Table:
Club	Season	League	Cup1	League Cup2	Continental3	Other4	Total

League	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals

Lyon	2013–14	Ligue 1	14	1	1	0	1	0	9	0	—	25	1

2014–15	38	7	2	0	0	0	3	0	—	43	7

2015–16	33	5	4	1	2	1	6	0	0	0	45	7

2016–17	31	8	1	1	0	0	14	4	1	1	47	14

Total	116	21	8	2	3	1	32	4	1	1	160	29

Bayern Munich	2017–18	Bundesliga	26	6	5	1	—	8	3	1	0	40	10

2018–19	2	1	1	0	—	0	0	0	0	3	1

Total	28	7	6	1	—	8	3	1	0	43	11

Career total	144	28	14	3	3	1	40	7	2	1	203	40

Examine the given table and extract the contents of in the specific rows or columns, denoted by row or column indices. 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"]}.
Specified rows or columns:
the 15th column,
the 9th column,
the 11th row,
the 1st row,

The extracted row or column contents are listed below.
For the 15th column: {"column_id": "15", "cell_list": ['', 'goals', '1', '7', '7', '14', '29', '10', '1', '11', '40']}
For the 9th column: {"column_id": "9", "cell_list": ['', 'goals', '0', '0', '1', '0', '1', '', '', '', '1']}
For the 11th row: {"row_id": "11", "cell_list": ['career total', '', '', '144', '28', '14', '3', '3', '1', '40', '7', '2', '1', '203', '40']}
For the 1st row: {"row_id": "1", "cell_list": ['club', 'season', 'league', '', '', 'cup1', '', 'league cup2', '', 'continental3', '', 'other4', '', 'total', '']}