It only took a short time to modify the existing python script to loop through all digits for all pick n games and gather the top followers.

Took a bit longer to run through the process of counting the zeros (hits) in each column, but because the follower data created so many extra zeros compared to the modified mirror system it looks like a valid upgrade of the existing software.

The pick 2 was the obvious start point, by the time the first game (mid day) was done I had established an updated work flow that reduced the previous update process by 80%. Script run to finished spreadsheets for all games in less than 1 hour. The longest process was draw history updates and making pick 2 .csv files for the Python part.

The year recap so far...

January saw the follower script in it's original form that had to be run daily to get picks. This system was winless for the majority of the month.

End of January through yesterday saw the new "mirror" system in play. This greatly reduced the need for updates and also picked a winner straight on the pick 3.

Today... the merging of the 2 systems. Keeping with the machine learning concepts of seeking a global minima for each column (highest number of zeros) and the ease of use of that mirror system while integrating the observed frequency of follower data. This will be tested throughout the rest of this month and March.

That pick 3 hit basically returned all of my money spent on both previous systems and will still fund the first 10 attempts of this new system.

Still looking for that elusive pick 5 straight hit. I believe that this progression will get me closer to that goal.

The ultimate refinement of this software structure would be to go through all 10 billion iterations of possible lookup table values but I realize my coding ability is not quite there yet. One day...

Happy Coding!