Update app.py

app.py

@@ -44,9 +44,9 @@ prop_format = {'L5 Success': '{:.2%}', 'L10_Success': '{:.2%}', 'L20_success': '
                'Implied Over': '{:.2%}', 'Implied Under': '{:.2%}', 'Over Edge': '{:.2%}', 'Under Edge': '{:.2%}'}
 prop_table_options = ['points', 'threes', 'rebounds', 'assists', 'blocks', 'steals', 'PRA', 'PR', 'PA', 'PR']
 all_sim_vars = ['points', 'rebounds', 'assists', 'PRA', 'points+rebounds', 'points+assists', 'rebounds+assists']
-sim_all_hold = pd.DataFrame(columns=['Player', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge'])
+sim_all_hold = pd.DataFrame(columns=['Player', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge'])
 
-@st.cache_resource(ttl = 360)
+@st.cache_resource(ttl = 300)
 def init_baselines():
     sh = gcservice_account.open_by_url(master_hold)
     worksheet = sh.worksheet('Betting Model Clean')
@@ -334,7 +334,7 @@ with tab5:
                                 over_dict = dict(zip(df.Player, df.Over))
                                 under_dict = dict(zip(df.Player, df.Under))
                                 
-                                total_sims = 5000
+                                total_sims = 500
         
                                 df.replace("", 0, inplace=True)
         
@@ -401,10 +401,11 @@ with tab5:
                                 players_only['Bet_suggest'] = np.where(players_only['Over_diff'] > players_only['Under_diff'], "Over" , "Under")
                                 players_only['Bet?'] = np.where(players_only['Bet_check'] >= players_only['prop_threshold'], players_only['Bet_suggest'], "No Bet")
                                 players_only['Edge'] = players_only['Bet_check']
+                                players_only['Prop type'] = prop
         
                                 players_only['Player'] = hold_file[['Player']]
         
-                                leg_outcomes = players_only[['Player', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
+                                leg_outcomes = players_only[['Player', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
                                 
                                 final_outcomes = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)