Refactor simulation data handling in app.py. Updated variable names for clarity, changing 'sim_results' to 'individual_sim_results' and added 'overall_sim_results' for aggregated player statistics. Enhanced data presentation by introducing subheaders for individual game simulations and overall simulations, improving user experience and data readability. This change streamlines the simulation process and enhances the clarity of displayed results.

app.py

@@ -346,7 +346,7 @@ def init_team_data(team, opponent, win_loss_settings, kill_predictions, death_pr
             results_dict[f'game {game + 1}'] = team_data.dropna()
             team_data['playername'] = team_data['playername'] + f' game {game + 1}'
 
-        overall_team_data = pd.concat([overall_team_data, team_data])
+            overall_team_data = pd.concat([overall_team_data, team_data])
 
         return overall_team_data.dropna().set_index('playername'), opp_boosts, results_dict
 
@@ -369,10 +369,10 @@ if st.button("Run"):
     player_summary = player_summary.set_index('playername')
 
     # Create simulated percentiles
-    sim_results = []
+    individual_sim_results = []
     for idx, row in team_data.iterrows():
         percentiles = simulate_stats(row)
-        sim_results.append({
+        individual_sim_results.append({
             'Player': idx,
             'Position': row['position'],
             'Stat': 'Kills',
@@ -384,7 +384,7 @@ if st.button("Run"):
         })
         # Repeat for other stats
         for stat, name in [('Death_Proj', 'Deaths'), ('Assist_Proj', 'Assists'), ('CS_Proj', 'CS')]:
-            sim_results.append({
+            individual_sim_results.append({
                 'Player': idx,
                 'Position': row['position'],
                 'Stat': name,
@@ -395,11 +395,42 @@ if st.button("Run"):
                 '90%': percentiles[stat][4]
             })
     
-    sim_df = pd.DataFrame(sim_results)
+    sim_df = pd.DataFrame(individual_sim_results)
+
+    # Create simulated percentiles
+    overall_sim_results = []
+    for idx, row in player_summary.iterrows():
+        percentiles = simulate_stats(row)
+        overall_sim_results.append({
+            'Player': idx,
+            'Position': row['position'],
+            'Stat': 'Kills',
+            '10%': percentiles['Kill_Proj'][0],
+            '25%': percentiles['Kill_Proj'][1],
+            '50%': percentiles['Kill_Proj'][2],
+            '75%': percentiles['Kill_Proj'][3],
+            '90%': percentiles['Kill_Proj'][4]
+        })
+        # Repeat for other stats
+        for stat, name in [('Death_Proj', 'Deaths'), ('Assist_Proj', 'Assists'), ('CS_Proj', 'CS')]:
+            overall_sim_results.append({
+                'Player': idx,
+                'Position': row['position'],
+                'Stat': name,
+                '10%': percentiles[stat][0],
+                '25%': percentiles[stat][1],
+                '50%': percentiles[stat][2],
+                '75%': percentiles[stat][3],
+                '90%': percentiles[stat][4]
+            })
+    
+    overall_sim_df = pd.DataFrame(overall_sim_results)
 
     tab1, tab2 = st.tabs(["Team Data", "Opponent Data"])
     with tab1:
+        st.subheader("Full Match Data")
         st.dataframe(player_summary.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(display_formats, precision=2), use_container_width = True)
+        st.subheader("Individual Game Data")
         st.dataframe(team_data.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(display_formats, precision=2), use_container_width = True)
     with tab2:
         st.dataframe(opp_boost.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
@@ -407,6 +438,7 @@ if st.button("Run"):
     unique_players = sim_df['Player'].unique().tolist()
     player_tabs = st.tabs(unique_players)
     
+    st.subheader("Individual Game Simulations")
     for player, tab in zip(unique_players, player_tabs):
         with tab:
             player_data = sim_df[sim_df['Player'] == player]
@@ -415,4 +447,7 @@ if st.button("Run"):
                 player_data[['10%', '25%', '50%', '75%', '90%']]
                 .style.format(precision=2),
                 use_container_width=True
-            )
+            )
+    
+    st.subheader("Overall Simulations")
+    st.dataframe(overall_sim_df.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(display_formats, precision=2), use_container_width = True)