Sort working portfolio by 'median' before resetting index in distribute_preset.py to enhance player selection accuracy. This change ensures that the highest median values are prioritized in the distribution process.

global_func/distribute_preset.py

@@ -60,7 +60,7 @@ def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols:
                 lambda row: not any(player in list(row) for player in player_out), axis=1
             )
             working_portfolio = working_portfolio[remove_mask]
-            working_portfolio = working_portfolio.reset_index(drop=True)
+            working_portfolio = working_portfolio.sort_values(by='median', ascending=False).reset_index(drop=True)
             curr_own_type_max = working_portfolio.loc[0, 'Similarity Score'] + (slack_var / 20 * working_portfolio.loc[0, 'Similarity Score'])
 
             for i in range(1, len(working_portfolio)):