Update app.py

app.py

@@ -673,15 +673,15 @@ with tab2:
                         
                         # Set the factors based on the contest_var1
                         factor_qb, factor_other = {
-                            'Small': (10, 5),
-                            'Medium': (6, 3),
-                            'Large': (3, 1.5),
+                            'Small': (8, 10),
+                            'Medium': (5, 5),
+                            'Large': (1.5, 1.5),
                         }[contest_var1]
                         
                         # Apply the calculation to the DataFrame
                         initial_proj['Own%'] = initial_proj.apply(lambda row: calculate_own(row['Position'], row['Own'], initial_proj.loc[initial_proj['Position'] == row['Position'], 'Own'].mean(), factor_qb if row['Position'] == 'QB' else factor_other), axis=1)
                         initial_proj['Own%'] = initial_proj['Own%'].clip(upper=75)
-                        initial_proj['Own'] = initial_proj['Own%'] * (500 / initial_proj['Own%'].sum())
+                        initial_proj['Own'] = initial_proj['Own%'] * (600 / initial_proj['Own%'].sum())
                         
                         # Drop unnecessary columns and create the final DataFrame
                         Overall_Proj = initial_proj[['Player', 'Team', 'Position', 'Median', 'Own', 'Salary']]
@@ -698,15 +698,15 @@ with tab2:
                         
                         # Set the factors based on the contest_var1
                         factor_qb, factor_other = {
-                            'Small': (10, 5),
-                            'Medium': (6, 3),
-                            'Large': (3, 1.5),
+                            'Small': (8, 10),
+                            'Medium': (5, 5),
+                            'Large': (1.5, 1.5),
                         }[contest_var1]
                         
                         # Apply the calculation to the DataFrame
                         initial_proj['Own%'] = initial_proj.apply(lambda row: calculate_own(row['Position'], row['Own'], initial_proj.loc[initial_proj['Position'] == row['Position'], 'Own'].mean(), factor_qb if row['Position'] == 'QB' else factor_other), axis=1)
                         initial_proj['Own%'] = initial_proj['Own%'].clip(upper=75)
-                        initial_proj['Own'] = initial_proj['Own%'] * (500 / initial_proj['Own%'].sum())
+                        initial_proj['Own'] = initial_proj['Own%'] * (600 / initial_proj['Own%'].sum())
                         
                         # Drop unnecessary columns and create the final DataFrame
                         Overall_Proj = initial_proj[['Player', 'Team', 'Position', 'Median', 'Own', 'Salary']]