Update app.py

app.py

@@ -47,6 +47,7 @@ def init_conn():
 gcservice_account = init_conn()
 
 NBAGetGameData = 'https://docs.google.com/spreadsheets/d/1tRQrF_I5rS7Q0g9vE8NrENDZ2P3_DvtbBZzKEakwOI0/edit#gid=1373653837'
+NCAAMensBasketball = 'https://docs.google.com/spreadsheets/d/1flWwlx1T7Xu68AjOkeq7u4Y7nWzukZzKTEI17RJ6MfE/edit#gid=1975368022'
 NBABettingModel = 'https://docs.google.com/spreadsheets/d/1WBnvOHQi_zVTGF63efejK5ho02AY00HiYrMHnMJXY1E/edit#gid=1157978351'
 
 game_format = {'Injury and Rotation Adjusted Win %': '{:.2%}'}
@@ -58,146 +59,64 @@ percentages_format = {'Playoff Odds': '{:.2%}', 'Division Odds': '{:.2%}', 'Top
 
 @st.cache_resource(ttl = 300)
 def init_baselines():
-    sh = gcservice_account.open_by_url(NBABettingModel)
+    sh = gcservice_account.open_by_url(NCAAMensBasketball)
 
-    worksheet = sh.worksheet('ExportTable')
+    worksheet = sh.worksheet('ActiveBets')
     raw_display = pd.DataFrame(worksheet.get_values())
     raw_display.columns = raw_display.iloc[0]
     raw_display = raw_display[1:]
     raw_display = raw_display.reset_index(drop=True)
     raw_display.replace('', np.nan, inplace=True)
-    cols_to_check = ['Win %', 'Injury and Rotation Adjusted Win %']
-    raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
-    raw_display = raw_display.apply(pd.to_numeric, errors='coerce').fillna(raw_display)
-    raw_display['Team Date'] = raw_display['Team'] + " " + raw_display['Date']
-    raw_display = raw_display.drop(columns=['Day of Season', 'Team', 'Opp', 'Date Num', 'DR Team', 'In Minutes File'])
-    game_model = raw_display[raw_display['Injury and Rotation Adjusted Win %'] != ""]
-    just_win_probs = game_model[['Team Date', 'Date', 'Time', 'Acro', 'Opponent', 'Injury and Rotation Adjusted Win %', 'Total Proj', 'Projected Points', 'Injury and Rotation Adjusted Expected Margin']]
+    game_model = raw_display[['#', 'date', 'gameid', 'HomeTeam', 'HomeDiv', 'HomeConf', 'AwayTeam', 'AwayDiv', 'AwayConf',
+                              'total', 'mlHome', 'mlAway', 'spreadHome', 'spreadAway', 'booksid', 'inconf', 'Neutral', 'Home Team PM',
+                              'Road Team PM', 'HCA', 'Home Team Margin', 'Home Team Win', 'Home ML Break even %',
+                              'Road ML Break Even %', 'Home Win Edge', 'Road Win Edge', 'Moneyline Bet Rec', 'Home Spread Edge',
+                              'Road Team Edge', 'Home Spread HKelly', 'Away Spread HKelly', 'Spread Bet Rec', 'Edge for Spread']]
+    data_cols = ['#', 'gameid', 'total', 'mlHome', 'mlAway', 'spreadHome', 'spreadAway', 'Neutral', 'Home Team PM',
+                 'Road Team PM', 'HCA', 'Home Team Margin', 'Home Team Win', 'Home ML Break even %',
+                 'Road ML Break Even %', 'Home Win Edge', 'Road Win Edge', 'Home Spread Edge',
+                 'Road Team Edge', 'Home Spread HKelly', 'Away Spread HKelly', 'Edge for Spread']
+    game_model[data_cols] = game_model[data_cols].apply(pd.to_numeric, errors='coerce')
+    game_model = game_model[game_model['Injury and Rotation Adjusted Win %'] != ""]
+    just_win_probs = game_model[['#', 'date', 'gameid', 'HomeTeam', 'AwayTeam', 'total', 'mlHome', 'mlAway', 'spreadHome', 'spreadAway', 'booksid',
+                              'Home Win Edge', 'Road Win Edge', 'Moneyline Bet Rec', 'Home Spread Edge', 'Road Team Edge', 'Spread Bet Rec']]
     
+    timestamp = raw_display['Time'].head(1)[0]
 
-    worksheet = sh.worksheet('SeasonExport')
-    raw_display = pd.DataFrame(worksheet.get_values())
-    raw_display.columns = raw_display.iloc[0]
-    raw_display = raw_display[1:]
-    raw_display = raw_display.reset_index(drop=True)
-    raw_display.replace('', 0, inplace=True)
-    cols_to_check = ['Playoff Odds', 'Division Odds', 'Top 4 Seed Odds', '1 Seed Odds', 'Win 1st Round', 'Win 2nd Round', 'Win Conference', 'Win Title',
-                     '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15']
-    raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
-    raw_display = raw_display.apply(pd.to_numeric, errors='coerce').fillna(raw_display)
-    season_model = raw_display[raw_display['Team'] != ""]
-    title_sims = season_model[['Team', 'Conference', 'Division', 'Power Rank', 'Team PointMarginPerGame', 'SeasonSimLookup', 'Win Projection Now',
-                               'Playoff Odds', 'Division Odds', 'Top 4 Seed Odds', '1 Seed Odds', 'Win 1st Round', 'Win 2nd Round', 'Win Conference', 'Win Title']]
-    seed_probs = season_model[['Team', 'Conference', 'Division', 'Avg Seed', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15']]
-
-    sh = gcservice_account.open_by_url('https://docs.google.com/spreadsheets/d/1Yq0vGriWK-bS79e-bD6_u9pqrYE6Yrlbb_wEkmH-ot0/edit#gid=1540807349')
-    
-    worksheet = sh.worksheet('Arturo Props')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
-    raw_display.replace('', np.nan, inplace=True)
-    timestamp = raw_display['Date'].head(1)[0]
-
-    return game_model, season_model, seed_probs, title_sims, just_win_probs, timestamp
+    return game_model, just_win_probs, timestamp
 
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-game_model, season_model, seed_probs, title_sims, just_win_probs, timestamp = init_baselines()
-t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-
-tab1, tab2 = st.tabs(["Game Betting Model", "Season and Futures"])
-
-with tab1:
-    st.info(t_stamp)
-    col1, col2 = st.columns([1, 9])
-    with col1:
-        if st.button("Reset Data", key='reset1'):
-                  st.cache_data.clear()
-                  game_model, season_model, seed_probs, title_sims, just_win_probs, timestamp = init_baselines()
-                  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-        view_var1 = st.radio("Would you like to view math and stuff or just the win percentages and margins?", ('Just win probs', 'Gimme details'), key='view_var1')
-        split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
-        if split_var1 == 'Specific Teams':
-            team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = game_model['Acro'].unique(), key='team_var1')
-        elif split_var1 == 'All':
-            team_var1 = game_model.Acro.values.tolist()
-        date_split_var1 = st.radio("Would you like to view all Dates or specific ones?", ('All', 'Specific Dates'), key='date_split_var1')
-        if date_split_var1 == 'Specific Dates':
-            date_var1 = st.multiselect('Which Dates would you like to include in the tables?', options = game_model['Date'].unique(), key='date_var1')
-        elif date_split_var1 == 'All':
-            date_var1 = game_model.Date.values.tolist()
-    with col2:
-        if view_var1 == 'Just win probs':
-            game_display = just_win_probs[just_win_probs['Acro'].isin(team_var1)]
-            game_display = game_display[game_display['Date'].isin(date_var1)]
-            game_display = game_display.set_index('Team Date')
-            st.dataframe(game_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(game_format, precision=2), use_container_width = True)
-            st.download_button(
-                label="Export Game Model",
-                data=convert_df_to_csv(game_model),
-                file_name='AmericanNumbers_Game_Model_export.csv',
-                mime='text/csv',
-            )
-        elif view_var1 == 'Gimme details':
-            game_display = game_model[game_model['Acro'].isin(team_var1)]
-            game_display = game_display[game_display['Date'].isin(date_var1)]
-            game_display = game_display.set_index('Team Date')
-            st.dataframe(game_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(game_format, precision=2), use_container_width = True)
-            st.download_button(
-                label="Export Game Model",
-                data=convert_df_to_csv(game_model),
-                file_name='AmericanNumbers_Game_Model_export.csv',
-                mime='text/csv',
-            )
-
-with tab2:
-    st.info(t_stamp)
-    col1, col2 = st.columns([1, 9])
-    with col1:
-        if st.button("Reset Data", key='reset2'):
-                  st.cache_data.clear()
-                  game_model, season_model, seed_probs, title_sims, just_win_probs, timestamp = init_baselines()
-                  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-        view_var2 = st.radio("Would you like to view title odds and win projections or seeding probabilities?", ('Win Odds', 'Seed Probabilities'), key='view_var2')
-        split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
-        if split_var2 == 'Specific Teams':
-            team_var2 = st.multiselect('Which teams would you like to include in the tables?', options = season_model['Team'].unique(), key='team_var2')
-        elif split_var2 == 'All':
-            team_var2 = season_model.Team.values.tolist()
-        conf_var2 = st.radio("Would you like to view all conferences or specific ones?", ('All', 'Specific Conferences'), key='conf_var2')
-        if conf_var2 == 'Specific Conferences':
-            conf_choice_var2 = st.multiselect('Which conferences would you like to include in the tables?', options = season_model['Conference'].unique(), key='conf_choice_var2')
-        elif conf_var2 == 'All':
-            conf_choice_var2 = season_model.Conference.values.tolist()
-        div_var2 = st.radio("Would you like to view all divisions or specific ones?", ('All', 'Specific Divisions'), key='div_var2')
-        if div_var2 == 'Specific Divisions':
-            div_choice_var2 = st.multiselect('Which divisions would you like to include in the tables?', options = season_model['Division'].unique(), key='div_choice_var2')
-        elif div_var2 == 'All':
-            div_choice_var2 = season_model.Division.values.tolist()
-    with col2:
-        if view_var2 == 'Win Odds':
-            title_sims = title_sims[title_sims['Team'].isin(team_var2)]
-            title_sims = title_sims[title_sims['Conference'].isin(conf_choice_var2)]
-            title_sims = title_sims[title_sims['Division'].isin(div_choice_var2)]
-            season_display = title_sims.set_index('Team')
-            season_display = season_display.sort_values(by=['Win Projection Now'], ascending=False)
-            st.dataframe(season_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
-            st.download_button(
-                label="Export Futures Model",
-                data=convert_df_to_csv(title_sims),
-                file_name='AmericanNumbers_Season_Futures.csv',
-                mime='text/csv',
-            )
-        elif view_var2 == 'Seed Probabilities':
-            seed_probs = seed_probs[seed_probs['Team'].isin(team_var2)]
-            seed_probs = seed_probs[seed_probs['Conference'].isin(conf_choice_var2)]
-            seed_probs = seed_probs[seed_probs['Division'].isin(div_choice_var2)]
-            season_display = seed_probs.set_index('Team')
-            season_display = season_display.sort_values(by=['Avg Seed'], ascending=True)
-            st.dataframe(season_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
-            st.download_button(
-                label="Export Futures Model",
-                data=convert_df_to_csv(seed_probs),
-                file_name='AmericanNumbers_Season_Futures.csv',
-                mime='text/csv',
-            )
+game_model, just_win_probs, timestamp = init_baselines()
+t_stamp = f"Last Update: " + str(timestamp) + f" EST"
+
+
+st.info(t_stamp)
+col1, col2 = st.columns([1, 9])
+with col1:
+    if st.button("Reset Data", key='reset1'):
+              st.cache_data.clear()
+              game_model, just_win_probs, timestamp = init_baselines()
+              t_stamp = f"Last Update: " + str(timestamp) + f" EST"
+    view_var1 = st.radio("Would you like to view math and stuff or just the win percentages and margins?", ('Just win probs', 'Gimme details'), key='view_var1')
+
+with col2:
+    if view_var1 == 'Just win probs':
+        game_display = just_win_probs
+        st.dataframe(game_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        st.download_button(
+            label="Export Game Model",
+            data=convert_df_to_csv(game_model),
+            file_name='AmericanNumbers_Game_Model_export.csv',
+            mime='text/csv',
+        )
+    elif view_var1 == 'Gimme details':
+        game_display = game_model
+        st.dataframe(game_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        st.download_button(
+            label="Export Game Model",
+            data=convert_df_to_csv(game_model),
+            file_name='AmericanNumbers_NCAA_BBall_export.csv',
+            mime='text/csv',
+        )