Starcraft AI blog

My proposed daring/solid metric turned out to draw a surprising degree of attention. Well, I was going to try it out anyway, but now I have reason to report in detail. Today I did only the first step, finding the elo values.

I chose to rate the players relative to a fictional opponent that scored exactly 50%, giving the fictional player elo 0, because it was easy that way. The game is zero-sum, so that’s the average player of the tournament, in a sense. We only care about elo differences, so the base is arbitrary.

I calculated the table by hand, which seemed easier for a first cut—I simply printed a big elo table and read it backwards, from winning percentage to elo difference. If the solidity metric works out, I’ll have to automate it. It doesn’t seem hard (maybe invert the function by binary search). In fact, the only reason it was easier to do it by hand the first time is that I’ll have to do it by hand anyway to verify that my code is correct.

Next: I want to draw graphs for each player showing the expected and actual scores against each opponent. That will give a visual indication of how well the metric will work out. If it works well, I’ll choose a way to turn it into a number.