Thank you for assembling the data and getting it into a nice chart! Appreciated.
(I knew there was a api, but I thought it was intended for other things… when I get some free time I’ll check it out)
Highest rated account is Handibot[9d+], by the way. Looks like it got the rank from beating Sai repeatedly.
Random shower thought: I wonder if we can get somebody do to the same for other servers? I do realise it would be a mistake to try and combine the data - as some players may have accounts on both servers, but still
It’s a natural thought but whoever knows API for all those other servers.
9k-6k, I would say
10k - 7k . . . … are highest on users who play at least once a year
. . . 8k - 6k . . . .are highest on deviation<160 , deviation<100 and who play at least every half year
. . . . .7k - 5k . . are highest on users who play at least every month/week/day
. . . . . . .6k - 4k are highest on users with at least 2000 games
The Central Limit Theorem does us a great disservice by biasing us to think that the underlying distribution is normal because samples always are “normalish”. It isn’t so. I believe Go rankings are more properly described by some kind of “fat tailed” power law, and am currently tinkering with OGS historical data to see if I can find it. The histogram shows OGS users, which is a biased sample of the universe of potential Go players (most of whom can only place stones randomly on a board).
Looks like a slightly tilted bell curve to me
I wonder if stable players should be counted at deviation less than 70. After update it seems if you play more or less regularly you’ll have like 65 deviation at all times.
I barely ever get to play and my.deviation is still 64… Seems like a reasonable theory
I made a graph with stable players, and multiple histograms through time, normalized. As you can see, as time goes on, peak of players goes down but region with players at 21k gets fatter. Probably more new players joined in 2020.
So I continued my graph building for earlier months. It looks pretty good, a little too good, if you ask me. I wonder if there’s some kind of mistake somewhere. Look how perfectly noob region is swelling up over the years. Could it actually happen naturally?
Additionally I’ll make top post wiki so editability doesn’t expire.
A suggestion: could you make this into an animated GIF, so we can see the hump sloshing over time?
there was a discussion in other topic, your diagram may be so perfect because there is something strange with OGS itself
Ah yes, ratings were re-calculated retroactively on january, i guess it makes historical comparison pointless
Yup totally. in 2017 ogs switched from elo-based rating system to glicko2, this caused the loss of all previous rating data :<
Ranks from that era are still saved on game chats, if you have the time you can look thru old chats and plot the ranks from those ^^
This shouldn’t be the case. It does appear there could have been some kind of error, but part of the reason ratings changes take so long is because
What this actually looks like, is anoek having the server re-run every single ranked game through the new algorithm so that it’s as if the current rating system had been used for all time.
Oh am i mistaken? Is the old elo-based rating data still existing somewhere? I would love to see the old ranks from that time ^^
I think we are confused on what is meant by “data”
I think anoek keeps the old rating system alive for a short time, just in case the new one goes tits up and he needs to roll back…
what I meant by keeping the “data” is that every single ranked game gets re-analyzed, so while you can’t compare the new rank to the old rank through history, the new historical ranks should still operate appropriately, as it’s as if we have had it the whole time…
for some reason, the historical ranks in this case do seem to be off for some reason