Enhance payout calculation logic in app.py

- Updated the get_payout_for_position function to handle ties by splitting the payout among tied positions, improving accuracy in payout calculations.
- Adjusted the application of the function in the dataframe to include the count of tied entries, ensuring correct payout values are computed for each finish position.

app.py

@@ -106,16 +106,38 @@ def export_contest_file(db, sport, type, contest_date, contest_id, contest_data)
 
     return return_message
 
-def get_payout_for_position(finish_pos, payout_df):
-    # Find the row where finish_pos falls between minPosition and maxPosition
-    matching_row = payout_df[
-        (payout_df['minPosition'] <= finish_pos + 1) & 
-        (payout_df['maxPosition'] >= finish_pos + 1)
-    ]
-    if not matching_row.empty:
-        return matching_row.iloc[0]['value']
+def get_payout_for_position(finish_pos, payout_df, dupes_count=1):
+    """
+    Calculate payout for a position, handling ties by splitting the combined payout.
+    
+    Args:
+        finish_pos: The finish position (0-indexed)
+        payout_df: DataFrame with payout structure
+        dupes_count: Number of entries that are tied (from the 'dupes' column)
+    """
+    if dupes_count == 1:
+        # Single position, no tie
+        matching_row = payout_df[
+            (payout_df['minPosition'] <= finish_pos + 1) & 
+            (payout_df['maxPosition'] >= finish_pos + 1)
+        ]
+        if not matching_row.empty:
+            return matching_row.iloc[0]['value']
+        else:
+            return 0
     else:
-        return 0  # Default value if no match found
+        # Handle tie - sum payouts for the range of positions and divide by number of ties
+        total_payout = 0
+        for pos in range(finish_pos, finish_pos + dupes_count):
+            matching_row = payout_df[
+                (payout_df['minPosition'] <= pos + 1) & 
+                (payout_df['maxPosition'] >= pos + 1)
+            ]
+            if not matching_row.empty:
+                total_payout += matching_row.iloc[0]['value']
+        
+        # Return the split payout
+        return total_payout / dupes_count
 
 def color_roi(val):
     """Color ROI values: green if > 100%, red if < 100%"""
@@ -424,7 +446,7 @@ if selected_tab == 'Data Load':
             working_df = working_df.drop(['sorted', 'index'], axis=1)
             try:
                 working_df['payout'] = working_df['finish'].apply(
-                        lambda x: get_payout_for_position(x, st.session_state['payout_info'])
+                        lambda x: get_payout_for_position(x, st.session_state['payout_info'], working_df['dupes'])
                     )
             except:
                 pass
@@ -505,7 +527,7 @@ if selected_tab == 'Data Load':
             working_df = working_df.drop(['sorted', 'index'], axis=1)
             try:
                 working_df['payout'] = working_df['finish'].apply(
-                        lambda x: get_payout_for_position(x, st.session_state['payout_info'])
+                        lambda x: get_payout_for_position(x, st.session_state['payout_info'], working_df['dupes'])
                     )
             except:
                 pass