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Update app.py
Browse files
app.py
CHANGED
@@ -63,16 +63,21 @@ def init_baselines():
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raw_display.replace('', np.nan, inplace=True)
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prop_frame = raw_display.dropna(subset='Team')
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worksheet = sh.worksheet('Pick6_ingest')
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raw_display = pd.DataFrame(worksheet.get_all_records())
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raw_display.replace('', np.nan, inplace=True)
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pick_frame = raw_display.dropna(subset='Player')
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return pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp
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pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
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tab1, tab2, tab3, tab4, tab5 = st.tabs(["Game Betting Model", "Pitcher Prop Projections", "Hitter Prop Projections", "Player Prop Simulations", "Stat Specific Simulations"])
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def convert_df_to_csv(df):
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return df.to_csv().encode('utf-8')
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@@ -81,7 +86,7 @@ with tab1:
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st.info(t_stamp)
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if st.button("Reset Data", key='reset1'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
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line_var1 = st.radio('How would you like to display odds?', options = ['Percentage', 'American'], key='line_var1')
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if line_var1 == 'Percentage':
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team_frame = team_frame[['Names', 'Game', 'Win Percentage', 'Spread', 'Cover Spread Percentage', 'Avg Score', 'Game Total', 'Avg Fifth Inning', 'Fifth Inning Lead Percentage']]
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@@ -105,7 +110,7 @@ with tab2:
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st.info(t_stamp)
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if st.button("Reset Data", key='reset2'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
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split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
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if split_var1 == 'Specific Teams':
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team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = pitcher_stats['Team'].unique(), key='team_var1')
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@@ -127,7 +132,7 @@ with tab3:
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st.info(t_stamp)
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if st.button("Reset Data", key='reset3'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
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split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
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if split_var2 == 'Specific Teams':
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team_var2 = st.multiselect('Which teams would you like to include in the tables?', options = hitter_stats['Team'].unique(), key='team_var2')
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@@ -149,7 +154,7 @@ with tab4:
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st.info(t_stamp)
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if st.button("Reset Data", key='reset4'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
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col1, col2 = st.columns([1, 5])
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with col2:
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@@ -556,4 +561,27 @@ with tab5:
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mime='text/csv',
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key='prop_proj',
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)
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raw_display.replace('', np.nan, inplace=True)
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prop_frame = raw_display.dropna(subset='Team')
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worksheet = sh.worksheet('Prop_results')
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raw_display = pd.DataFrame(worksheet.get_all_records())
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raw_display.replace('', np.nan, inplace=True)
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betsheet_frame = raw_display.dropna(subset='proj')
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worksheet = sh.worksheet('Pick6_ingest')
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raw_display = pd.DataFrame(worksheet.get_all_records())
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raw_display.replace('', np.nan, inplace=True)
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pick_frame = raw_display.dropna(subset='Player')
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return pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp
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pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
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tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs(["Game Betting Model", "Pitcher Prop Projections", "Hitter Prop Projections", "Player Prop Simulations", "Stat Specific Simulations", "Bet Sheet"])
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def convert_df_to_csv(df):
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return df.to_csv().encode('utf-8')
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st.info(t_stamp)
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if st.button("Reset Data", key='reset1'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
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line_var1 = st.radio('How would you like to display odds?', options = ['Percentage', 'American'], key='line_var1')
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if line_var1 == 'Percentage':
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team_frame = team_frame[['Names', 'Game', 'Win Percentage', 'Spread', 'Cover Spread Percentage', 'Avg Score', 'Game Total', 'Avg Fifth Inning', 'Fifth Inning Lead Percentage']]
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st.info(t_stamp)
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if st.button("Reset Data", key='reset2'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
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split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
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if split_var1 == 'Specific Teams':
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team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = pitcher_stats['Team'].unique(), key='team_var1')
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st.info(t_stamp)
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if st.button("Reset Data", key='reset3'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
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split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
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if split_var2 == 'Specific Teams':
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team_var2 = st.multiselect('Which teams would you like to include in the tables?', options = hitter_stats['Team'].unique(), key='team_var2')
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st.info(t_stamp)
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if st.button("Reset Data", key='reset4'):
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
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col1, col2 = st.columns([1, 5])
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with col2:
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mime='text/csv',
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key='prop_proj',
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)
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with tab6:
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st.info(t_stamp)
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if st.button("Reset Data", key='reset6'):
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st.info('This sheet is more or less a static represenation of the Stat Specific Simulations. ROR is rate of return based on hit rate and payout. Use the over and under EDGEs to place bets. 20%+ should be considered a 1 unit bet, 15-20% is .75 units, 10-15% is .50 units, 5-10% is .25 units, and 0-5% is .1 units.')
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st.cache_data.clear()
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pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
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split_var6 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var6')
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if split_var6 == 'Specific Teams':
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team_var6 = st.multiselect('Which teams would you like to include in the tables?', options = betsheet_frame['Team'].unique(), key='team_var6')
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elif split_var6 == 'All':
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team_var6 = pitcher_stats.Team.values.tolist()
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betsheet_disp = betsheet_frame.copy()
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betsheet_disp = betsheet_disp[betsheet_disp['Team'].isin(team_var6)]
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betsheet_disp = betsheet_disp.set_index('Player')
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betsheet_disp = betsheet_disp.sort_values(by='over_EDGE', ascending=False)
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st.dataframe(betsheet_disp.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
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st.download_button(
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label="Export Betsheet",
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data=convert_df_to_csv(betsheet_disp),
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file_name='MLB_Betsheet_export.csv',
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mime='text/csv',
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key='MLB_Betsheet_export',
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)
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