ping

src/streamlit_app.py

@@ -145,6 +145,9 @@ selected_tab = st.segmented_control(
 )
             
 if selected_tab == "Regular Slate Contest Sims":
+    dk_raw, fd_raw = init_baselines('Main Slate')
+    raw_baselines = dk_raw
+    column_names = dk_columns
     with st.expander("Info and Filters"):
         site_data_col, slate_data_col, contest_size_col, contest_sharpness_col = st.columns([1, 1, 1, 1])
         with site_data_col:
@@ -234,20 +237,6 @@ if selected_tab == "Regular Slate Contest Sims":
             st.session_state.Sim_Winner_Display = Sim_Winner_Frame.copy()
             st.session_state.freq_copy = st.session_state.Sim_Winner_Display
         else:
-            if sim_site_var1 == 'Draftkings':
-                st.session_state.working_seed = init_DK_seed_frames(sim_slate_var1, sharp_split)
-                dk_raw, fd_raw = init_baselines(sim_slate_var1)
-                dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_ID)) 
-                    
-                raw_baselines = dk_raw
-                column_names = dk_columns
-            elif sim_site_var1 == 'Fanduel':
-                st.session_state.working_seed = init_FD_seed_frames(sim_slate_var1, sharp_split)
-                dk_raw, fd_raw = init_baselines(sim_slate_var1)
-                fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_ID))
-                    
-                raw_baselines = fd_raw
-                column_names = fd_columns
             st.session_state.maps_dict = {
                     'Projection_map':dict(zip(raw_baselines.Player,raw_baselines.Median)),
                     'Salary_map':dict(zip(raw_baselines.Player,raw_baselines.Salary)),
@@ -532,6 +521,8 @@ if selected_tab == "Regular Slate Contest Sims":
 
 if selected_tab == "Showdown Contest Sims":
     dk_sd_raw, fd_sd_raw = init_SD_baselines('Showdown #1')
+    raw_baselines = dk_sd_raw
+    column_names = dk_sd_columns
     with st.expander("Info and Filters"):
         site_data_col, slate_data_col, contest_size_col, contest_sharpness_col = st.columns([1, 1, 1, 1])
         with site_data_col: