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Recently, too few rating points have been issued for winning a game. When defeating an opponent who is 110 points higher, they give me 10 rating points, although earlier it was all 12-13. What is the reason for this? Is this a mistake or will it always be like this now?
@Toadofsky #2: I found that or similar answers in some threads lately. I also noticed that I gain and lose less rating points than previously. I still don't understand why. Why is "stabilizing" a desirable aim - in comparison to the bewilderment you cause in long-standing Lichess-players?
You reduced RD to 50. Why is 50 better than 49? Or 55? I think, after such a value is set, you should stick to it; it is an arbitrary decision anyways.
Thanks , you have just taken the fun out of playing rated games on this site .
#3 The RD floor was reduced from 60 to 50, to stabilize ratings of frequent players.

#4 The RD *floor* was reduced. If you read Glickman's paper, it doesn't have an RD floor; theoretically, ratings provide the greatest predictive accuracy if the RD floor is zero. Which immediately raises the question: what if I improve at the game?

The key difference between Glicko and Glicko-2 is a volatility term to keep track of (within a rating period) whether a player's level of performance is consistent (and if so, RD decreases slower). So if you're an improving player, your rating volatility should be high, causing RD to slowly decrease; conversely, a player who isn't improving or worsening will have a low volatility and a low RD. All that said, RD slowly increases over time to account for uncertainty due to player inactivity.
@Boobie2
You are exaggerating. In practice there is hardly a difference.

@Toadofsky
As far as I understand, this is still not an answer: Why did you change it? Why was 60 a good number for a couple of years, and now it is not? Maybe 50 is a better value first place, but now 60 has been established over a long period of time, and people got accustomed to it. Why should the ratings be stabilized anyways?
The short version: ratings should have predictive accuracy. Having random ratings doesn't make sense. (As I again reread http://www.glicko.net/glicko/glicko2.pdf I think the RD >= 30 in Glicko-1 is unnecessary in Glicko-2 because the volatility term already accounts for improving or declining players. However this raises a question about Glicko-based systems with undefined rating periods and whether volatility terms are stable. As an aside... I've been beating a dead horse about improving Lichess rating system in this forum for years, and only now do people care to chime in... I suppose not everyone reads the forums.)

Thanks to gcp for this analysis/simulation: github.com/ornicar/lila/pull/4034#issuecomment-433472996

Because the RD(phi) increase is applied after every game instead of every rating period, Glicko-2 has much higher RDs by default, causing the ratings to flobber about much more. Empirically, on lichess the majority of players never go below RD=60, there's maybe a dozen or so in my entire dataset (mostly because they managed to get non-default lower volatility, which is also very rare).

After removing the RD >=60 limitation, or putting it to >= 30 (as recommended in the Glicko-1 paper), the prediction performance of this pull (Glicko-2 + sigma scaling over time, aka Lickgo-2) beats Glicko-1 and it's a strong improvement over the current Glicko-2 ratings.

Limiting the RD to 30 or not limiting at all seems to make very little difference [in terms of predictive accuracy]. In general it will grow quickly unless the player is playing a ton of games, in which case their rating is constantly adjusted anyway. So the limit probably just isn't necessary at all.

Glicko 1 prediction rate 56.591%, MSE=0.2250
Glicko 1 (no RD cap) prediction rate 56.618%, MSE=0.2250
Ligcko 2 prediction rate 55.483%, MSE=0.2269
Lickgo-2 (no RD cap) prediction rate 56.729%, MSE=0.2248
lichess prediction rate 55.122%

So, if the minimum RD gets lowered to 30, or removed entirely, it would clearly improve the accuracy of lichess ratings.
What do u mean bt stablising rating of frequent players( to decrease or....)
I mean that a player who has played 100 rated games who loses 1 game should have a smaller rating decrease than a player who has played 10 rated games.

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