The concept of sums is not new, but it is something I have not worked with. The idea comes from the world of machine learning, in particular feature detection and feature extraction.

The way sums seem to be done for lottery is across one row. Such that a pick 3 number of 1 3 9 has a sum of 13. This provides spatial context to the draw combo. Collecting this data and graphing it will show the distribution of draw sums, compacting the range of all 1,000 possibilities into 28 sums (0 through 27).

From time series analysis, I will be adding a vertical sum of the last 3 draws (for pick 3), this will have the exact same range and provide a temporal context for each column.

What I am looking for is some way to correlate the vertical sums and the horizontal sum to find patterns that emerge that are just not visible when looking at the raw history results.

If you look at the last 3 draws, the horizontal component is just as random as the numbers themselves, however, you already know 2 of the 3 components for the next vertical sum...

The spreadsheet should be super simple to create. Summary statistics on the distribution will take a bit longer. Nothing too difficult. Then the part where actionable intel can be gleaned from the data may take quite some time.

The vertical, or "rolling" sums seem to be more useful than the rolling averages also found in time series data analysis, particularly for the nature of lottery data.

Wouldn't it be interesting if getting a pick was essentially like solving the bottom row of a sudoku puzzle?