Table:
Club	Season	League	Cup	Continental	Other	Total

Division	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals

San Lorenzo	2002–03	Argentine Primera División	11	0	—	1	0	—	12	0

2003–04	Argentine Primera División	27	3	—	3	0	—	30	3

2004–05	Argentine Primera División	28	5	—	9	0	—	37	5

Total	66	8	0	0	13	0	0	0	79	8

Espanyol	2005–06	La Liga	27	2	1	0	7	0	—	35	2

2006–07	La Liga	20	0	0	0	9	0	2	0	31	0

2007–08	La Liga	32	1	4	0	—	36	1

Total	79	3	5	0	16	0	2	0	102	3

Manchester City	2008–09	Premier League	29	1	2	0	11	0	—	42	1

2009–10	Premier League	27	0	8	0	—	35	0

2010–11	Premier League	26	2	8	0	11	0	—	45	2

2011–12	Premier League	21	1	5	0	5	0	0	0	31	1

2012–13	Premier League	30	2	6	1	5	0	1	0	42	3

2013–14	Premier League	35	1	7	0	6	0	—	48	1

2014–15	Premier League	29	1	1	0	6	1	0	0	36	2

2015–16	Premier League	13	0	6	0	3	0	—	22	0

2016–17	Premier League	20	1	5	1	7	0	—	32	2

Total	230	9	48	2	54	1	1	0	333	12

West Ham United	2017–18	Premier League	37	0	2	0	—	39	0

2018–19	Premier League	25	0	1	0	—	26	0

Total	62	0	3	0	0	0	0	0	65	0

Career total	437	20	56	2	83	1	3	0	579	23

Analyze the provided table and extract the contents of cells located at the specified positions, identified by row and column indices. Represent each cell value in the JSON format {"row_id":"m", "column_id":"n", "cell_value":"<Corresponding Cell Value>"}. For instance, {"row_id":"5", "column_id":"4", "cell_value":"missouri 4"}.
Positions:
row 7 and column 2,
row 10 and column 4,
row 9 and column 11,
row 8 and column 6,

The extracted cell contents are listed below.
{"row_id":"7", "column_id":"2", "cell_value":"2005-06"}
{"row_id":"10", "column_id":"4", "cell_value":"79"}
{"row_id":"9", "column_id":"11", "cell_value":"1"}
{"row_id":"8", "column_id":"6", "cell_value":"0"}