Update scoring percentages calculation in app.py to include separate metrics for DraftKings and FanDuel. This change enhances the data structure by introducing 'DK_Runs/$' and 'FD_Runs/$', while also refining the handling of average salary columns for each platform, improving overall data accuracy for player selection.

Update app.py to include 'FLEX5' in player selection for various slate types. This change enhances the data structure for player lineups, ensuring compatibility with expanded player options in the application.

Refactor player selection logic in app.py to improve handling of 'Top (1-5)' and 'Mid (4-8)' conditions. This update introduces additional player selection when the count is less than auto_size_var, ensuring accurate sorting and selection of players, thereby enhancing the application's functionality.

Enhance player selection logic in app.py by adding display of selected players for 'Mid (4-8)' condition. This update improves user feedback by showing the selected players when the count is less than the specified auto_size_var, thereby enhancing the application's usability.

Update player selection logic in app.py to correctly handle additional player selection for 'Mid (4-8)' condition. This change ensures that the logic accommodates the specified auto_size_var, enhancing the accuracy of player selection in the application.

Enhance player selection logic in app.py to ensure accurate handling of auto_size_var for 'Top (1-5)' and 'Mid (4-8)' conditions. This update improves player selection by allowing for an additional player when the selected count is less than the specified size, thereby enhancing the application's functionality.

Fix player selection logic in app.py to correctly handle auto_size_var for 'Mid (4-8)' condition. This adjustment ensures accurate player selection based on the specified size, enhancing the functionality of the application.

Refactor player selection logic in app.py to accommodate dynamic auto size

Refactor player data mapping in app.py to improve position-based logic

Enhance data handling in app.py by expanding player data mapping

Comment out redundant player index setting in app.py to prevent potential errors during data display. This change maintains the existing functionality while improving error handling in the data presentation logic.

Refactor player count logic in app.py to enhance clarity

Refactor opponent and team total mapping in app.py for improved data handling

Refactor data mapping in app.py to simplify opponent assignment

Remove redundant CSS rule for portal element in app.py to streamline styling

Update CSS in app.py to further adjust font size for portal element

Update CSS in app.py to adjust font size for portal element

Add CSS rule in app.py to set font size for table rows

Update CSS selector in app.py to simplify box-sizing implementation

Update CSS selector in app.py to improve layout consistency

Update CSS styles in app.py to enhance layout and box-sizing

Update font size in app.py for improved readability

Enhance styling in app.py for improved readability

Refactor lineup display in app.py to improve styling and readability

Enhance lineup building logic in app.py to support both Draftkings and Fanduel platforms

Add error handling for opponent and team total mappings in app.py

Adjust player selection logic in app.py for 'Mid' category to correct range calculation, ensuring accurate filtering of players based on updated order parameters. This change enhances the user experience in lineup creation.

Update player selection logic in app.py to adjust range parameters for 'Mid' and 'Wrap' categories. Enhanced the selection criteria to ensure accurate player filtering based on updated order ranges, improving user experience in lineup creation.

Refactor player selection DataFrame in app.py to ensure consistent filtering by salary and position. Updated logic to apply filters correctly, enhancing data integrity and user experience in lineup creation.

Refactor player position selection logic in app.py to simplify user experience. Removed conditional check for 'Specific' position selection, allowing direct multiselect input for positions.

Update position selection key in player filters for consistency

Add player filters to app.py for enhanced selection options

Update 'Team_Total' and 'Opp_Total' column mappings in app.py to reference RHH_Info instead of RHP_Info, ensuring accurate data retrieval for team and opponent totals and enhancing data integrity in player selection metrics.

Correct 'Team_Total' and 'Opp_Total' column mappings in app.py to accurately reference 'Opp' and 'Team', respectively, ensuring improved data integrity in player selection metrics.

Refactor 'Team_Total' and 'Opp_Total' column mappings in app.py to utilize drop_duplicates() for improved data accuracy and integrity in player selection metrics.

Refactor 'Team_Total' and 'Opp_Total' column mappings in app.py to utilize the first value from the respective DataFrame, ensuring accurate data retrieval and enhancing the integrity of player selection metrics.

Update 'Team_Total' and 'Opp_Total' column mappings in app.py to use the first value from the respective DataFrame, ensuring accurate data retrieval and improving the integrity of player selection metrics.

Correct 'Opp_Total' column mapping in app.py to reference 'Opp' instead of 'Team', ensuring accurate data retrieval for opponent totals and improving data integrity in player selection metrics.

Correct 'Team_Total' column mapping in app.py to reference 'Team' instead of 'Player', ensuring accurate data retrieval for team totals and maintaining data integrity in player selection metrics.

Fix 'Team_Total' column mapping in app.py to correctly reference 'Player' instead of 'Team'. This adjustment ensures accurate data retrieval for team totals, enhancing the integrity of player selection metrics.

Enhance player data management in app.py by adding 'Team_Total' and 'Opp_Total' columns to the lineup. Updated DataFrame structures and quick fill options to incorporate these new metrics, improving the clarity and depth of player selection information.

Handle potential errors when inserting 'Order' column in roo_data within app.py. Added a try-except block to ensure compatibility with non-integer values, enhancing data integrity during player selection.

Refactor Handbuilder section in app.py to include a slate selection dropdown, allowing users to filter player data based on slate type. Updated team filtering logic to utilize the filtered handbuild_roo dataset for improved accuracy in player selection.

Update quick fill options in app.py to include detailed descriptions for player selection ranges. This change enhances clarity for users by specifying the player order ranges associated with each option.

Enhance player selection logic in app.py by modifying the wrap option to include the first three and last two players based on order. This change improves the flexibility and efficiency of lineup management.

Add quick fill options in app.py to streamline player selection for lineups. Implemented logic to auto-fill eligible players based on team, size, and order preferences, enhancing user experience and efficiency in lineup management.

Add 'Opp' column to roo_data in app.py for enhanced player matchup information. Adjusted column order to improve data organization and clarity in the lineup summary.

Refactor salary display logic in app.py by removing JavaScript dependency for screen width and simplifying column layout. This change enhances the user experience by ensuring consistent presentation of salary information across all devices.

Refactor mobile layout in app.py to enhance salary display by adjusting column alignment and improving HTML formatting. This change ensures consistent presentation of per player salary and leftover amounts across different screen sizes.

Refactor HTML styling in app.py for salary display to improve alignment and visual consistency. Adjusted vertical alignment and margin properties for better presentation of player salary and leftover amounts in the lineup summary.