Update player data columns in init_baselines function to include additional statistics and rename 'Player' to 'name' for consistency. This enhances data representation and aligns with updated data sources.

src/streamlit_app.py

@@ -145,8 +145,9 @@ def init_baselines(type_var: str):
     cursor = collection.find()
 
     raw_display = pd.DataFrame(list(cursor))
-    raw_display = raw_display[['Player', 'Team', 'Opp', 'Position', 'dropbacks', 'pass_yards', 'pass_tds', 'rush_att', 'rush_yards', 'rush_tds', 'targets', 'rec', 'rec_yards', 'rec_tds', 'PPR', 'Half_PPR']]
-    raw_display['Player'] = raw_display['Player'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display['Player'])
+    raw_display = raw_display[['name', 'Team', 'Opp', 'Position', 'Salary', 'team_plays', 'team_pass', 'team_rush', 'team_tds', 'team_pass_tds', 'team_rush_tds', 'dropbacks', 'pass_yards', 'pass_tds',
+                               'rush_att', 'rush_yards', 'rush_tds', 'targets', 'rec', 'rec_yards', 'rec_tds', 'PPR', 'Half_PPR', 'Own']]
+    raw_display['name'] = raw_display['name'].map(dict(zip(wrong_team_names, right_name_teams)), na_action='ignore').fillna(raw_display['name'])
     player_stats = raw_display[raw_display['Position'] != 'K']
 
     if type_var == 'Regular':