Enhance overall stats retrieval in app.py: implement conditional logic for NBA and WNBA leagues to customize data frame structure and column renaming, improving data handling and clarity for player statistics.

Refactor league variable usage in app.py: replace hardcoded 'NBA' string with direct argument in load_overall_stats function calls, improving code clarity and maintainability.

Add WNBA database support in app.py: modify connection initialization and update overall stats retrieval to handle both NBA and WNBA data, enhancing functionality for player statistics management.

Update player ID processing in app.py: modify Fanduel data frame to split player IDs at the last hyphen, ensuring accurate mapping and enhancing data integrity during export.

Refine player ID processing in app.py: update Fanduel data frame to split player IDs at the last hyphen, ensuring accurate mapping and improving data integrity during export.

Refine player ID processing in app.py: update Fanduel data frame to remove the last four characters from player IDs, ensuring accurate mapping and improving data integrity during export.

Update player ID mapping in app.py: modify Fanduel data frame to remove '-mvp' suffix from player IDs and ensure accurate mapping for Showdown slate types, enhancing data integrity during export.

Enhance overall stats retrieval in app.py: add separate data frames for Draftkings and Fanduel to improve player ID mapping and streamline data handling during lineup processing.

Refine lineup data retrieval in app.py: update database queries to filter teams with less than 6 players for both Draftkings and Fanduel, enhancing data accuracy and lineup generation.

Enhance data export functionality in app.py: add separate download buttons for optimal lineups by player names and IDs, improving user experience and data accessibility.

Update data export column handling in app.py: increase the number of columns processed for Showdown slate types in both Draftkings and Fanduel, ensuring accurate player ID mapping and enhancing data export functionality.

Implement conditional data export logic in app.py: enhance the data export functionality by incorporating slate type (Regular or Showdown) for both Draftkings and Fanduel, ensuring accurate player ID mapping and improving data handling during export.

Remove 'working_seed' from session state in app.py: implement logic to delete 'working_seed' when switching between sites, ensuring accurate data handling and preventing stale data issues during lineup processing.

Refactor working seed initialization in app.py: update logic for setting working seed based on slate type (Regular or Showdown) for both Draftkings and Fanduel, ensuring accurate lineup data handling and improving code clarity.

Enhance summary statistics generation in app.py: implement conditional logic for slate type (Regular or Showdown) to accurately compute metrics for Draftkings and Fanduel, improving data representation and user experience.

Refactor lineup initialization in app.py: remove try-except blocks for lineup creation, ensuring consistent DataFrame initialization for both Draftkings and Fanduel across Regular and Showdown slate types, enhancing code clarity and reliability.

Update salary input fields in app.py: adjust minimum salary values for both lowest and highest salary inputs to enhance user experience and ensure valid input range.

Update slate selection logic in app.py: enhance raw baseline retrieval by incorporating slate type (Regular or Showdown) for both Main and Secondary slates, improving data accuracy based on user input.

Add debug output in load_overall_stats function of app.py: print top 10 sorted player statistics for improved visibility during data processing.

Enhance app.py: add support for selecting slate type (Regular or Showdown) in the UI, update site selection logic to accommodate new slate types, and adjust column layout for improved user experience.

Fix player ID column naming in load_overall_stats function of app.py: update column name from 'player_ID' to 'player_id' for consistency and rename it back to 'player_ID' for display purposes.

Enhance app.py: add support for secondary slate data retrieval and processing, update overall stats function to include new data, and improve data export functionality for both Draftkings and Fanduel

Refactor app.py: streamline connection initialization by removing unused Google Sheets credentials and enhance lineup functions to support multiple slate designations for improved flexibility

Refactor load_overall_stats function in app.py: remove backlog data retrieval and associated UI elements to streamline data handling and improve performance

Update display_proj assignment in tab1: set index to "Player" with drop option for improved data handling

Refine "Player" column configuration in tab1: set fixed width properties to enhance layout consistency and maintain sticky header functionality

Enhance dataframe display in tab1: add column configuration for "Player" to improve readability and maintain sticky header functionality

Update tab styling: change background colors for active and hover states to enhance UI consistency

Update display_proj handling in tab1: comment out index setting and add hide_index option to dataframe display

Reorganize tab2 data loading and expander layout

Refactor tab1 display options layout and improve UI organization

Minor UI refinement: Rename "Display Options" to "Data Options" expander

Refactor tab2 layout with expanded display options and improved data management

Enhance tab styling and move display options into an expander

Add salary range filter to projection display

Fine-tune dataframe styling in simple view projection display

Adjust font size in simple view projection display

Improve simple view display with font size adjustment

Remove Team column from simple view projection display

Reorganize tab1 layout and improve site/slate selection logic

Refactor tab1 layout and improve user interface for ROO projection view

Update ROO percentage formatting to use percentage sign

Add custom formatting for ROO percentage columns in player projection display

Refactor player frequency tables to include salary and improve formatting

Add player salary to simple view summary DataFrame

Update simple view to display player ownership instead of value multiplier

Modify view options and remove debug print statements in lineup initialization

Enhance DK and FD lineup initialization by mapping player names from database collections. Added functionality to convert player identifiers to names for improved display in lineups.

export file now uses player IDs

I'm not actually sure if this works