Fix column indexing in app.py for FLEX and goalie calculations based on site selection. Updated DataFrame slicing to ensure accurate frequency counts for Draftkings and Fanduel, enhancing data processing consistency in simulations.

Refactor dk_columns in app.py to remove 'W3' from the list, ensuring consistency in data handling. Update raw_display DataFrame to reflect this change, enhancing clarity in data processing for simulations.

Refactor position mapping logic in app.py to use sim_site_var1 for site selection in FLEX column calculations. This change enhances clarity and consistency in handling position mappings for Draftkings and Fanduel, ensuring accurate data processing in simulations.

Enhance position mapping logic in app.py for FLEX columns based on site selection. Implemented conditional mapping for Draftkings and Fanduel, allowing for separate handling of FLEX1 and FLEX2 positions. This improves the accuracy of position counts in simulations.

Update stack summary in app.py to rename 'Position' to 'Stack Size', sort by stack size, and set it as the index. This enhances clarity and organization of stack type statistics displayed in the application.

Update stack multipliers in sim_contest function of app.py to enforce maximum limits, improving accuracy in projection calculations. Adjusted multipliers for team participation to ensure they do not exceed specified thresholds, enhancing the precision of contest simulations.

Adjust stack multipliers in sim_contest function of app.py to improve accuracy in projection calculations. The multiplier values for team participation have been halved, enhancing the precision of contest simulations based on the number of teams playing.

Refactor sim_contest function in app.py to implement stack multipliers for projection calculations, enhancing accuracy based on team participation. Removed unused stack frequency tab from UI, streamlining the user interface and improving overall performance.

Update sharp_split thresholds in app.py for strength categories to improve simulation accuracy. Adjusted values for 'Below Average', 'Average', 'Above Average', and 'Very' to enhance performance metrics in the application.

Enhance app.py by adding a new tab for Stack Type Statistics, which displays average statistics and counts for team stacks. Update existing tabs to include 'Avg Own' in dataframes and improve user feedback when simulation data is unavailable. Additionally, implement a download button for stack frequency data, enhancing data export functionality.

Enhance app.py by adding a teams_playing_count parameter to the sim_contest function, allowing for dynamic adjustments in projection calculations. This change includes the implementation of a stack bonus based on the number of teams playing, improving the accuracy of contest simulations. Additionally, update init_baselines to return the teams_playing_count for better data management across the application.

Enhance app.py by standardizing team abbreviations for Draftkings and Fanduel data, ensuring consistency in data representation. Additionally, clear session state on data export to prevent stale data issues. This improves data integrity and user experience in the application.

Refactor app.py to remove unused player ID dictionaries for Draftkings and Fanduel. This simplifies the code and improves performance by eliminating unnecessary data structures during seed frame initialization and data export processes.

Fix case sensitivity in duplicate removal for Sim_Winner_Export in app.py by changing 'Salary' to 'salary'. This ensures consistent data handling and improves the accuracy of the export functionality.

Enhance Sim_Winner_Export functionality in app.py by adding duplicate removal based on key columns and implementing a download button for exporting the full frame as a CSV file. This improves data integrity and user experience in contest simulations.

Refactor app.py to utilize session state for mapping player data. Updated frequency calculations to reference session state maps instead of local variables, enhancing data consistency and management across contest simulations.

Refactor app.py to enhance data handling and user input. Updated seed frame initialization to accept a dynamic lineup limit, improved data export functionality, and streamlined session state management for contest simulations. Removed unnecessary imports and optimized data retrieval processes.

Refactor app.py to streamline database connection and data retrieval. Removed hardcoded Google Sheets credentials and replaced them with a MongoDB connection. Updated data loading logic to fetch player data directly from the MongoDB collection.

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