@Animiral, @GreenAsJade, “time spent thinking” wouldn’t work with correspondence. And I’m not sure what else we’ll get from that. 13k spike is basically because of people with 0 ranked games (even 1 game is enough to throw off you from 13k). Distributing ranks to bins according to probability that they have one rank of another sounds way too complicated to be honest. Simple filtering is better, but I don’t think in these particular graphs it matters much. For example, for overall rank histogram I separated them, in post №1. In terms of filtering I think it’s best to use rating points, after all Glicko deals with rating and ranks are there just for convenience. 100 sounds about right, maybe a bit higher, like 125.
Looks like it’s almost impossible to get deviation lower than 60. Point on the far right is GnuGo with deviation of 59 and 173831 played games. And you can see a high point of 355 deviation which is higher than starting 350, kinda weird how that would work.