Update app.py

app.py

@@ -363,6 +363,33 @@ with tab5:
                             prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+100)), 100/(prop_df['over_line']+100))
                             prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+100)), 100/(prop_df['under_line']+100))
                             df = pd.merge(player_df, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
+                        elif prop_type_var == "Earned Runs (Pitchers)":
+                            player_df = pitcher_stats
+                            prop_df = prop_frame[prop_frame['prop_type'] == 'pitcher_earned_runs']
+                            prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                            prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)   
+                            prop_df = prop_df.loc[prop_df['Prop'] != 0]
+                            prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+100)), 100/(prop_df['over_line']+100))
+                            prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+100)), 100/(prop_df['under_line']+100))
+                            df = pd.merge(player_df, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
+                        elif prop_type_var == "Hits Against (Pitchers)":
+                            player_df = pitcher_stats
+                            prop_df = prop_frame[prop_frame['prop_type'] == 'pitcher_hits_allowed']
+                            prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                            prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)   
+                            prop_df = prop_df.loc[prop_df['Prop'] != 0]
+                            prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+100)), 100/(prop_df['over_line']+100))
+                            prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+100)), 100/(prop_df['under_line']+100))
+                            df = pd.merge(player_df, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
+                        elif prop_type_var == "Walks Allowed (Pitchers)":
+                            player_df = pitcher_stats
+                            prop_df = prop_frame[prop_frame['prop_type'] == 'pitcher_walks']
+                            prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                            prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)   
+                            prop_df = prop_df.loc[prop_df['Prop'] != 0]
+                            prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+100)), 100/(prop_df['over_line']+100))
+                            prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+100)), 100/(prop_df['under_line']+100))
+                            df = pd.merge(player_df, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                         elif prop_type_var == "Total Bases (Hitters)":
                             player_df = hitter_stats
                             prop_df = prop_frame[prop_frame['prop_type'] == 'batter_total_bases']
@@ -381,6 +408,15 @@ with tab5:
                             prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+100)), 100/(prop_df['over_line']+100))
                             prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+100)), 100/(prop_df['under_line']+100))
                             df = pd.merge(player_df, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
+                        elif prop_type_var == "Hits (Hitters)":
+                            player_df = hitter_stats
+                            prop_df = prop_frame[prop_frame['prop_type'] == 'batter_hits']
+                            prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                            prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
+                            prop_df = prop_df.loc[prop_df['Prop'] != 0]
+                            prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+100)), 100/(prop_df['over_line']+100))
+                            prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+100)), 100/(prop_df['under_line']+100))
+                            df = pd.merge(player_df, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                         
                         prop_dict = dict(zip(df.Player, df.Prop))
                         over_dict = dict(zip(df.Player, df.Over))
@@ -392,8 +428,14 @@ with tab5:
 
                         if prop_type_var == "Strikeouts (Pitchers)":
                             df['Median'] = df['Ks']
+                        elif prop_type_var == "Earned Runs (Pitchers)":
+                            df['Median'] = df['ERs']
                         elif prop_type_var == "Total Outs (Pitchers)":
                             df['Median'] = df['Outs']
+                        elif prop_type_var == "Hits Against (Pitchers)":
+                            df['Median'] = df['Hits']
+                        elif prop_type_var == "Walks Allowed (Pitchers)":
+                            df['Median'] = df['BB']
                         elif prop_type_var == "Total Bases (Hitters)":
                             df['Median'] = df['Total Bases']
                         elif prop_type_var == "Stolen Bases (Hitters)":
@@ -402,28 +444,49 @@ with tab5:
                         flex_file = df
                         if prop_type_var == 'Strikeouts (Pitchers)':
                             flex_file['Floor'] = flex_file['Median'] * .20
-                            flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * .80)
+                            flex_file['Ceiling'] = flex_file['Median'] * 1.8
                             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']]
 
                         elif prop_type_var == 'Total Outs (Pitchers)':
                             flex_file['Floor'] = flex_file['Median'] * .20
-                            flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * .80)
+                            flex_file['Ceiling'] = flex_file['Median'] * 1.8
+                            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']]
+                        
+                        elif prop_type_var == 'Earned Runs (Pitchers)':
+                            flex_file['Floor'] = flex_file['Median'] * .20
+                            flex_file['Ceiling'] = flex_file['Median'] * 1.8
+                            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']]
+                        
+                        elif prop_type_var == 'Hits Against (Pitchers)':
+                            flex_file['Floor'] = flex_file['Median'] * .20
+                            flex_file['Ceiling'] = flex_file['Median'] * 1.8
+                            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']]
+                        
+                        elif prop_type_var == 'Walks Allowed (Pitchers)':
+                            flex_file['Floor'] = flex_file['Median'] * .20
+                            flex_file['Ceiling'] = flex_file['Median'] * 1.8
                             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']]
 
                         elif prop_type_var == 'Total Bases (Hitters)':
                             flex_file['Floor'] = np.where((prop_type_var == "Fantasy") | (prop_type_var == "FD_Fantasy") | (prop_type_var == "PrizePicks"), flex_file['Median'] * .20, 0)
-                            flex_file['Ceiling'] = np.where((prop_type_var == "Fantasy") | (prop_type_var == "FD_Fantasy") | (prop_type_var == "PrizePicks"), flex_file['Median'] + (flex_file['Median'] * .80), flex_file['Median'] * 4)
+                            flex_file['Ceiling'] = np.where((prop_type_var == "Fantasy") | (prop_type_var == "FD_Fantasy") | (prop_type_var == "PrizePicks"), flex_file['Median'] * 1.8, flex_file['Median'] * 4)
                             flex_file['STD'] = flex_file['Median'] / 1.5
                             flex_file['Prop'] = flex_file['Player'].map(prop_dict)
                             flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
 
                         elif prop_type_var == 'Stolen Bases (Hitters)':
                             flex_file['Floor'] = np.where((prop_type_var == "Fantasy") | (prop_type_var == "FD_Fantasy") | (prop_type_var == "PrizePicks"), flex_file['Median'] * .20, 0)
-                            flex_file['Ceiling'] = np.where((prop_type_var == "Fantasy") | (prop_type_var == "FD_Fantasy") | (prop_type_var == "PrizePicks"), flex_file['Median'] + (flex_file['Median'] * .80), flex_file['Median'] * 4)
+                            flex_file['Ceiling'] = np.where((prop_type_var == "Fantasy") | (prop_type_var == "FD_Fantasy") | (prop_type_var == "PrizePicks"), flex_file['Median'] * 1.8, flex_file['Median'] * 4)
                             flex_file['STD'] = flex_file['Median'] / 1.5
                             flex_file['Prop'] = flex_file['Player'].map(prop_dict)
                             flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]