[brennonbrimhall]

There are quite a few ways out there to predict matches numerically and mathematically. One of the methods Team 20 has been using is using our scouting data to generate a normal distribution for the match (as part of our collaborative scouting efforts, six scouts scout each robot each match). By adding the average scores for each robot on each alliance, subtracting each alliance's sum score from each other, adding the variances, and taking the square root of those variances to find the standard deviation, we then can figure out what percentage of the normal curve's area is past zero.

I'm looking for other ways to predict matches. Besides going through each match and predicting it for yourself, what are some of the way you/your team predict match outcomes? How accurate are your models?