I suggest you use str.extract + combine_first
df['fecha_debut'] = df['Debut'].str.extract(r'(d{4})').combine_first(df['Debut Deportivo'].str.extract(r'(d{4})'))
print(df)
Output
Debut Debut Deportivo fecha_debut
0 27 de mayo de 2006 2006(UD Vecindario) 2006
1 21 de agosto de 2010 11 de agosto de 2010(Portuguesa) 2010
2 21 de agosto de 2010 NaN 2010
3 NaN NaN NaN
For more on how to work with strings in pandas see this.
UPDATE
If you need the column to be numeric you could do:
df['fecha_debut'] = pd.to_numeric(df['fecha_debut']).astype(pd.Int32Dtype())
Note that because you have missing values in the column it cannot be of type int32. It can be either nullable integer or float. For more on working with missing data see this.
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