Table:
Year

Division

League

Reg. Season

Playoffs

National Cup

1934/35

N/A

ASL

6th

No playoff

?

1935/36

N/A

ASL

2nd

No playoff

?

1936/37

N/A

ASL

2nd, American

1st Round

?

1937/38

N/A

ASL

4th, American

Did not qualify

?

1938/39

N/A

ASL

5th, American

Did not qualify

?

1939/40

N/A

ASL

2nd(t)

No playoff

Co-champion

1940/41

N/A

ASL

3rd

No playoff

?

1941/42

N/A

ASL

5th

No playoff

?

1942/43

N/A

ASL

5th

No playoff

?

1943/44

N/A

ASL

3rd

No playoff

?

1944/45

N/A

ASL

4th

No playoff

?

1945/46

N/A

ASL

1st

Champion (no playoff)

?

1946/47

N/A

ASL

4th

No playoff

?

1947/48

N/A

ASL

4th

No playoff

?

1948/49

N/A

ASL

Withdrew after 3 games

N/A

N/A

Return the cells' value in the subsequent table rows or columns:
the 10th row
the 16th row
the 1st column
the 3rd column

Output the cell values in each row or column as JSON in the format {"row_id/column_id":"<row or column index>", "cell_list":"<a list of cells in this row/column>"}, e.g., {"column_id":"3", "cell_list": ["123.89", "News gathering", "selected tools"]}.

The extracted row or column contents are listed below.
For the 10th row: {"row_id": "10", "cell_list": ['1942/43', 'N/A', 'ASL', '5th', 'No playoff', '?']}
For the 16th row: {"row_id": "16", "cell_list": ['1948/49', 'N/A', 'ASL', 'Withdrew after 3 games', 'N/A', 'N/A']}
For the 1st column: {"column_id": "1", "cell_list": ['Year', '1934/35', '1935/36', '1936/37', '1937/38', '1938/39', '1939/40', '1940/41', '1941/42', '1942/43', '1943/44', '1944/45', '1945/46', '1946/47', '1947/48', '1948/49']}
For the 3rd column: {"column_id": "3", "cell_list": ['League', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL', 'ASL']}