Update calculation of 'Lineup Edge' in predict_dupes.py to scale by 10000 for improved accuracy in contest performance metrics.

global_func/predict_dupes.py

@@ -435,7 +435,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
     
     portfolio['low_own_count'] = portfolio[own_columns].apply(lambda row: (row < 0.10).sum(), axis=1)
     portfolio['Finish_percentile'] = portfolio.apply(lambda row: row['Finish_percentile'] if row['low_own_count'] <= 0 else row['Finish_percentile'] / row['low_own_count'], axis=1)
-    portfolio['Lineup Edge'] = (portfolio['Win%'] * ((.5 - portfolio['Finish_percentile']) * (Contest_Size / 2.5)))
+    portfolio['Lineup Edge'] = (portfolio['Win%'] * ((.5 - portfolio['Finish_percentile']) * 10000))
     # portfolio['Lineup Edge'] = portfolio.apply(lambda row: row['Lineup Edge'] / (row['Dupes'] + 1) if row['Dupes'] > 0 else row['Lineup Edge'], axis=1)
     portfolio['Lineup Edge'] = ((portfolio['Lineup Edge'] - portfolio['Lineup Edge'].mean())) - ((portfolio['Dupes'] - portfolio['Dupes'].mean()) / 50) 
     max_edge = portfolio['Lineup Edge'].max()