Refactor salary and projection calculations in 'exposure_spread' function to apply conditional logic based on 'type_var', improving accuracy for Showdown scenarios.

global_func/exposure_spread.py

@@ -153,9 +153,15 @@ def exposure_spread(working_frame, exposure_player, exposure_target, ignore_stac
     
     comparable_players = comparable_players.reset_index(drop=True)
     comp_salary_high = comparable_players['salary'][0]
-    comp_salary_low = comparable_players['salary'][0] - 500
+    if type_var == 'Showdown':
+        comp_salary_low = comparable_players['salary'][0] - 1000
+    else:
+        comp_salary_low = comparable_players['salary'][0] - 500
     comp_projection_high = comparable_players['median'][0]
-    comp_projection_low = comparable_players['median'][0] - (comparable_players['median'][0] * .75)
+    if type_var == 'Showdown':
+        comp_projection_low = comparable_players['median'][0] - (comparable_players['median'][0] * .5)
+    else:
+        comp_projection_low = comparable_players['median'][0] - (comparable_players['median'][0] * .75)
     # players can be eligible at multiple positions, so we need to find all the positions the player is eligible at
     # the position column can have positions designated as 1B/OF which means they are eligible at 1B and OF
     comp_player_position = comparable_players['position'].tolist()