[Ether]

Originally Posted by ngreen

Thanks for providing these.

I'm glad you've found them to be useful.

@all_readers: if there is any additional available raw data that you would like to analyze and which isn't included in the CSVs I am posting, let me know and I'll see if I can add it.

I wanted to instead calculate team-based scores from the alliance-based scores (basically OPR). I expect this could be done in Tableau with scripting, but I ended up doing this in Excel, building the matrix (by copy/pasting the 3 team alliances for each permutation (1&1,2&2,3&3,1&2,2&1,1&3,3&1,2&3,3&2), and then using a series of countifs to fill the matrix). And then solving Ax=b in Excel for each. I then exported a CSV

There's a much simpler way to get OPRs. Caleb Sykes posts a large XLSX spreadsheet here. And Team 2834 maintains an XLXM scouting database here.

Or with just a little bit of effort using AWK (or Python) and Octave (or Matlab) you can easily create a CSV of OPR values for any raw data that has match-by-match scores:

Here's a complete AWK script that reads an 8-column whitespace-separated plaintext file that contains the fields red1 red2 red 3 blue1 blue2 blue3 redscore bluescore, and outputs the team list column vector T, the alliance scores column vector b, and the sparse binary 2MxN design matrix A (M is number of matches, N is number of teams).

Here's an Octave script that reads the AWK output and computes OPR.

I only started looking at match data a few days before our regional. Not having the API/JSON experience, I did have a student begin to compile match data manually. However, by lunch Friday I knew we didn't have resources to even make that work.

What match data are you referring to, and what were you trying to compile manually? I post all the raw match data as CSV files.