Refactor captain ownership calculation in app.py to simplify logic by removing unnecessary type variable check, ensuring accurate ownership adjustments when captain ownership data is missing.

app.py

@@ -175,12 +175,11 @@ with tab1:
                     pass
                 projections['salary'] = projections['salary'].dropna().astype(int)
                 projections['ownership'] = projections['ownership'].astype(float)
-                if type_var == 'Showdown':
-                    if projections['captain ownership'].isna().all():
-                        projections['CPT_Own_raw'] = (projections['ownership'] / 2) * ((100 - (100-projections['ownership']))/100)
-                        cpt_own_var = 100 / projections['CPT_Own_raw'].sum()
-                        projections['captain ownership'] = projections['CPT_Own_raw'] * cpt_own_var
-                        projections = projections.drop(columns='CPT_Own_raw', axis=1)
+                if projections['captain ownership'].isna().all():
+                    projections['CPT_Own_raw'] = (projections['ownership'] / 2) * ((100 - (100-projections['ownership']))/100)
+                    cpt_own_var = 100 / projections['CPT_Own_raw'].sum()
+                    projections['captain ownership'] = projections['CPT_Own_raw'] * cpt_own_var
+                    projections = projections.drop(columns='CPT_Own_raw', axis=1)
                             
                 projections = projections.apply(lambda x: x.replace(player_wrong_names_mlb, player_right_names_mlb))
                 st.dataframe(projections.head(10))