Replace distribute_preset with hedging_preset to manage player exposure in lineup generation. Update app.py to reflect the new preset option and remove the obsolete distribute_preset function. This change enhances the flexibility of lineup strategies by allowing users to hedge against high-exposure players while maintaining performance metrics.

Refactor large_field_preset function to streamline player removal logic by eliminating unnecessary iterations and simplifying the exposure tracking process. Ensure sufficient lineups are generated before finalizing selections, enhancing overall efficiency and accuracy.

Enhance large_field_preset function to improve player exposure tracking by implementing a mechanism to remove high-exposure players across iterations, ensuring lineup integrity and preventing excessive ownership. Adjust logic to check for sufficient lineups before finalizing selections.

Refactor large_field_preset function to streamline the portfolio selection process by removing unnecessary iterations and simplifying the logic for team-based filtering, enhancing efficiency and lineup accuracy.

Enhance small_field_preset and large_field_preset functions to accept an additional parameter for excluded columns, improving filtering capabilities and lineup accuracy. Update app.py to reflect these changes in preset selections.

Refactor large_field_preset function to adjust filtering criteria, replacing 'Finish_percentile' with 'Own' for team-based selection, enhancing accuracy in lineup targeting and improving the logic for dropping rows based on ownership thresholds.

Refactor large_field_preset function to simplify ranking logic by removing median and finish percentile rankings, and adjust filtering criteria to focus on 'Finish_percentile' for team-based selection, enhancing accuracy in lineup targeting.

Remove filtering of working_portfolio by 'Lineup Edge' in large_field_preset function to allow for broader selection of portfolios, enhancing lineup options.

Update ranking logic in large_field_preset function to sort 'median' in descending order and 'Finish_percentile' in ascending order, enhancing accuracy in team-based filtering and lineup targeting.

Refactor large_field_preset function to improve team-based filtering by introducing median and finish percentile rankings for enhanced sorting accuracy. Clean up temporary columns after processing to maintain DataFrame integrity.

Refactor large_field_preset and small_field_preset functions to use 'Stack' instead of 'Team' for team-based filtering, ensuring consistency in portfolio adjustments and improving accuracy in lineup targeting.

Refactor large_field_preset and small_field_preset functions to enhance lineup targeting: increase slack_var range, implement team-based filtering, and consolidate results into a single DataFrame for improved accuracy in portfolio adjustments.

Refactor large_field_preset function to improve sorting logic: change the final return statement to sort by 'Finish_percentile' instead of 'Own', ensuring more accurate lineup targeting based on performance metrics.

Add large field preset functionality in app.py and implement large_field_preset function for improved lineup targeting. Update small_field_preset function to sort by 'Own' for consistency in portfolio adjustments.