Update player column selection in predict_dupes function to include an additional player, ensuring compatibility with the updated League of Legends (LOL) logic for enhanced prediction accuracy.

global_func/predict_dupes.py

@@ -490,7 +490,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
                 own_columns = ['CPT_Own', 'TOP_Own', 'JNG_Own', 'MID_Own', 'ADC_Own', 'SUP_Own', 'Team_Own']
                 calc_columns = ['own_product', 'own_average', 'own_sum', 'avg_own_rank', 'dupes_calc', 'low_own_count', 'Ref_Proj', 'Max_Proj', 'Min_Proj', 'Avg_Ref', 'own_ratio']
                 # Get the original player columns (first 6 columns excluding salary, median, Own)
-                player_columns = [col for col in portfolio.columns[:6] if col not in ['salary', 'median', 'Own']]
+                player_columns = [col for col in portfolio.columns[:7] if col not in ['salary', 'median', 'Own']]
                 
                 flex_ownerships = pd.concat([
                     portfolio.iloc[:,1].map(maps_dict['own_map']),