As the integration of a limited set of follower distributions is added to the hot/cold script, it becomes important to try and select the proper sample sizes from the whole history files...

It is one thing to calculate by counting, another entirely to learn how to use the information output... and it becomes obvious that no single system is a magic bullet.

Sticking in the core concept of frequency, the short term data of hot and cold is based on frequency, short term followers are based on frequency.

Once the code is written for initial operation (I am down to implementing the limited draw number and Y offset for the follower function) the difficult part does begin... creating a back test to see how this program plays out across the entire draw history...

I have the requisite building blocks in place, but the most important variable will be the back test offset. This will determine the number of draws to repeat the existing script at different points in time. I feel that the largest data set size, the number of short term followers to collect, will be the deciding factor. Then there is collecting this data in a csv file for further analysis. Coding will proceed anyway, but here are the burning unanswered questions left to answer....

How many draws are required to get an accurate measure of followers? 100, 1,000?

How many draws will it take to get a clear picture of repeatable hot and cold trends?

Is it possible to calculate the statistical significance of the distribution and assign the thresholds of hot and cold based on standard deviation? << actively working on this one.

I think I will be off of playing for quite some time while figuring this one out... 

In other news, while calculating the "most frequent" combo for the PA mid day, it was determined to be 198, that number came out straight yesterday and of course I was NOT playing it... such is life...