paper: Weeks 1-2 Elo Analysis

[Michael Hill]

So I decided to take this data a little bit further. What I did was to take all of these calculations and run them through the data this year and try to predict matches. For this, I also included a modified Elo system that has diminishing returns for large margins of victory (Calling this Elo Mod). I got some rather surprising results.

My baseline was just using OPR for predicting match outcomes, it was able to predict about 77.1% of the matches this year. This was calculated by adding up the OPRs of each alliance and comparing with the result of the match. TrueSkill was able to predict 79.0% of the matches, a pretty good improvement. I need to develop the prediction model a bit better because it currently doesn't take into account the standard deviation as a measure of certainty. The modified Elo system was able to predict 79.5% of matches, an improvement over TrueSkill. The baseline, unadulterated Elo system as used in this thread was able to predict a whopping 81.4% of matches, by far the best out of any of these models. There is still room for improvement with the TrueSkill and Modified Elo. With the modified Elo, there are some constants that can be tuned for better results. But overall, the results are somewhat interesting. It seems that no matter the ranking model used, about 1 in 5 qualification matches will result in an upset.

Here is the spreadsheet I used: https://dl.dropboxusercontent.com/u/...Trueskill.xlsx