17
65
3.8
0
30
216
13
8

2010
NYG

16
16
539
339
62.9
4,002
7.4
92
31
25
85.3
32
70
2.2
0
16
117
7
5

2011
NYG

16
16
589
359
61.0
4,933
8.4
99
29
16
92.9
35
15
0.4
1
28
199
8
4

2012
NYG

16
16
536
321
59.9
3,948
7.4
80
26
15
87.2
20
30
1.5
0
19
136
4
1

2013
NYG

16
16
551
317
57.5
3,818
6.9
70
18
27
69.4
18
36
2.0
0
39
281
7
2

2014
NYG

16
16
601
379
63.1
4,410
7.3
80
30
14
92.1
12
31
2.6
1
28
187
7
4

2015
NYG

16
16
618
387
62.6
4,432
7.2
87
35
14
93.6
20
61
3.1
0
27
157
11
4

2016
NYG

16
16
598
377
63.0
4,027
6.7
75
26
16
86.0
21
-9
-0.4
0
21
142
7
4

2017
NYG

15
15
571
352
61.6
3,468
6.1
77
19
13
80.4
12
26
2.2
1
31
189
11
5

2018
NYG

16
16
576
380
66.0
4,299
7.5
58
21
11
92.4
15
20
1.3
1
47
358
7
4

Total
232
230
7,972
4,804
60.3
55,981
7.0
99
360
239
84.1
311
560
1.8
7
406
2,826
122
55

Based on the given table, what are the contents of the subsequent rows or columns?
the 5th column,
the 14th row,
the 16th column,

Requirements: Represent the cells in a row or a column with the JSON format {"row_id/column_id":"<row or column index>", "cell_list":"<a list of cells in this row/column>"}. For instance, {"row_id":"5", "cell_list": ["13", "england", "2023-1201"]}.

The extracted row or column contents are listed below.
For the 5th column: {"column_id": "5", "cell_list": ['passing', 'att', '197', '557', '522', '529', '479', '509', '539', '589', '536', '551', '601', '618', '598', '571', '576', '7,972']}
For the 14th row: {"row_id": "14", "cell_list": ['2015', 'nyg', '16', '16', '618', '387', '62.6', '4,432', '7.2', '87', '35', '14', '93.6', '20', '61', '3.1', '0', '27', '157', '11', '4']}
For the 16th column: {"column_id": "16", "cell_list": ['', 'avg', '5.8', '2.8', '0.8', '2.4', '0.5', '3.8', '2.2', '0.4', '1.5', '2.0', '2.6', '3.1', '-0.4', '2.2', '1.3', '1.8']}