Refactor VORP scoring logic in Streamlit app to include league type conditions and enhance player ranking calculations, improving accuracy and output structure for halfPPR and custom scoring formats.

src/streamlit_app.py

@@ -348,7 +348,44 @@ def create_custom_rv(frame: pd.DataFrame, pos_reqs: dict, league_settings: dict)
 
     return rv_dict
 
-def assign_vorp(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, league_settings: dict, pos_vorp_limiters: dict) -> pd.DataFrame:
+def assign_vorp_scoring(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, league_settings: dict, pos_vorp_limiters: dict) -> pd.DataFrame:
+    if league_settings['TYPE'] == 'Half PPR':
+        rv_type = 'halfPpr'
+    elif league_settings['TYPE'] == 'PPR':
+        rv_type = 'ppr'
+    elif league_settings['TYPE'] == 'Standard':
+        rv_type = 'standard'
+    elif league_settings['TYPE'] == 'Superflex':
+        rv_type = 'halfPpr'
+    elif league_settings['TYPE'] == 'TE Premium':
+        rv_type = 'halfPpr'
+
+    vorp_frame = pd.DataFrame()
+    for positions in ['QB', 'RB', 'WR', 'TE']:
+        pos_frame = frame[frame['Pos'] == positions]
+        pos_frame = pos_frame[pos_frame['Rank'] != 0]
+        pos_frame = pos_frame.sort_values(by='Rank', ascending=True).reset_index(drop=True)
+        
+        pos_frame['halfPpr_rv'] = halfPpr_rv[positions]
+        pos_frame['custom_rv'] = custom_rv[positions]
+        pos_frame['halfPpr_VORP'] = pos_frame['halfPpr'] - halfPpr_rv[positions]
+        pos_frame['custom_VORP'] = pos_frame[rv_type] - custom_rv[positions]
+        
+        vorp_frame = pd.concat([vorp_frame, pos_frame]).reset_index(drop=True)
+
+    vorp_frame['halfPpr_vorp_rank'] = vorp_frame['halfPpr_VORP'].rank(method='max', ascending=False)
+    vorp_frame['custom_vorp_rank'] = vorp_frame['custom_VORP'].rank(method='max', ascending=False)
+    vorp_frame['vorp_diff'] = np.where(vorp_frame['halfPpr_VORP'] == vorp_frame['custom_VORP'], 0, vorp_frame['halfPpr_vorp_rank'] - vorp_frame['custom_vorp_rank'])
+    for positions in ['QB', 'RB', 'WR', 'TE']:
+        vorp_frame.loc[vorp_frame['Pos'] == positions, 'Rank_Adjust'] = (vorp_frame['Rank'] - (vorp_frame['vorp_diff'] * pos_vorp_limiters[positions])).astype(float)
+    vorp_frame['custom_rank'] = vorp_frame['Rank_Adjust'].rank(method='first', ascending=True).astype(int)
+    vorp_frame['pos_rank'] = vorp_frame.groupby('Pos')['custom_rank'].rank(method='first', ascending=True).astype(int)
+    vorp_frame['pos_designation'] = vorp_frame['Pos'] + vorp_frame['pos_rank'].astype(str)
+    pos_des_dict = dict(zip(vorp_frame['pos_designation'], vorp_frame['Name']))
+
+    return pos_des_dict
+
+def assign_vorp_roster(frame: pd.DataFrame, halfPpr_rv: dict, custom_rv: dict, league_settings: dict, pos_vorp_limiters: dict) -> pd.DataFrame:
     if league_settings['TYPE'] == 'Half PPR':
         rv_type = 'halfPpr'
     elif league_settings['TYPE'] == 'PPR':
@@ -425,13 +462,15 @@ def main():
     
     # Calculate replacement values
     halfPpr_rv = create_halfPpr_rv(position_df, base_pos_reqs)
-    custom_rv = create_custom_rv(position_df, custom_pos_reqs, user_league_settings)
+    custom_scoring_rv = create_custom_rv(position_df, base_pos_reqs, user_league_settings)
+    custom_roster_rv = create_custom_rv(position_df, custom_pos_reqs, user_league_settings)
     
     # Calculate VORP and rankings
-    final_df, pos_lock_dict, name_lock_dict = assign_vorp(position_df, halfPpr_rv, custom_rv, user_league_settings, user_pos_vorp_limiters)
-    final_df = final_df.drop(columns=['SR_ID'], axis=1)
+    pos_des_dict = assign_vorp_scoring(position_df, halfPpr_rv, custom_scoring_rv, user_league_settings, user_pos_vorp_limiters)
+    final_df = assign_vorp_roster(position_df, halfPpr_rv, custom_roster_rv, user_league_settings, user_pos_vorp_limiters)
+    final_df, pos_lock_dict, name_lock_dict = final_df.drop(columns=['SR_ID'], axis=1)
     final_df['orig_rank'] = final_df['Name'].map(name_lock_dict)
-    final_df['pos_lock_name'] = final_df['pos_designation'].map(pos_lock_dict)
+    final_df['pos_lock_name'] = final_df['pos_designation'].map(pos_des_dict)
     
     # Display results
     st.header("Player Rankings")
@@ -440,7 +479,7 @@ def main():
     # Position breakdown
     st.header("Position Breakdown")
     for pos in ['QB', 'RB', 'WR', 'TE']:
-        pos_df = final_df[final_df['Pos'] == pos].head(20)
+        pos_df = final_df[final_df['Pos'] == pos].head(50)
         st.subheader(f"Top {pos}s")
         st.dataframe(pos_df, use_container_width=True)