Update 'cpt_Median' calculation in app.py to improve projection accuracy. Adjusted multiplier from 1.5 to 1.25 for both DraftKings and FanDuel dataframes, ensuring more precise ownership metrics in the init_baselines function.

app.py

@@ -132,7 +132,7 @@ def init_baselines(sport):
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%',
                                    'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX', 'version', 'slate', 'timestamp', 'player_id', 'site']]
-        raw_display['cpt_Median'] = raw_display['Median'] * 1.5
+        raw_display['cpt_Median'] = raw_display['Median'] * 1.25
         raw_display['STDev'] = raw_display['Median'] / 4
         raw_display['CPT_STDev'] = raw_display['cpt_Median'] / 4
         
@@ -158,7 +158,7 @@ def init_baselines(sport):
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display[['Player', 'Minutes Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
                                    'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX', 'site', 'version', 'slate', 'timestamp']]
-        raw_display['cpt_Median'] = raw_display['Median'] * 1.5
+        raw_display['cpt_Median'] = raw_display['Median'] * 1.25
         raw_display = raw_display[raw_display['site'] == 'Draftkings']
         raw_display['STDev'] = raw_display['Median'] / 4
         raw_display['CPT_STDev'] = raw_display['cpt_Median'] / 4