okay yeah that should work

app.py

@@ -1742,6 +1742,8 @@ if selected_tab == 'Data Load':
 
 if selected_tab == 'Manage Portfolio':
     if 'origin_portfolio' in st.session_state and 'projections_df' in st.session_state:
+        if 'base_frame_names' not in st.session_state:
+            st.session_state['base_frame_names'] = ['Default']
         with st.container():
             reset_port_col, recalc_div_col, set_base_col, blank_reset_col, contest_size_col = st.columns([1, 1, 1, 6, 4])
             with reset_port_col:
@@ -1800,7 +1802,7 @@ if selected_tab == 'Manage Portfolio':
                 st.session_state['working_frame']['Size'] = st.session_state['working_frame'].index.map(st.session_state['size_dict'])
             
             st.session_state['base_frame'] = predict_dupes(st.session_state['working_frame'], st.session_state['map_dict'], site_var, type_var, Contest_Size, strength_var, sport_var, salary_max)
-            st.session_state[f'{base_choice}'] = st.session_state['base_frame']
+            st.session_state[f'Default'] = st.session_state['base_frame']
             st.session_state['working_frame'] = st.session_state['base_frame']
             # st.session_state['highest_owned_teams'] = st.session_state['projections_df'][~st.session_state['projections_df']['position'].isin(['P', 'SP'])].groupby('team')['ownership'].sum().sort_values(ascending=False).head(3).index.tolist()
             # st.session_state['highest_owned_pitchers'] = st.session_state['projections_df'][st.session_state['projections_df']['position'].isin(['P', 'SP'])]['player_names'].sort_values(by='ownership', ascending=False).head(3).tolist()