Refactor ownership baseline calculations in predict_dupes.py to use set for unique team mapping, improving accuracy and performance.

more printing

printing debug

fixing predict_dupes

Refactor player update logic in projections management by removing redundant comments and enhancing ownership baseline calculations for NFL, NBA, and NHL sports. Adjusted baseline formulas to improve accuracy based on team mapping.

pulling the number up a bit

more adjustments to the way finishing percentiles are handled

adjusting own_baseline into finish_percentile calc

had to add the used of the ownership baseline into the reg dupe predictions

wrote the wrong min/max function

printing

Trying to do some team len scaling on ownership baselines

Update baseline logic in predict_dupes function to adjust own_baseline based on team count for NFL Classic type

adjusting finish percentile to scale

Refactor 'Lineup Edge' calculation in predict_dupes.py to scale by Contest_Size for improved accuracy in contest performance metrics and apply clipping to ensure values remain within a specified range.

Update calculation of 'Lineup Edge' in predict_dupes.py to scale by 10000 for improved accuracy in contest performance metrics.

aiming to fix dupes dropping while increasing size

Refactor SE Score calculation in predict_dupes function to adjust the order of operations, ensuring player diversity is factored in after the score computation. This change enhances the accuracy of the SE Score while maintaining code clarity.

Refactor SE Score calculation in predict_dupes function to incorporate player diversity, enhancing the accuracy of the score. Removed redundant print statement for cleaner output.

Add print statement to display the top 10 SE Scores in predict_dupes function for debugging purposes

Adding SE score

recent changes

Enhance Lineup Edge calculation in predict_dupes.py by normalizing the edge values based on the maximum and minimum edges. This adjustment improves the scaling of the Lineup Edge, leading to more accurate portfolio predictions.

ping

Correct Lineup Edge calculation in predict_dupes.py by changing the adjustment from addition to subtraction based on duplicate ownership. This modification refines the edge computation, improving the accuracy of portfolio predictions.

Update Lineup Edge calculation in predict_dupes.py to include a normalized adjustment based on duplicate ownership. This change improves the accuracy of the edge computation by factoring in the average number of duplicates, enhancing overall portfolio predictions.

Refactor similarity score calculation in predict_dupes.py by removing the reference to duplicate adjustments. This change clarifies the computation of player selection diversity while preserving the overall prediction model's integrity.

Refactor Lineup Edge calculation in predict_dupes.py by removing the duplicate adjustment and simplifying the formula. This change enhances clarity in the computation while maintaining the integrity of the prediction model.

ping

Refactor Lineup Edge calculation in predict_dupes.py to incorporate both raw edge and adjusted edge values. This change enhances the accuracy of the prediction model by averaging the adjusted edge with the raw edge, improving overall portfolio predictions.

Adjust Lineup Edge_Raw calculation in predict_dupes.py to include a constant offset, enhancing the accuracy of the edge computation for portfolio predictions.

Refactor Lineup Edge calculation in predict_dupes.py to utilize the raw edge value for duplicate adjustment. This change clarifies the computation and maintains the integrity of the prediction model.

Update Lineup Edge calculation in predict_dupes.py to separate raw edge computation. Adjusted the formula to remove the scaling based on duplicates, enhancing clarity and maintaining prediction accuracy.

ping

Refine Lineup Edge calculation in predict_dupes.py to adjust the edge based on the mean of duplicates. This update improves the accuracy of the prediction model by incorporating a scaling factor related to the average number of duplicates.

Refine Lineup Edge calculation in predict_dupes.py to average the adjusted edge based on the number of duplicates. This update enhances the prediction model's accuracy and performance.

diverting

Refine Lineup Edge calculation in predict_dupes.py to improve accuracy. Adjusted the formula to incorporate a divisor of (Dupes + 1) and modified the scaling factor, enhancing the prediction model's performance.

ping

Refine Lineup Edge calculation in predict_dupes.py to enhance accuracy. Updated the formula to adjust the edge based on the number of duplicates, improving the prediction model's performance.

Refactor Lineup Edge calculation in predict_dupes.py to improve accuracy. Updated the formula to average the adjusted edge based on the number of duplicates, enhancing the overall performance of the prediction model.

Add memory-efficient ranking calculation in predict_dupes.py

Update diversity score calculation to use chunked processing for improved performance in predict_dupes.py

Implement chunked processing for player similarity score calculation to enhance memory efficiency in predict_dupes.py

finalized dupe math, maintaining on staging

another small adj

SMALL adj

Update dupes calculation in 'predict_dupes.py' by changing the denominator in the scaling factor for CPT_Own_percent_rank from 100 to 90, aiming to further enhance prediction accuracy.

Adjust dupes calculation in 'predict_dupes.py' by modifying the salary scaling factor from 0.96 to 0.98, aiming to enhance prediction accuracy.

ping