Enhance app.py to include F1 in sport selection and implement position and team variable assignments based on selected sport. Update projections to reflect these variables for GOLF, TENNIS, MMA, NASCAR, and F1, improving data handling for player eligibility.

Refactor app.py to enhance user interface by updating form button labels to "Portfolio" and "Export" for clarity. Introduce informative messages to guide users on the functionality of each button, improving overall user experience in data submission processes.

Update app.py to correct data assignment by replacing 'working_frame' with 'export_base' for parsed_frame. This change ensures accurate filtering based on duplication and salary criteria, enhancing data integrity in the export process.

Refactor app.py to streamline data handling by removing 'display_frame_source' checks. Update working_frame and export_merge assignments to ensure consistent data processing across functionalities, including filtering, trimming, and exposure management, enhancing overall code clarity and maintainability.

Enhance app.py to differentiate data handling based on 'display_frame_source'. Implement conditional logic for working_frame and export_merge updates in various functionalities, including filtering, trimming, and exposure management, ensuring accurate data processing for both Portfolio and Base sources.

Refactor display frame handling in app.py to use a unified session state variable. Update references to 'display_frame' to ensure consistency and improve data management across various functionalities, including player and stack analysis.

Update default target exposure value in exposure management form from 0.25 to 0.50 for improved user experience.

Add salary, median, and ownership calculations for Classic and Showdown types in exposure_spread function

Enhance exposure_spread function by adding salary_max parameter for improved salary filtering and adjusting lineups_to_remove calculation to a 125% factor, refining player selection logic and ensuring existing players are excluded from comparable options.

Enhance exposure_spread function to include an option for removing specified teams, improving flexibility in player comparison and exposure calculations.

Refactor dupes calculation in predict_dupes function to incorporate ownership ratio adjustment based on Contest_Size, enhancing the accuracy of duplicate predictions. Additionally, modify the calculation to use a salary ratio of 50 for improved precision.

Refactor captain ownership calculation in app.py to simplify logic by removing unnecessary type variable check, ensuring accurate ownership adjustments when captain ownership data is missing.

Remove type conversion for 'Own' column in predict_dupes function and add debug print statement to display the first 10 rows of the working frame, aiding in data verification.

Add support for LOL in app.py and related functions, updating sport selection and eligibility checks across multiple modules to include League of Legends, enhancing overall functionality and user experience.

Update exposure selection logic in app.py to conditionally display stack maintenance option based on the presence of 'Stack' column in the working frame, defaulting to 'No' if absent.

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Refactor player statistics calculation in exposure_spread function to handle GOLF sport-specific logic, ensuring accurate lineup counts and averages for players across Captain and FLEX positions.

Update exposure_spread function call in app.py to include type_var parameter, ensuring sport-specific logic is applied during player eligibility checks and enhancing the accuracy of player replacements.

Enhance exposure_spread function to include sport-specific position eligibility checks, ensuring accurate player replacements based on their eligible positions across various sports.

fixed exposure_player default var

Add exposure management feature in app.py and implement exposure_spread function

Add stratification functionality and enhance portfolio handling in app.py

Update MLB player name mappings in app.py to include 'Temi Fágbénlé' and 'Temi Fagbenle', improving accuracy in player recognition.

Add player combination analysis feature in app.py and implement analyze_player_combos function. This update introduces a new tab for analyzing player combinations, allowing users to select combo sizes and view statistics on the most common player pairings or triplets, enhancing the analytical capabilities of the application.

Update player name mappings in app.py for MLB to include 'Jakob Bauers' and 'Jake Bauers', enhancing accuracy in name recognition.

Remove NASCAR table display from app.py to streamline portfolio presentation and improve user experience. Update name mapping logic in load_dk_fd_file.py to enhance ID handling and ensure cleaner data output.

Add table display for NASCAR portfolios in app.py to enhance data visibility for NASCAR users.

Update sport selection in app.py to include 'NASCAR' in the options, enhancing user choice for sports selection.

Change dataframe display from table to interactive dataframe in app.py for enhanced user experience and improved data visualization. This update maintains the existing styled formatting and background gradients.

Enhance dataframe display in app.py by applying styled formatting and column configurations for improved visual representation. This update includes background gradients and custom number columns to better convey statistical data in the user interface.

Replace dataframe display with table in app.py for improved performance and simplicity. This change enhances the user interface by streamlining the presentation of paginated data.

Enhance stack summary management in app.py by introducing session state checks for 'origin_stack_exposures'. This update ensures accurate stack statistics are displayed based on user settings and improves data handling for stack summaries during portfolio interactions.

Refactor name matching analysis in app.py to streamline the process of matching portfolio and projection names. This update enhances the accuracy of name matching, improves session state management, and ensures proper handling of unmatched names during user interactions.

Refactor name matching analysis in app.py to ensure execution only occurs when 'origin_portfolio' is absent. This update improves the accuracy of player name matching and enhances session state management for portfolio and projections, ensuring proper data handling during user interactions.

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Update session state condition in app.py to prevent analysis execution when 'origin_portfolio' is present. This change enhances the accuracy of the name matching analysis by ensuring proper data handling based on user interactions.

Update player name lists in app.py to include additional entries for MLB, enhancing accuracy in player identification and lineup generation.

Refactor import statements across multiple files to replace 'fuzzywuzzy' with 'rapidfuzz' for improved performance and consistency in string matching functionality. Additionally, clean up unused imports in app.py and related global functions to enhance code clarity and maintainability.

Refine session state condition in app.py to ensure player summary assignment only occurs when the display source is 'Portfolio'. This change enhances the accuracy of player statistics management during user interactions.

Add session state management for 'settings_base' in app.py to improve portfolio handling during user interactions. This change ensures the correct initialization of session state when working with the portfolio, enhancing overall user experience.

Refactor session state management in app.py to enhance portfolio reset functionality and streamline player summary assignment. Introduce logic to toggle 'settings_base' state during form submissions, ensuring accurate handling of player exposures and improving user experience.

Update session state key in app.py from 'origin_player_exposures' to 'player_summary' to improve player statistics management and ensure accurate data handling during lineup generation.

Update player summary management in app.py to ensure accurate session state handling. On portfolio reset, copy player exposures to maintain consistency. Refactor player summary assignment logic to streamline data flow and enhance user experience.

Refactor player statistics calculation in app.py to streamline logic for 'Showdown' and 'Classic' formats. Introduce session state management for player exposures when the source is 'Portfolio', enhancing lineup generation accuracy and user experience.

Enhance preset functions in app.py and related modules to include 'sport' parameter for improved flexibility in lineup management. This update modifies the small_field_preset, large_field_preset, volatility_preset, hedging_preset, and reduce_volatility_preset functions to accommodate sport-specific logic, enhancing user experience and accuracy in lineup strategies.

Update player name lists in app.py to include 'Joseph Cantillo' and 'Joey Cantillo' for improved accuracy in lineup management. This change ensures correct player identification in the MLB context.

Remove 'Reduce Volatility' option from preset selection in app.py to streamline user choices. This change simplifies the interface for lineup management, focusing on the most relevant presets for users.

Add 'Reduce Volatility' preset option in app.py and implement reduce_volatility_preset function. This update enhances user options for lineup management by allowing users to manage volatility in their selections, improving overall portfolio strategy.

Similarity Score > Diversity

Update sorting variable options in app.py to include 'Own' and 'Weighted Own' for enhanced user selection. This change improves the flexibility of variable sorting, allowing for more tailored data analysis.