How correct is the chess.com rating

You gave me the wrong answer by saying that the reason that (w+0.5d)/(w+d+l) is not adopted is that it is impossible for 100001 persons to play against 100000 persons. The real reason is that strong players do not want to play with weak players. And scientists did not find a way to adjust (w+0.5d)/(w+d+l) to give more points when you beat a strong opponent than when you beat a weak opponent, that is why Elo was invented. I have found a way to adjust it but I can't see how correct it is, and it needs a matrix with past results of quite a few championships, which I have, but I don't explain here . The correct adjustment would most probably be better than Elo Truskill and Glicko  because it divides the points with the number of games w+d+l. Perhaps you can locate the adjustment, think of it as soccer teams and half of the teams in e.g. 8 games (of the last season) have faced weak opponents and half have faced strong opponents (but without the adjustment the only clue of weakness or strength is the (w+0.5d)/(w+l+d)).  The rating of those whose who faced strong opponents should be greater that the rating who faced weak opponents (given that they all achieved equal (w+0.5d)/(w+d+l)? No because then they are all of egual strength).  Note that if all players have played against each other once, the adjustment should be equal to the no adjustment, because each has faced opponents of the same strength as every other player.                                                           

By the way,  a player of high rating earns 8 Glicko points for each win against a player of equal rating as his? I earn 8 points when I win against a player of equal rating as mine, and my rating is below 1000 for the moment.

But there is another problem (that Elo did not perhaps consider and Truskill and perhaps Glicko came with an answer), that there is a need for another adjustment that gives a more true rating when the number of games is very small, e.g. just one. There you need a very difficult to apply Bayesian inference. So I don't bother with that, it is very difficult to apply it whereas I had grasped it and applied it with easy maths.

You don't need to grasp difficult maths to judge on these matters. Easy maths will do.

r/iamverysmart

The chess.com rating system is more or less correlated with actual FIDE eating system. Plus or minus hundred points. 

It seems nobody can answer my questions. Here is a relevantly easy one: How many games are needed to reach the rating of the player with the highest rating:

1.) With the chess.com rating and the fact that the 2 opponents are of almost the same rating, e.g starting with my current rating of ~900.

2.) With the (wins+0.5draws)/(wins+draws+losses) rating, if the 2 opponents of each game were not of almost the same rating, but opponents were chosen randomly from all ranges of ratings.

If with no 2 are required fewer games, then the chess.com is an “Elo hell” and No2 should be adopted (and e.g. strong players be forced to face weak opponents too), or at least some kind of modification to the chess.com methodology (rating and/or facing opponents from all ranges of ratings) should be applied.

("Elo hell" perhaps means something else).

Perhaps I would be able to calculate it myself, but I do not know e.g. how many Glicko points are gained for each win when 2 players of high rating confront each other.

I can't answer your question because I am not educated, but glicko bases your rating gains/losses off of the rating of your opponent compared to your rating a 2220 (me) facing players from 2195 - 2245 (+/- 25) would give a win/draw/loss of +8/0/-8. If the opponent is higher than 2245, it will give me more points for winning/drawing and less points for losing.

ELO Hell is a situation in video games where more skilled players—and their rankings—are dragged down or unable to advance because of poor teammates. Chess is one versus one. ELO Hell doesn't exist in chess, it's just whoever plays better in that match wins. 

As for your idea of calculating matchmaking, it would not be enjoyable at least in my opinion getting crushed by players way stronger than I am and beating players that are significantly weaker. I prefer the glicko rating matching me against those with similar rating.

In my case my new rating and my ECF grade were 4 points apart. 1626 and 1622 my Fide grade is 1551 so quite accurate. Well done.

https://www.365chess.com/players/Magnus_Carlsen

Suppose that chess.com rating and Elo were the same, then I would need (2881-900)/8=247.625 consecutive won games to reach his 2881 rating. And if the (w+0.5d)/(w+d+l) was used, the answer is uncertain because he obviously played only strong players in these 2750 games, since he has 42.4% wins, 42.58% draws, 15.02% losses, and the (w+0.5d)/(w+d+l) that he would have if he had faced opponents from all ranges of ratings, is unknown. But suppose that he would have a rating of (0.95*2881+0.04*0.5*2881)/2881=0.97, i.e. 95% wins, 4% draws, 1% losses.  Myself so far I have 131 wins, 24 draws, 139 losses. I would need (131+x+0.5*24)/(131+24+139+x)=0.97=>x=4739 consecutive won games to reach his 0.97 rating! The surely correct rating is more hell than Elo etc!

Actually, to locate probabilities for win,draw,loss in the next game, derived from the correct rating, you need to modify the rating giving greater weight to the results of the most recent games, because by the passage of time players improve or become worse.

The math does account for everything you are concerned about. You don't need to play random opponent rating levels for your rating to be accurate. All of this is included in the math. People really don't understand how these things work it seems.

I read some of your comments and I have absolute certainty that you have no clue how these things work.

The Glicko-2 system has a ratings deviation based on activity, that's why it's an improvement on the Elo system in most cases.  You get to whatever rating you deserve rather quickly if you play for the first time or if you take a big break, the RD adjusts and you might lose or gain 20 points instead of 8.

It's completely logical that it's -8 or +8 against an opponent of equal skill... because in the long run if a 1200 player plays another 1200 player they should still remain at the same ratings... and if a 1200 player plays a 1400 for 1000 games, they will remain at the same ratings. The system accounts for the fact that the 1200 wins less, so he gets more rating for a win.


If someone isn't at a rating that they deserve, they will either win, or lose more than they need to and thus gravitate towards whatever rank they deserve. There is nothing "incorrect" about it and it has stood the test of time.

A rating gain of 8 happens when you are playing with an accurate RD against an opponent of a similar rating. Not when playing against someone much higher rated. Your calculations make no sense for several reasons.

You assume his rating will be static - which it won't. You assume you only gain 8, which you won't. The list goes on. 

Example:

If someone is 200 rating points higher than you and it means you will win 3/4 games. If you played in infinite amount of games you ratings should remain the same, so the ratings for gain/loss should account for this. 1200 vs 1000:

The 1200 player gets around 5 rating per win, but he loses 15 per defeat. In the long-run he stays at his rating if he deserves it, but if he doesn't perform as well as a 1200 player should, that changes.

You don't understand the math of the Glicko system but are trying to claim your method is more mathematically sound? That's not how math works ....

20 soccer teams have played 19 games each, confronting each other once in the championship. What is the most accurate rating? (wins+0.5draws)/(wins+draws+losses) as this is also equivalent to (wins-losses)/(wins+draws+losses). This is easy to conclude. Now, what about the totality of all e.g. >10000 teams that the have not confronted each other? That is why Elo invented a rating system that gives weight to the points gained on each win according to how strong the opponent is. And I am simply saying that it is unknown how correct Elo etc are, and you do not need to grasp the math to conclude some things. For example, a team at premier league has (w+0.5d)/(w+d+l)=0.75, and a team at league 2 has also 0.75. How can one calculate how much stronger the premier league team is than the league 2 team? It is impossible to answer without games between premier league teams against league 2 teams! IF some games between premier league and league 2 teams are played, then an answer can be considered by a unknown modification of the (w+0.5d)/(w+d+l) that gives more points to the teams that they faced teams with high (w+0.5d)/(w+d+l) and less points to the teams that they faced teams with low (w+0.5d)/(w+d+l). Myself have found such a modification but it is impossiple to describe it here. Note that if the 20+20 teams of these two leagues or the >10000 teams had faced each other once, the modification should be equal to the no modification. And for example,  if I had played against opponents of random selection from all ranges of ratings, my rating (131+0.5*24)/(131+24+139) would surely be correct. But since I faced opponents only close to my past current ratings,  I doubt whether this or my Glicko rating is correct. It's as simple as that. But I also prooved to you that with the surely correct system the consecutive wins to reach the top player should be more than Glicko suggests, but this ignores the fact that Glicko perhaps has given greater weight to more recent results. But again, there is also a modification of (w+0.5d)/(w+d+l) that gives greater weight to more recent results, is Glicko as correct as that?

Chess is not like soccer. In chess everyone plays everyone indirectly in the sense that you can almost always find a chain of games linking any 2 players. For example I am just 2 players away from Fischer: I played a top guy in our club, he once played GM Florin Gheorghiu who beat Fischer at the Havana Olympiad in 1966. If you've played enough games there is almost surely such a chain from you to Carlsen.

I don't even see how your formula can be applied in practice. Let's say you have a website with 10000 players. What do you do? Keep them unrated until they finish a round robin tourney with everyone playing 9999 games?

What do you mean by "correct" when you ask how correct Elo is?

I have already answered your 2 latter paragraphs.

In previous posts you only define correctness by comparing ELO/Glicko to your formula (Wins+0.5Ddraws)/(Wins+Draws+Losses). But we can't perform this comparison for the whole playing pull in reality because everyone playing everyone is physically impossible.

If you check results of multiple round robin tournaments you'll see that on average final rankings (which are equivalent to your formula) correspond to ELO. Doesn't it mean that ELO is mostly correct?

I have answered your first paragraph. I do not understand your second paragraph. I guess you mean that somewhere they have used my formula? But my formula is useless because strong players have faced only strong players and weak players have faced only weak players. I have found a modification that gives more points to the players or teams that they have faced strong players, but it is again useless, again I told you why, because if no games are played between premier league and league 2 teams, there is no way to conclude if a team having (w+0.5d)/(w+d+l)=0.75 in premier league is stronger than a team having 0.75 in league 2. The same problem obviously exists in any rating system, the only solution is that oppponents should be chosen randomly from all ranges of ratings. I wrote a little mistake, in the beginning strong players have faced weak players too, otherwise they could not have the high rating they have. But later they played only strong players, so this problem pops up.

Your claim that "problem obviously exists in any rating system" is just a hypothesis. You didn't show any numbers to prove it.

Your formula is actually used in any round robin tourney to find the final rankings. The number of points is w+0.5d. As it's same number of games for every player the denominator (w+d+l) doesn't change anythings. The fact that final rankings in tourneys follow ratings in average is a hint that Elo is mostly correct.

"strong players have faced only strong players and weak players have faced only weak players" - this is simply wrong. Strong players play not only elite tourneys but also opens, olympiads etc. where they often play with lower rated players.

With some patience you can find open challenges with ratings as far as 500 points away from yours here at chess.com. Just try it and see the results.

All that this guys formula is is win %. Which would be completely worthless.