Update app.py

app.py

@@ -360,9 +360,9 @@ with tab6:
     with col1:
         game_select_var = st.selectbox('Select prop source', options = ['Aggregate', 'Pick6'])
         if game_select_var == 'Aggregate':
-            prop_df = prop_frame[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
+            prop_df = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
         elif game_select_var == 'Pick6':
-            prop_df = pick_frame[['Full_name', 'over_prop', 'over_line', 'under_line', 'prop_type']]
+            prop_df = pick_frame[['Full_name', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
             prop_df.rename(columns={"Full_name": "Player"}, inplace = True)
         st.download_button(
             label="Download Prop Source",
@@ -381,17 +381,17 @@ with tab6:
                             for prop in all_sim_vars:
                                 
                                 if game_select_var == 'Aggregate':
-                                    prop_df = prop_frame[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
+                                    prop_df = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                 elif game_select_var == 'Pick6':
-                                    prop_df = pick_frame[['Full_name', 'over_prop', 'over_line', 'under_line', 'prop_type']]
+                                    prop_df = pick_frame[['Full_name', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                     prop_df.rename(columns={"Full_name": "Player"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['prop_type'] == prop]
-                                prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                                prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                                 
                                 prop_dict = dict(zip(df.Player, df.Prop))
@@ -418,7 +418,7 @@ with tab6:
                                 flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1.75)
                                 flex_file['STD'] = flex_file['Median'] / 4
                                 flex_file['Prop'] = flex_file['Player'].map(prop_dict)
-                                flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
+                                flex_file = flex_file[['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
         
                                 hold_file = flex_file
                                 overall_file = flex_file
@@ -429,12 +429,12 @@ with tab6:
                                 for x in range(0,total_sims):    
                                     prop_file[x] = prop_file['Prop']
         
-                                prop_file = prop_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                                prop_file = prop_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
         
                                 for x in range(0,total_sims):
                                     overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
         
-                                overall_file=overall_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                                overall_file=overall_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
         
                                 players_only = hold_file[['Player']]
         
@@ -466,7 +466,7 @@ with tab6:
                                 players_only['Player'] = hold_file[['Player']]
                                 players_only['Team'] = players_only['Player'].map(team_dict)
         
-                                leg_outcomes = players_only[['Player', 'Team', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
+                                leg_outcomes = players_only[['Player', 'Team', 'book', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
                                 sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                                 
                                 final_outcomes = sim_all_hold
@@ -474,9 +474,9 @@ with tab6:
                         elif prop_type_var != 'All Props':
                             
                             if game_select_var == 'Aggregate':
-                                prop_df = prop_frame[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
+                                prop_df = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                             elif game_select_var == 'Pick6':
-                                prop_df = pick_frame[['Full_name', 'over_prop', 'over_line', 'under_line', 'prop_type']]
+                                prop_df = pick_frame[['Full_name', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                 prop_df.rename(columns={"Full_name": "Player"}, inplace = True)
                             
                             if prop_type_var == "pass_yards":
@@ -485,8 +485,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "rush_yards":
                                 prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RUSHING_YARDS']
@@ -494,8 +494,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "rec_yards":
                                 prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RECEIVING_YARDS']
@@ -503,8 +503,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "receptions":
                                 prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RECEIVING_RECEPTIONS']
@@ -512,8 +512,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "rush_attempts":
                                 prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RUSHING_ATTEMPTS']
@@ -521,8 +521,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "pass_attempts":
                                 prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_PASSING_ATTEMPTS']
@@ -530,8 +530,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "pass_completions":
                                 prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_PASSING_COMPLETIONS']
@@ -539,8 +539,8 @@ with tab6:
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                 st.table(prop_df)
-                                prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
-                                prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
+                                prop_df['Over'] = 1 / prop_df['over_line']
+                                prop_df['Under'] = 1 / prop_df['under_line']
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             
                             prop_dict = dict(zip(df.Player, df.Prop))
@@ -567,7 +567,7 @@ with tab6:
                             flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1.75)
                             flex_file['STD'] = flex_file['Median'] / 4
                             flex_file['Prop'] = flex_file['Player'].map(prop_dict)
-                            flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
+                            flex_file = flex_file[['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
     
                             hold_file = flex_file
                             overall_file = flex_file
@@ -578,12 +578,12 @@ with tab6:
                             for x in range(0,total_sims):    
                                 prop_file[x] = prop_file['Prop']
     
-                            prop_file = prop_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                            prop_file = prop_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
     
                             for x in range(0,total_sims):
                                 overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
     
-                            overall_file=overall_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                            overall_file=overall_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
     
                             players_only = hold_file[['Player']]
     
@@ -614,7 +614,7 @@ with tab6:
                             players_only['Player'] = hold_file[['Player']]
                             players_only['Team'] = players_only['Player'].map(team_dict)
     
-                            final_outcomes = players_only[['Player', 'Team', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
+                            final_outcomes = players_only[['Player', 'Team', 'book', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
                         
                         final_outcomes = final_outcomes.sort_values(by='Edge', ascending=False)