Enhance match output in app.py: update the display of matched portfolio names to include matching scores, improving user feedback and providing more detailed insights into the matching process.

Add match confirmation output in app.py: include a statement to display matched portfolio names, enhancing user feedback and improving traceability of the matching process.

Add unmatched names warning in app.py: implement logic to identify and display portfolio names without matches in projections, enhancing user feedback and improving data validation during the matching process.

Add portfolio name extraction and matching in app.py: implement a new function to retrieve unique player names from the portfolio, enhance name matching logic, and update session state with matched names for improved data consistency and analysis.

Remove redundant update of projections_df in app.py: eliminate unnecessary reassignment of projections_df with name mismatches, streamlining the session state management and improving code efficiency.

Enhance name matching process in app.py: streamline the handling of player names by implementing a more efficient matching algorithm, updating session state management, and improving debug output for better traceability of matches.

Refactor name standardization and mapping logic in app.py: introduce functions for creating site mappings and standardizing player names, improving code organization and efficiency in handling name variations across dataframes.

Refactor name matching logic in app.py: streamline the process of creating the name ID mapping and matching player names, improving efficiency and clarity in data handling.

Refactor debug output in app.py: adjust the placement of the export dictionary display statement to ensure it appears after applying matches, improving clarity in data processing verification.

Add debug output in app.py: include a statement to display the export dictionary after applying matches, aiding in the verification of data processing.

Update weighted ownership calculation in predict_dupes.py: adjust the multiplication factor for ownership values and change the return value to a larger scale, enhancing the accuracy of percentage representation in ownership metrics.

Refactor calculate_weighted_ownership function in predict_dupes.py: remove debug print statements, adjust ownership value calculations to handle percentages, and ensure the return value is in percentage form, improving clarity and accuracy of ownership metrics.

Add debug statements in calculate_weighted_ownership function: include print statements to trace input values and intermediate calculations, aiding in the debugging process for ownership metrics.

Add weighted ownership calculation in predict_dupes.py: implement a new function to calculate weighted ownership values, enhancing the accuracy of ownership metrics in portfolio analysis.

Refactor filter form keys in app.py: rename filter form keys to 'macro_filter_form' and 'micro_filter_form' for improved clarity and organization in the filtering options.

Refactor filter options in app.py: rename 'Filter Options' to 'Macro Filter Options' and streamline the filter form by consolidating stack selection logic, enhancing user experience and clarity in filtering functionalities.

Update ownership nerf logic in predict_dupes.py: implement sport-specific adjustments for CS2, allowing for differentiated ownership ratio calculations based on sport type, enhancing accuracy in duplication predictions.

Enhance portfolio calculations in app.py: implement sport-specific logic for CS2 to differentiate salary, median, and ownership calculations for Captain and FLEX positions, improving accuracy in player statistics and overall portfolio analysis.

Enhance ownership calculations in predict_dupes.py: add support for an additional FLEX5 ownership column, improving the accuracy of duplication predictions for CS2 portfolios and ensuring comprehensive analysis of player ownership metrics.

Refactor ownership calculations in predict_dupes.py: remove redundant ownership columns for CS2, streamlining the duplication prediction logic and enhancing performance in portfolio analysis.

Update sport selection in app.py: add 'CS2' to the sport selection dropdown, expanding user options for game type selection.

Update portfolio duplication prediction in app.py: modify predict_dupes call to include sport_var, enhancing the accuracy of duplication metrics based on sport-specific logic.

Refactor portfolio duplication prediction in predict_dupes.py: enhance the function to accommodate sport-specific logic for CS2, improving ownership calculations and ensuring accurate duplication metrics based on player ownership and salary. Update app.py to pass sport_var to predict_dupes for better context in calculations.

Remove export dictionary display in app.py: eliminate the output of the export dictionary contents to streamline the user interface and focus on essential information during portfolio processing.

Enhance export file processing in app.py: implement mapping for non-excluded columns in the export file using the export dictionary, ensuring improved data accuracy during portfolio downloads.

Enhance export file processing in app.py: add mapping for non-excluded columns in the export file using the export dictionary, improving data accuracy during portfolio downloads.

Refactor name matching process in app.py: optimize the matching logic by processing names individually with extractOne for improved efficiency, while maintaining the handling of name-to-ID mapping and ensuring consistent debug output for better user feedback.

Refactor name matching process in app.py: streamline the handling of name-to-ID mapping and matching logic, ensuring consistent debug output while maintaining clarity in the export dictionary assignment, enhancing overall efficiency and user feedback.

Add detailed debug output for name matching process in app.py: include additional print statements to provide insights into the name-to-ID mapping, number of names to match, and results of the matching process, enhancing visibility for debugging and user feedback.

Refactor name matching and export dictionary handling in app.py: streamline the name-to-ID mapping process by ensuring it only occurs when necessary, and enhance match handling by fixing the conversion to match_dict, improving overall efficiency and user experience during exports.

Refactor export dictionary handling in app.py: simplify the export dictionary assignment by using match_dict directly and enhance user feedback by displaying the export dictionary in the app interface.

Improve name matching logic in app.py: enhance the match validation by adding a threshold check and retain original names for unmatched entries, along with debug output for better visibility into the matching process.

Add debug output for export dictionary in app.py: include a display of the generated export dictionary to enhance user feedback and facilitate debugging during the export process.

Refactor name-to-ID mapping and matching logic in app.py: streamline the process by consolidating the mapping and matching steps, improving efficiency and maintaining user experience during exports.

Add fuzzywuzzy to requirements.txt: include fuzzywuzzy library for enhanced string matching capabilities alongside rapidfuzz.

Update requirements.txt: replace fuzzywuzzy with rapidfuzz to enhance performance in export matching functionality.

Enhance export matching functionality in app.py: replace fuzzywuzzy with rapidfuzz for improved performance, and streamline the name-to-ID mapping process by processing all names in a batch, enhancing efficiency and user experience during exports.

Refactor export matching logic in app.py: move the name-to-ID mapping and best match application to a dedicated button, improving user interaction and streamlining the export process while removing redundant debug messages.

Implement button for export matching in app.py: add a button to initiate the creation of a name-to-ID mapping and apply best match logic, enhancing user interaction and functionality during the export process.

Add debug messages in app.py: include notifications for the start and completion of name matching to enhance user feedback and improve debugging capabilities.

Refactor tab structure in app.py: remove the 'Late Swap' tab and adjust related logic to streamline user interface and improve overall functionality in portfolio management.

Add debug messages in app.py: include 'initiated' notifications during portfolio trimming processes to enhance user feedback and improve debugging capabilities.

Update trimming variable options in app.py: add 'Geomean' to the selection for trimming variable, enhancing user choice in portfolio analysis.

Fix typo in geometric mean calculation in predict_dupes: rename 'Goemean' to 'Geomean' for consistency and clarity in portfolio analysis.

Add geometric mean calculation in predict_dupes: introduce a new column 'Goemean' to compute the geometric mean of ownership percentages, enhancing portfolio analysis capabilities.

Enhance export options in app.py: introduce a selection for 'Simple' or 'Advanced' download types, allowing users to choose between direct portfolio export or customized stack adjustments, improving flexibility and user experience during data export.

Adjust column widths in filter options of app.py: modify the layout to improve the visual balance and user experience in the filter options section.

Update export file handling in app.py: add logic to initialize the export file from the portfolio when no export file exists, enhancing data management and ensuring a seamless user experience during portfolio updates.

Update download button logic in app.py: modify the export file availability check to ensure the download button is only shown when the export file exists, improving user experience and preventing errors during download attempts.

Refactor portfolio copy handling in app.py: simplify the logic for creating a portfolio copy and streamline export file updates, enhancing data management and user experience during portfolio interactions.