Experiementing with a high cpt stdev

Update projection calculations in app.py to ensure accurate ownership metrics. Adjusted 'Proj Own' calculations for both 'cpt_working' and 'flex_working' DataFrames by dividing by 100, enhancing the precision of player ownership projections.

Enhance projection calculations by adding 'cpt_Own_map' to mapping logic in app.py. Updated 'Proj Own' calculations for both 'cpt_working' and 'flex_working' DataFrames to utilize the new mapping, improving accuracy in player ownership projections.

Refactor projection logic in sim_contest function to improve clarity and performance. Updated handling of the first column using 'vec_cpt_projection_map' and adjusted the application of 'vec_projection_map' for remaining columns, ensuring consistent simulation calculations.

Fix typo in vectorization of 'cpt_projection_map' in sim_contest function for consistency in simulation calculations.

Added vectorization for 'cpt_Projection_map' in sim_contest function to enhance performance and maintain consistency in simulation calculations.

Enhance player median calculations and projections in init_baselines and sim_contest functions. Added 'cpt_Median' field to raw_display DataFrame for both DraftKings and FanDuel, and updated projection logic to utilize 'cpt_projection_map' for improved accuracy in simulations.

replacing first 7 columns of lineup export with player_ids

maybe not an array in export L471

yeah wasn't an array

referenced the wrong frame, this might break if not an array

aiming to export player IDs

removed use of gspread and transferred to mongo

added some keys to variables

added var for init baselines

Aimed to add NBA as an option for the seed frame source

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