Got the Python program working, now I need to modify the column processing to take the last angle using lastAngle = df.iloc(-1) so each column has the correct angle instead of displaying all 19 angles for every column. Should be an easy modification.

Up next is using the visualization tool to show valid vectors (their angles being most important at this time) i will run the script 10 times with lead in numbers 0 through 9 and take a pic of each, in order. This should help simplify the pick process. This makes it faster and limits the information displayed to only the relevant angle in question for each column. BIG gains in speed and efficiency when scaling up later to the big games.

Start with the highest frequency follower angle and if it appears in the valid list of 10 for the last drawn number, that is your pick. If it is not on the list then it violates the upper or lower bound constraint, therefore check the next most frequent.

Spent time making sure the spreadsheets are all perfect. Plan for today...

1. Get the script exactly where it needs to be

Modicy the visualizer to get photos of all possible angle lead ins (the time consuming part)

2. Update all draw histories (last was 8/17)

3. Export the required .csv data (the other time consuming part)

4. Figure out and record the exact steps to make a pick.

If all goes well, might have a live test by the weekend!