How to build a hybrid_method that counts the number of records from the last X days?

I have a table of tennis matches and I would like to create a query field that counts the number of previous matches within a date range of the date of the focal match. For example:

+----------+------------+---------------------------+
| match_id |    date    | num_matches within 3 days |
+----------+------------+---------------------------+
|        1 | 01/01/2020 |                         0 |
|        2 | 02/01/2020 |                         1 |
|        3 | 03/01/2020 |                         2 |
|        4 | 05/01/2020 |                         2 |
|        5 | 05/01/2020 |                         3 |
|        6 | 10/01/2020 |                         0 |
+----------+------------+---------------------------+

I've tried using a correlated sub-query as set out here but I can't figure out how to create the conditions:

@hybrid_method
def match_count(self, timespan_days):
    cut_off = self.date_time_inferred - timedelta(days=timespan_days)
    return sum(x >= cut_off and <some_cond_for_less_than_current_match_date> for x in self.date_time_inferred)

@match_count.expression
def match_count(cls, timespan_days):
    cut_off = cls.date_time_inferred - timedelta(days=timespan_days)
    return (
        select(func.count(cls.date_time_inferred)).
        where(
            and_(
                cls.date_time_inferred.__ge__(cut_off),
                cls.date_time_inferred.__lt__(<not_sure_what_goes_here>),
            )
        ).label('match_count')
    )

In trialling simpler forms of the above I also kept getting the following error:

sqlalchemy.exc.ArgumentError: columns argument to select() must be a Python list or other iterable

On the code:

select(func.count(cls.date))

So I'm clearly doing a whole heap of stuff wrong.

Hopefully someone can help me understand how to fix this? Also very open to different ways to accomplish the same thing. I would like to stick with a hybrid attribute though...

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