Refactor dupes calculation in app.py to improve accuracy by adjusting the Dupes metric scaling based on sharp_split. This change enhances the precision of player ownership analysis and contest lineup simulations by ensuring the Dupes values are rounded appropriately after scaling.

app.py

@@ -585,6 +585,7 @@ with tab1:
                         0, 
                         np.round(Sim_Winner_Frame['dupes_calc'], 0) - 1
                     )
+                    Sim_Winner_Frame['Dupes'] = Sim_Winner_Frame['Dupes'] * ((500000 / sharp_split) / 2)
                 elif sim_site_var1 == 'Draftkings':
                     dup_count_columns = ['CPT_Own_percent_rank', 'FLEX1_Own_percent_rank', 'FLEX2_Own_percent_rank', 'FLEX3_Own_percent_rank', 'FLEX4_Own_percent_rank', 'FLEX5_Own_percent_rank']
                     own_columns = ['CPT_Own', 'FLEX1_Own', 'FLEX2_Own', 'FLEX3_Own', 'FLEX4_Own', 'FLEX5_Own']
@@ -617,7 +618,8 @@ with tab1:
                         0, 
                         np.round(Sim_Winner_Frame['dupes_calc'], 0) - 1
                     )
-                Sim_Winner_Frame['Dupes'] = np.round(Sim_Winner_Frame['Dupes'].astype(np.float32) * ((500000 / strength_var1) / 2), 0)
+                    Sim_Winner_Frame['Dupes'] = Sim_Winner_Frame['Dupes'] * ((500000 / sharp_split) / 2)
+                Sim_Winner_Frame['Dupes'] = np.round(Sim_Winner_Frame['Dupes'], 0)
                 Sim_Winner_Frame = Sim_Winner_Frame.drop(columns=dup_count_columns)
                 Sim_Winner_Frame = Sim_Winner_Frame.drop(columns=own_columns)
                 Sim_Winner_Frame = Sim_Winner_Frame.drop(columns=calc_columns)