Creating multiple dataframes from a stored procedure

I’m working with a stored procedure in which I pass it a start and end date and it returns data. Im passing it ten different dates and making ten calls to it, see below:

match1 = sp_data(startDate = listOfDates[0], endDate=listOfDates[0])
match2 = sp_data(startDate = listOfDates[1], endDate=listOfDates[1])
match3 = sp_data(startDate = listOfDates[2], endDate=listOfDates[2])
match4 = sp_data(startDate = listOfDates[3], endDate=listOfDates[3])
match5 = sp_data(startDate = listOfDates[4], endDate=listOfDates[4])
match6 = sp_data(startDate = listOfDates[5], endDate=listOfDates[5])
match7 = sp_data(startDate = listOfDates[6], endDate=listOfDates[6])
match8 = sp_data(startDate = listOfDates[7], endDate=listOfDates[7])
match9 = sp_data(startDate = listOfDates[8], endDate=listOfDates[8])
match10 = sp_data(startDate = listOfDates[9], endDate=listOfDates[9])

See listOfDates pandas series below:

print(listOfDates)

0    20220524
1    20220613
2    20220705
3    20220713
4    20220720
5    20220805
6    20220903
7    20220907
8    20220928
9    20221024
Name: TradeDate, dtype: object

Is there a better and more efficient way of doing this? Potentially in a loop of some kind?

Any help greatly appreciated, thanks!