Maximize R squared using solver DOCUMENT ATTACHED (may be difficult)

smeador

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Hey guys,

I'm creating an algorithm for daily fantasy basketball and I have hit a little roadblock.

Here is the link to download my spreadsheet:

View attachment Linest Solver.xlsx


Now the data at the top is pulled from a database I have created on another sheet that I have omitted for these purposes. So the premise is, each playe'r's performance in basketball can be predicted by a different set of statistics. In the B column I have listed some of the ones I have come up with so far. The "Actual" data is the Y data for the Linest function I wish to run.

This will be a much easier question to answer if you download the file. I have put 0's or 1's in the A column beside each of the data types. I then have a data array beginning in B17 that displays the rows with 1's next to them as adjacent columns. Then starting in D30, I run a dynamic Linest Function on the displayed array using offset functions and row/column count functions in order to select the data displayed in the step in the previous sentence.

ANYWAY, if you MANUALLY change the 0's and 1's the data does change with it and everything is accurate. If you make all the rows a 1, then all the rows will display as adjacent columns below, if only 7 then 7 adjacent columns will show, etc.

Having only a working knowledge of using solver at THIS level (I've done basic binary situations before), I cannot spot the reason why the solver wont change the 0's and 1's to maximize the R squared value in D32. Again, if I manually change the 0's and 1's I can maximize this value with trial and error, but I thought that was what the iterations in Solver were for.

If you have any suggestions about how I can go about fixing this PLEASE let me know, as manually doing these situations would be impossible due to the volume required (this is on one player's data). And PLEASE download the file so that your answer does not depend fully on my explanation.
 
Select Solving Method = Evolutionary

Your problem is non-smooth (binary are jumps). Suggest also reduce convergence, unless you have a really fast PC :) .0001 probably more than enough.
Also R squared is by definition <=1 and you are looking for the maximum so remove constraints on solution
 
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