Refactor exposure_spread function to improve readability by consolidating conditional checks for stacking sports and comparable players filtering.

global_func/exposure_spread.py

@@ -272,13 +272,13 @@ def exposure_spread(working_frame, exposure_player, exposure_target, exposure_st
                         (projections_df['salary'] <= comp_salary_high + (salary_max - working_frame['salary'][row])) &
                         (projections_df['position'].apply(lambda x: has_position_overlap(x, comp_player_position)))
                     ]
-                if sport_var in stacking_sports:
                     if sport_var in stacking_sports:
-                        if working_frame.iloc[row]['Size'] == 5 and comp_team != working_frame.iloc[row]['Stack']:
-                            remove_mask = comparable_players.apply(
-                                lambda player_row: not any(team in list(player_row) for team in [working_frame.iloc[row]['Stack']]), axis=1
-                            )
-                            comparable_players = comparable_players[remove_mask]
+                        if sport_var in stacking_sports:
+                            if working_frame.iloc[row]['Size'] == 5 and comp_team != working_frame.iloc[row]['Stack']:
+                                remove_mask = comparable_players.apply(
+                                    lambda player_row: not any(team in list(player_row) for team in [working_frame.iloc[row]['Stack']]), axis=1
+                                )
+                                comparable_players = comparable_players[remove_mask]
                 
                 if remove_teams is not None:
                     remove_mask = comparable_players.apply(