okay lets try it this way

app.py

@@ -3302,169 +3302,172 @@ if selected_tab == 'Manage Portfolio':
             )
         player_stats_col, stack_stats_col, combos_col = st.tabs(['Player Stats', 'Stack Stats', 'Combos'])
         with player_stats_col:
-            if st.button("Analyze Players", key='analyze_players'):
-                player_stats = []
-                
-                if st.session_state['settings_base'] and 'origin_player_exposures' in st.session_state and display_frame_source == 'Portfolio':
-                    st.session_state['player_summary'] = st.session_state['origin_player_exposures']
-                else:
-                    if type_var == 'Showdown':
-                        if sport_var == 'GOLF':
-                            for player in player_names:
-                                player_mask = st.session_state['display_frame'][st.session_state['player_columns']].apply(
-                                    lambda row: player in list(row), axis=1
-                                )
-                                
-                                if player_mask.any():
-                                    player_stats.append({
-                                        'Player': player,
-                                        'Position': st.session_state['map_dict']['pos_map'][player],
-                                        'Team': st.session_state['map_dict']['team_map'][player],
-                                        'ProjOwn': st.session_state['map_dict']['own_map'][player] / 100.0,
-                                        'Exposure': player_mask.sum() / len(st.session_state['display_frame']),
-                                        'Avg Median': st.session_state['display_frame'][player_mask]['median'].mean(),
-                                        'Avg Own': st.session_state['display_frame'][player_mask]['Own'].mean(),
-                                        'Avg Dupes': st.session_state['display_frame'][player_mask]['Dupes'].mean(),
-                                        'Avg Finish %': st.session_state['display_frame'][player_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': st.session_state['display_frame'][player_mask]['Lineup Edge'].mean(),
-                                        'Avg Diversity': st.session_state['display_frame'][player_mask]['Diversity'].mean(),
-                                    })
+            position_parse_col, analyze_button_col = st.tabs(['Position Parse', 'Analyze Players'])
+            with position_parse_col:
+                position_parse = st.selectbox("Parse by:", options=['All', *st.session_state['player_summary']['Position'].unique()], key='position_parse')
+            with analyze_button_col:
+                if st.button("Analyze Players", key='analyze_players'):
+                    player_stats = []
+                    
+                    if st.session_state['settings_base'] and 'origin_player_exposures' in st.session_state and display_frame_source == 'Portfolio':
+                        if position_parse != 'All':
+                            st.session_state['player_summary'] = st.session_state['origin_player_exposures'][st.session_state['origin_player_exposures']['Position'].str.contains(position_parse)]
                         else:
-                            for player in player_names:
-                                # Create mask for lineups where this player is Captain (first column)
-                                cpt_mask = st.session_state['display_frame'][st.session_state['player_columns'][0]] == player
-                                
-                                if cpt_mask.any():
-                                    player_stats.append({
-                                        'Player': f"{player} (CPT)",
-                                        'Position': 'CPT',
-                                        'Team': st.session_state['map_dict']['team_map'][player],
-                                        'ProjOwn': st.session_state['map_dict']['cpt_own_map'][player] / 100.0,
-                                        'Exposure': cpt_mask.sum() / len(st.session_state['display_frame']),
-                                        'Own_Edge': st.session_state['map_dict']['cpt_own_map'][player] / 100.0 - (cpt_mask.sum() / len(st.session_state['display_frame'])),
-                                        'Avg Median': st.session_state['display_frame'][cpt_mask]['median'].mean(),
-                                        'Avg Own': st.session_state['display_frame'][cpt_mask]['Own'].mean(),
-                                        'Avg Dupes': st.session_state['display_frame'][cpt_mask]['Dupes'].mean(),
-                                        'Avg Finish %': st.session_state['display_frame'][cpt_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': st.session_state['display_frame'][cpt_mask]['Lineup Edge'].mean(),
-                                        'Avg Diversity': st.session_state['display_frame'][cpt_mask]['Diversity'].mean(),
-                                    })
-                                
-                                # Create mask for lineups where this player is FLEX (other columns)
-                                flex_mask = st.session_state['display_frame'][st.session_state['player_columns'][1:]].apply(
-                                    lambda row: player in list(row), axis=1
-                                )
-                                
-                                if flex_mask.any():
-                                    player_stats.append({
-                                        'Player': f"{player} (FLEX)",
-                                        'Position': 'FLEX',
-                                        'Team': st.session_state['map_dict']['team_map'][player],
-                                        'ProjOwn': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0,
-                                        'Exposure': flex_mask.sum() / len(st.session_state['display_frame']),
-                                        'Own_Edge': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0 - (flex_mask.sum() / len(st.session_state['display_frame'])),
-                                        'Avg Median': st.session_state['display_frame'][flex_mask]['median'].mean(),
-                                        'Avg Own': st.session_state['display_frame'][flex_mask]['Own'].mean(),
-                                        'Avg Dupes': st.session_state['display_frame'][flex_mask]['Dupes'].mean(),
-                                        'Avg Finish %': st.session_state['display_frame'][flex_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': st.session_state['display_frame'][flex_mask]['Lineup Edge'].mean(),
-                                        'Avg Diversity': st.session_state['display_frame'][flex_mask]['Diversity'].mean(),
-                                    })
+                            st.session_state['player_summary'] = st.session_state['origin_player_exposures']
                     else:
-                        if sport_var == 'CS2' or sport_var == 'LOL':
-                            # Handle Captain positions
-                            for player in player_names:
-                                # Create mask for lineups where this player is Captain (first column)
-                                cpt_mask = st.session_state['display_frame'][st.session_state['player_columns'][0]] == player
-                                
-                                if cpt_mask.any():
-                                    player_stats.append({
-                                        'Player': f"{player} (CPT)",
-                                        'Position': 'CPT',
-                                        'Team': st.session_state['map_dict']['team_map'][player],
-                                        'ProjOwn': st.session_state['map_dict']['cpt_own_map'][player] / 100.0,
-                                        'Exposure': cpt_mask.sum() / len(st.session_state['display_frame']),
-                                        'Own_Edge': st.session_state['map_dict']['cpt_own_map'][player] / 100.0 - (cpt_mask.sum() / len(st.session_state['display_frame'])),
-                                        'Avg Median': st.session_state['display_frame'][cpt_mask]['median'].mean(),
-                                        'Avg Own': st.session_state['display_frame'][cpt_mask]['Own'].mean(),
-                                        'Avg Dupes': st.session_state['display_frame'][cpt_mask]['Dupes'].mean(),
-                                        'Avg Finish %': st.session_state['display_frame'][cpt_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': st.session_state['display_frame'][cpt_mask]['Lineup Edge'].mean(),
-                                        'Avg Diversity': st.session_state['display_frame'][cpt_mask]['Diversity'].mean(),
-                                    })
-                                
-                                # Create mask for lineups where this player is FLEX (other columns)
-                                flex_mask = st.session_state['display_frame'][st.session_state['player_columns'][1:]].apply(
-                                    lambda row: player in list(row), axis=1
-                                )
-                                
-                                if flex_mask.any():
-                                    player_stats.append({
-                                        'Player': f"{player} (FLEX)",
-                                        'Position': 'FLEX',
-                                        'Team': st.session_state['map_dict']['team_map'][player],
-                                        'ProjOwn': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0,
-                                        'Exposure': flex_mask.sum() / len(st.session_state['display_frame']),
-                                        'Own_Edge': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0 - (flex_mask.sum() / len(st.session_state['display_frame'])),
-                                        'Avg Median': st.session_state['display_frame'][flex_mask]['median'].mean(),
-                                        'Avg Own': st.session_state['display_frame'][flex_mask]['Own'].mean(),
-                                        'Avg Dupes': st.session_state['display_frame'][flex_mask]['Dupes'].mean(),
-                                        'Avg Finish %': st.session_state['display_frame'][flex_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': st.session_state['display_frame'][flex_mask]['Lineup Edge'].mean(),
-                                        'Avg Diversity': st.session_state['display_frame'][flex_mask]['Diversity'].mean(),
-                                    })
-                        elif sport_var != 'CS2' and sport_var != 'LOL':
-                            # Original Classic format processing
-                            for player in player_names:
-                                player_mask = st.session_state['display_frame'][st.session_state['player_columns']].apply(
-                                    lambda row: player in list(row), axis=1
-                                )
-                                
-                                if player_mask.any():
-                                    player_stats.append({
-                                        'Player': player,
-                                        'Position': st.session_state['map_dict']['pos_map'][player],
-                                        'Team': st.session_state['map_dict']['team_map'][player],
-                                        'ProjOwn': st.session_state['map_dict']['own_map'][player] / 100.0,
-                                        'Exposure': player_mask.sum() / len(st.session_state['display_frame']),
-                                        'Own_Edge': st.session_state['map_dict']['own_map'][player] / 100.0 - (player_mask.sum() / len(st.session_state['display_frame'])),
-                                        'Avg Median': st.session_state['display_frame'][player_mask]['median'].mean(),
-                                        'Avg Own': st.session_state['display_frame'][player_mask]['Own'].mean(),
-                                        'Avg Dupes': st.session_state['display_frame'][player_mask]['Dupes'].mean(),
-                                        'Avg Finish %': st.session_state['display_frame'][player_mask]['Finish_percentile'].mean(),
-                                        'Avg Lineup Edge': st.session_state['display_frame'][player_mask]['Lineup Edge'].mean(),
-                                        'Avg Diversity': st.session_state['display_frame'][player_mask]['Diversity'].mean(),
-                                    })
+                        if type_var == 'Showdown':
+                            if sport_var == 'GOLF':
+                                for player in player_names:
+                                    player_mask = st.session_state['display_frame'][st.session_state['player_columns']].apply(
+                                        lambda row: player in list(row), axis=1
+                                    )
+                                    
+                                    if player_mask.any():
+                                        player_stats.append({
+                                            'Player': player,
+                                            'Position': st.session_state['map_dict']['pos_map'][player],
+                                            'Team': st.session_state['map_dict']['team_map'][player],
+                                            'ProjOwn': st.session_state['map_dict']['own_map'][player] / 100.0,
+                                            'Exposure': player_mask.sum() / len(st.session_state['display_frame']),
+                                            'Avg Median': st.session_state['display_frame'][player_mask]['median'].mean(),
+                                            'Avg Own': st.session_state['display_frame'][player_mask]['Own'].mean(),
+                                            'Avg Dupes': st.session_state['display_frame'][player_mask]['Dupes'].mean(),
+                                            'Avg Finish %': st.session_state['display_frame'][player_mask]['Finish_percentile'].mean(),
+                                            'Avg Lineup Edge': st.session_state['display_frame'][player_mask]['Lineup Edge'].mean(),
+                                            'Avg Diversity': st.session_state['display_frame'][player_mask]['Diversity'].mean(),
+                                        })
+                            else:
+                                for player in player_names:
+                                    # Create mask for lineups where this player is Captain (first column)
+                                    cpt_mask = st.session_state['display_frame'][st.session_state['player_columns'][0]] == player
+                                    
+                                    if cpt_mask.any():
+                                        player_stats.append({
+                                            'Player': f"{player} (CPT)",
+                                            'Position': 'CPT',
+                                            'Team': st.session_state['map_dict']['team_map'][player],
+                                            'ProjOwn': st.session_state['map_dict']['cpt_own_map'][player] / 100.0,
+                                            'Exposure': cpt_mask.sum() / len(st.session_state['display_frame']),
+                                            'Own_Edge': st.session_state['map_dict']['cpt_own_map'][player] / 100.0 - (cpt_mask.sum() / len(st.session_state['display_frame'])),
+                                            'Avg Median': st.session_state['display_frame'][cpt_mask]['median'].mean(),
+                                            'Avg Own': st.session_state['display_frame'][cpt_mask]['Own'].mean(),
+                                            'Avg Dupes': st.session_state['display_frame'][cpt_mask]['Dupes'].mean(),
+                                            'Avg Finish %': st.session_state['display_frame'][cpt_mask]['Finish_percentile'].mean(),
+                                            'Avg Lineup Edge': st.session_state['display_frame'][cpt_mask]['Lineup Edge'].mean(),
+                                            'Avg Diversity': st.session_state['display_frame'][cpt_mask]['Diversity'].mean(),
+                                        })
+                                    
+                                    # Create mask for lineups where this player is FLEX (other columns)
+                                    flex_mask = st.session_state['display_frame'][st.session_state['player_columns'][1:]].apply(
+                                        lambda row: player in list(row), axis=1
+                                    )
+                                    
+                                    if flex_mask.any():
+                                        player_stats.append({
+                                            'Player': f"{player} (FLEX)",
+                                            'Position': 'FLEX',
+                                            'Team': st.session_state['map_dict']['team_map'][player],
+                                            'ProjOwn': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0,
+                                            'Exposure': flex_mask.sum() / len(st.session_state['display_frame']),
+                                            'Own_Edge': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0 - (flex_mask.sum() / len(st.session_state['display_frame'])),
+                                            'Avg Median': st.session_state['display_frame'][flex_mask]['median'].mean(),
+                                            'Avg Own': st.session_state['display_frame'][flex_mask]['Own'].mean(),
+                                            'Avg Dupes': st.session_state['display_frame'][flex_mask]['Dupes'].mean(),
+                                            'Avg Finish %': st.session_state['display_frame'][flex_mask]['Finish_percentile'].mean(),
+                                            'Avg Lineup Edge': st.session_state['display_frame'][flex_mask]['Lineup Edge'].mean(),
+                                            'Avg Diversity': st.session_state['display_frame'][flex_mask]['Diversity'].mean(),
+                                        })
+                        else:
+                            if sport_var == 'CS2' or sport_var == 'LOL':
+                                # Handle Captain positions
+                                for player in player_names:
+                                    # Create mask for lineups where this player is Captain (first column)
+                                    cpt_mask = st.session_state['display_frame'][st.session_state['player_columns'][0]] == player
+                                    
+                                    if cpt_mask.any():
+                                        player_stats.append({
+                                            'Player': f"{player} (CPT)",
+                                            'Position': 'CPT',
+                                            'Team': st.session_state['map_dict']['team_map'][player],
+                                            'ProjOwn': st.session_state['map_dict']['cpt_own_map'][player] / 100.0,
+                                            'Exposure': cpt_mask.sum() / len(st.session_state['display_frame']),
+                                            'Own_Edge': st.session_state['map_dict']['cpt_own_map'][player] / 100.0 - (cpt_mask.sum() / len(st.session_state['display_frame'])),
+                                            'Avg Median': st.session_state['display_frame'][cpt_mask]['median'].mean(),
+                                            'Avg Own': st.session_state['display_frame'][cpt_mask]['Own'].mean(),
+                                            'Avg Dupes': st.session_state['display_frame'][cpt_mask]['Dupes'].mean(),
+                                            'Avg Finish %': st.session_state['display_frame'][cpt_mask]['Finish_percentile'].mean(),
+                                            'Avg Lineup Edge': st.session_state['display_frame'][cpt_mask]['Lineup Edge'].mean(),
+                                            'Avg Diversity': st.session_state['display_frame'][cpt_mask]['Diversity'].mean(),
+                                        })
+                                    
+                                    # Create mask for lineups where this player is FLEX (other columns)
+                                    flex_mask = st.session_state['display_frame'][st.session_state['player_columns'][1:]].apply(
+                                        lambda row: player in list(row), axis=1
+                                    )
+                                    
+                                    if flex_mask.any():
+                                        player_stats.append({
+                                            'Player': f"{player} (FLEX)",
+                                            'Position': 'FLEX',
+                                            'Team': st.session_state['map_dict']['team_map'][player],
+                                            'ProjOwn': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0,
+                                            'Exposure': flex_mask.sum() / len(st.session_state['display_frame']),
+                                            'Own_Edge': (st.session_state['map_dict']['own_map'][player] - st.session_state['map_dict']['cpt_own_map'][player]) / 100.0 - (flex_mask.sum() / len(st.session_state['display_frame'])),
+                                            'Avg Median': st.session_state['display_frame'][flex_mask]['median'].mean(),
+                                            'Avg Own': st.session_state['display_frame'][flex_mask]['Own'].mean(),
+                                            'Avg Dupes': st.session_state['display_frame'][flex_mask]['Dupes'].mean(),
+                                            'Avg Finish %': st.session_state['display_frame'][flex_mask]['Finish_percentile'].mean(),
+                                            'Avg Lineup Edge': st.session_state['display_frame'][flex_mask]['Lineup Edge'].mean(),
+                                            'Avg Diversity': st.session_state['display_frame'][flex_mask]['Diversity'].mean(),
+                                        })
+                            elif sport_var != 'CS2' and sport_var != 'LOL':
+                                # Original Classic format processing
+                                for player in player_names:
+                                    player_mask = st.session_state['display_frame'][st.session_state['player_columns']].apply(
+                                        lambda row: player in list(row), axis=1
+                                    )
+                                    
+                                    if player_mask.any():
+                                        player_stats.append({
+                                            'Player': player,
+                                            'Position': st.session_state['map_dict']['pos_map'][player],
+                                            'Team': st.session_state['map_dict']['team_map'][player],
+                                            'ProjOwn': st.session_state['map_dict']['own_map'][player] / 100.0,
+                                            'Exposure': player_mask.sum() / len(st.session_state['display_frame']),
+                                            'Own_Edge': st.session_state['map_dict']['own_map'][player] / 100.0 - (player_mask.sum() / len(st.session_state['display_frame'])),
+                                            'Avg Median': st.session_state['display_frame'][player_mask]['median'].mean(),
+                                            'Avg Own': st.session_state['display_frame'][player_mask]['Own'].mean(),
+                                            'Avg Dupes': st.session_state['display_frame'][player_mask]['Dupes'].mean(),
+                                            'Avg Finish %': st.session_state['display_frame'][player_mask]['Finish_percentile'].mean(),
+                                            'Avg Lineup Edge': st.session_state['display_frame'][player_mask]['Lineup Edge'].mean(),
+                                            'Avg Diversity': st.session_state['display_frame'][player_mask]['Diversity'].mean(),
+                                        })
+                        
+                        player_summary = pd.DataFrame(player_stats)
+                        player_summary = player_summary.sort_values('Exposure', ascending=False)
+                        st.session_state['player_summary'] = player_summary.copy()
+                        if 'origin_player_exposures' not in st.session_state:
+                            st.session_state['origin_player_exposures'] = player_summary.copy()
                     
-                    player_summary = pd.DataFrame(player_stats)
-                    player_summary = player_summary.sort_values('Exposure', ascending=False)
-                    st.session_state['player_summary'] = player_summary.copy()
-                    if 'origin_player_exposures' not in st.session_state:
-                        st.session_state['origin_player_exposures'] = player_summary.copy()
-                
-                position_parse = st.selectbox("Parse by:", options=['All', *st.session_state['player_summary']['Position'].unique()], key='position_parse')
-                st.subheader("Player Summary")
-                if position_parse != 'All':
-                    st.session_state['player_summary'] = st.session_state['player_summary'][st.session_state['player_summary']['Position'].str.contains(position_parse)]
-                else:
-                    st.session_state['player_summary'] = st.session_state['player_summary']
-                st.dataframe(
-                    st.session_state['player_summary'].style
-                    .background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Avg Finish %', 'Avg Own', 'Avg Dupes'])
-                    .format({
-                        'ProjOwn': '{:.2%}',
-                        'Own_Edge': '{:.2%}',
-                        'Avg Median': '{:.2f}',
-                        'Avg Own': '{:.2f}',
-                        'Avg Dupes': '{:.2f}',
-                        'Avg Finish %': '{:.2%}',
-                        'Avg Lineup Edge': '{:.2%}',
-                        'Exposure': '{:.2%}',
-                        'Avg Diversity': '{:.2%}'
-                    }),
-                    height=400,
-                    use_container_width=True
-                )
+                    
+                    st.subheader("Player Summary")
+                    st.dataframe(
+                        st.session_state['player_summary'].style
+                        .background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Avg Finish %', 'Avg Own', 'Avg Dupes'])
+                        .format({
+                            'ProjOwn': '{:.2%}',
+                            'Own_Edge': '{:.2%}',
+                            'Avg Median': '{:.2f}',
+                            'Avg Own': '{:.2f}',
+                            'Avg Dupes': '{:.2f}',
+                            'Avg Finish %': '{:.2%}',
+                            'Avg Lineup Edge': '{:.2%}',
+                            'Exposure': '{:.2%}',
+                            'Avg Diversity': '{:.2%}'
+                        }),
+                        height=400,
+                        use_container_width=True
+                    )
         
         with stack_stats_col:
             if 'Stack' in st.session_state['display_frame'].columns: