Update tab styling colors in app.py for improved visual consistency

Update team selection keys to prevent Streamlit key collision

Add team filtering functionality to Player Stat and Prop Trend tables

Enhance prop trends UI by adding an expandable filter section for improved user interaction and interface organization

Merge branch 'main' of https://huggingface.co/spaces/Multichem/NHL_Betting_Models

Add custom Streamlit tab styling to improve UI aesthetics and user experience

Update app.py

Update app.py

Convert prop_table stat columns to float for accurate numerical processing

Refactor app.py to simplify 'over_adj' and 'under_adj' calculations by removing the subtraction of 1 in the conditional logic. This change enhances the accuracy of player projections by directly using the ratio of 'Mean_Outcome' to 'Prop', ensuring a more reliable analysis of prop outcomes.

Refactor app.py to remove 'over_adj' and 'under_adj' from 'Over%' and 'Under%' calculations, streamlining the prop percentage formulas. This change enhances the clarity of player projections by focusing on the weighted averages of 'Over', 'Trending Over', 'Imp Over', 'Under', 'Trending Under', and 'Imp Under', ensuring a more accurate analysis of prop outcomes.

Refactor app.py to improve 'over_adj' and 'under_adj' calculations by adjusting the logic to use conditional checks instead of division, enhancing the accuracy of player projections. Additionally, update 'Bet_check' calculations to incorporate these adjustments, ensuring a more reliable analysis of betting suggestions based on player performance metrics.

Refactor app.py to update 'over_adj' and 'under_adj' calculations by replacing division by 100 with a conditional adjustment using np_where. This change ensures that adjustments are capped at 0.10, improving the accuracy and reliability of player projections based on the relationship between 'Mean_Outcome' and 'Prop'.

Refactor app.py to adjust 'over_adj' and 'under_adj' calculations by dividing by 100, enhancing the accuracy of player projections. This change ensures that the adjustments based on the relationship between 'Mean_Outcome' and 'Prop' are correctly scaled, improving the reliability of prop outcome analysis.

Enhance prop percentage calculations in app.py by incorporating 'over_adj' and 'under_adj' metrics into 'Over%' and 'Under%' formulas. This update improves the accuracy of player projections by factoring in adjustments based on the relationship between 'Mean_Outcome' and 'Prop', ensuring a more reliable analysis of prop outcomes.

Refactor app.py to enhance prop percentage calculations by updating 'Over%' and 'Under%' metrics to use a weighted average approach. This change improves the accuracy of player projections by incorporating 'Imp Over', 'Trending Over', 'Imp Under', and 'Trending Under' with specified weights, ensuring a more reliable analysis of prop outcomes.

Refactor app.py to standardize DataFrame column names for leg_outcomes. Changed 'Imp Over' and 'Imp Under' to 'Over' and 'Under' respectively, enhancing clarity and consistency in prop data handling.

Update prop variable names in app.py for consistency and clarity. Changed 'NHL_GAME_PLAYER_BLOCKED_SHOTS' to 'NHL_GAME_PLAYER_SHOTS_BLOCKED' across multiple instances to ensure uniformity in prop category references, enhancing code readability and maintainability.

Remove unnecessary sleep delays in pull_baselines function to optimize data retrieval process from worksheets. This change enhances performance by eliminating redundant pauses during API calls.

Update worksheet reference in pull_baselines function from 'prop_trends' to 'prop_trends_check' for improved data management.

Introduce sleep delays in pull_baselines function to manage API request rate limits. Added time.sleep(3) before fetching data from 'prop_trends' and 'Pick6_ingest' worksheets to prevent potential throttling issues during data retrieval.

Refactor app.py to streamline prop selection process and improve UI. Consolidated selection logic for game type and book options, enhancing clarity and reducing redundancy. Updated prop category selection based on game type, ensuring a more intuitive user experience.

Refactor app.py to improve UI layout and enhance prop simulation functionality. Introduced a settings container for better organization of selection options, including prop source, book, and prop category. Streamlined the simulation process for player props, ensuring accurate calculations and improved data handling. Updated download functionality for prop sources and projections, enhancing user experience and data accessibility.

Update leg_outcomes DataFrame to include 'Trending Over' and 'Trending Under' columns for enhanced prop data analysis. This change improves the clarity and accuracy of player projections by aligning with recent updates in prop data handling.

Enhance prop data handling by adding 'Trending Over' and 'Trending Under' columns to prop_df and player_df. Update calculations for 'Over%' and 'Under%' to include trending metrics for improved accuracy in player projections.

ping

added poisson var

added poisson math

cleaned up stat run

changed filter process for agg

more prints

fixed source of prop frame for agg

more changes from type to Type

fixed Prop Type from Prop type

changed book selections for pick6

printing some tables

fixed prop options for sim var

removed player as index in prop trends table

fixed prop_table_options

Lots of changes to stat specifc loop, added pick6 functionality

removed a duplicate "book" declaration

added book objects to a bunch of dataframes

changed variable designation in prop sim

Full update to prop sim to fix trends and object orientations

Update app.py

Update app.py

Update app.py

Update app.py

Update app.py

Update app.py