Elo-Rangliste im Schachportal. In der Statistik finden sich alle Schachspieler sortiert nach ELO-Punktzahl und Anzahl der Gegner bzw. Spiele. ÖSB-Eloliste: fxhope.com Fide-Eloliste: fxhope.com ICCF-Eloliste: fxhope.com Wir bieten Vereinen oder Sportgruppen eine kostenlose Online-Verwaltung von Forderungs-Ranglisten (Pyramide / Tannenbaum) sowie ELO-Ranglisten für eine.
Weltrangliste der besten Schachspieler nach Elo-Punkten 2020Wir bieten Vereinen oder Sportgruppen eine kostenlose Online-Verwaltung von Forderungs-Ranglisten (Pyramide / Tannenbaum) sowie ELO-Ranglisten für eine. Aktuelle Elo-Ranglisten Deutschland. Standard-Liste Top Standard - Top - Dezember Magnus Carlsen.
Elo Rangliste Navigation menu VideoThe Elo Rating System for Chess and Beyond
Euro Elo Rangliste ohne Einzahlung erzielt Sportwetten 5 Euro Gutschein, sondern. - ... übrigens:Anand, Viswanathan. rows · Diese Liste der Schachspieler mit einer Elo-Zahl von oder mehr enthält alle . Ranking/ELO Info. Created On November 27, by FACEIT Support. Häufig werden deshalb die Ratingzahlen auch als "Elo-Zahlen" bezeichnet. Die Ratingzahlen der FIDE beginnen bei Zahlen von (Amateur) und reichen bis zu über Die FIDE veröffentlichte bis Juli viermal jährlich neue Weltranglisten, deren Zahlen dann für das nächste Quartal Gültigkeit hatten. Mit den Listen vom September
Chiron 2 bit. Rybka 3 Human bit. Crafty Marvin 3. Nemorino 2. Sting SF Cheng 4. Sting SF 19 bit. Sting SF 7. Monolith 2 bit. Rodent IV 0. Sting SF 9 bit.
Hakkapeliitta TCEC v2 bit. Sting SF 24 bit. Bagatur 2. Gull II b2 bit. Weiss 1. Deep Fritz 11 4CPU. Rodent IV bit.
Gull R bit. Gull II bit. Deep Fritz 12 4CPU. Scorpio 2. Hiarcs Cheng4 0. Deuterium Godel 7. Bobcat 7. Komodo 1.
EXchess 7. Spark 1. Naum 3. Bagatur 1. Fritz Zappa Mexico bit 4CPU. Toga II 4. Naum 3 bit 4CPU.
Naum 4 bit. Hakkapeliitta 3. Chess Zanzibar bit 4CPU. FabChess 1. Gaviota 1. Deep Sjeng c't Tucano 7. Deep Shredder 12 bit.
The Baron 3. Onno 1. Tucano 9. Spark 0. Ethereal 8. Shredder 12 bit. Amoeba 2. Thinker 5. Godel 6. Deep Junior Yokohama bit. Gull 1. Toga II 3.
Deep Junior 13 bit. Deep Shredder 11 bit 4CPU. Rodent II 0. DisasterArea 1. Francesca MAD 0. Gogobello 2. Asymptote 0. Deep Sjeng 3.
Wasp 1. Counter 3. Quazar 0. Fruit Reloaded 15th ann. Naum 2. Nemorino 1. Toga II 1. Gull 0. Rybka 1. Koivisto 3. Jan Nepomnjaschtschi.
Anatoli Karpow. Boris Gelfand. Pjotr Swidler. Pawel Eljanow. Ruslan Ponomarjow. Wang Hao. Michael Adams.
Wladislaw Artemjew. Dmitri Jakowenko. Jewgeni Tomaschewski. Jan-Krzysztof Duda. Wang Yue. Alexei Schirow. Sergej Movsesjan.
David Navara. Nikita Witjugow. Dmitri Andreikin. GM Vlastimil Hort. IM Thomas Reich. IM Nikolas Lubbe. GM Lev Gutman. IM Steve Berger.
IM Christof Sielecki. FM Jens Hirneise. GM Rainer Polzin. IM Tobias Jugelt. IM Mark Kvetny. GM Mathias Womacka.
IM Arnd Lauber. IM Gerlef Meins. IM Srdjan Panzalovic. IM Joerg Wegerle. IM Karl-Heinz Podzielny. GM Sebastian Siebrecht.
IM Ferenc Langheinrich. GM Eckhard Schmittdiel. IM Stefan Fruebing. FM Dr. Markus Hochgraefe. IM Bernd Schneider. FM Moritz Lauer. IM Atila Gajo Figura.
IM Benedict Krause. FM Marcel Harff. Oswald Gschnitzer. IM Sebastian Plischki. IM Georg Seul. FM Volker Kraft. IM Alexander Raykhman. IM Stefan Walter.
GM Lothar Vogt. GM Gerhard Schebler. Schnellschach-Liste Frauen Top Schnellschach Frauen - Top - Dezember 1. WFM Bergit Barthel.
Paula Wiesner. WFM Diana Skibbe. WFM Teodora Rogozenco. Jutta Ries. WFM Katrin Daemering. Tatiana Rubina. Julia Scheynin.
Inken Koehler. Melina Siegl. Anita Just. Liubov Orlova. Hannelore Neumeyer. WFM Dorota Weclawski. Elisa Zeller. Tena Frank. Anastasia Erofeev.
Katja Hartung. Elke Zimmer. Barbara Niedermaier. Theresa Peters. Lea Rieping. Rabea Schumann. Britta Leib. Gerda Strate.
Anne Lukas. Olena Kosovska. Dagmar Aden. Johanna Ehmann. Constanze Wulf. Nicole Nentwig. Anke Freter. Astrid Froehlich-Dill.
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Masters of RMS. Knights of the Empire. Double Cup. Master of the Circus. If a player has achieved the rating of Original Life Master, their rating floor is set at The achievement of this title is unique in that no other recognized USCF title will result in a new floor.
Pairwise comparisons form the basis of the Elo rating methodology. Performance is not measured absolutely; it is inferred from wins, losses, and draws against other players.
Players' ratings depend on the ratings of their opponents and the results scored against them. The difference in rating between two players determines an estimate for the expected score between them.
Both the average and the spread of ratings can be arbitrarily chosen. Elo suggested scaling ratings so that a difference of rating points in chess would mean that the stronger player has an expected score which basically is an expected average score of approximately 0.
A player's expected score is their probability of winning plus half their probability of drawing. Thus, an expected score of 0.
The probability of drawing, as opposed to having a decisive result, is not specified in the Elo system. Instead, a draw is considered half a win and half a loss.
In practice, since the true strength of each player is unknown, the expected scores are calculated using the player's current ratings as follows.
It then follows that for each rating points of advantage over the opponent, the expected score is magnified ten times in comparison to the opponent's expected score.
When a player's actual tournament scores exceed their expected scores, the Elo system takes this as evidence that player's rating is too low, and needs to be adjusted upward.
Similarly, when a player's actual tournament scores fall short of their expected scores, that player's rating is adjusted downward.
Elo's original suggestion, which is still widely used, was a simple linear adjustment proportional to the amount by which a player overperformed or underperformed their expected score.
The formula for updating that player's rating is. This update can be performed after each game or each tournament, or after any suitable rating period.
An example may help to clarify. Suppose Player A has a rating of and plays in a five-round tournament. He loses to a player rated , draws with a player rated , defeats a player rated , defeats a player rated , and loses to a player rated The expected score, calculated according to the formula above, was 0.
Note that while two wins, two losses, and one draw may seem like a par score, it is worse than expected for Player A because their opponents were lower rated on average.
Therefore, Player A is slightly penalized. New players are assigned provisional ratings, which are adjusted more drastically than established ratings.
The principles used in these rating systems can be used for rating other competitions—for instance, international football matches. See Go rating with Elo for more.
The first mathematical concern addressed by the USCF was the use of the normal distribution. They found that this did not accurately represent the actual results achieved, particularly by the lower rated players.
Instead they switched to a logistic distribution model, which the USCF found provided a better fit for the actual results achieved. The second major concern is the correct "K-factor" used.
If the K-factor coefficient is set too large, there will be too much sensitivity to just a few, recent events, in terms of a large number of points exchanged in each game.
And if the K-value is too low, the sensitivity will be minimal, and the system will not respond quickly enough to changes in a player's actual level of performance.
Elo's original K-factor estimation was made without the benefit of huge databases and statistical evidence. Sonas indicates that a K-factor of 24 for players rated above may be more accurate both as a predictive tool of future performance, and also more sensitive to performance.
Certain Internet chess sites seem to avoid a three-level K-factor staggering based on rating range. The USCF which makes use of a logistic distribution as opposed to a normal distribution formerly staggered the K-factor according to three main rating ranges of:.
Currently, the USCF uses a formula that calculates the K-factor based on factors including the number of games played and the player's rating.
The K-factor is also reduced for high rated players if the event has shorter time controls. FIDE uses the following ranges: .
FIDE used the following ranges before July . The gradation of the K-factor reduces ratings changes at the top end of the rating spectrum, reducing the possibility for rapid ratings inflation or deflation for those with a low K-factor.
This might in theory apply equally to an online chess site or over-the-board players, since it is more difficult for players to get much higher ratings when their K-factor is reduced.
In some cases the rating system can discourage game activity for players who wish to protect their rating. Beyond the chess world, concerns over players avoiding competitive play to protect their ratings caused Wizards of the Coast to abandon the Elo system for Magic: the Gathering tournaments in favour of a system of their own devising called "Planeswalker Points".
A more subtle issue is related to pairing. When players can choose their own opponents, they can choose opponents with minimal risk of losing, and maximum reward for winning.
In the category of choosing overrated opponents, new entrants to the rating system who have played fewer than 50 games are in theory a convenient target as they may be overrated in their provisional rating.
The ICC compensates for this issue by assigning a lower K-factor to the established player if they do win against a new rating entrant. The K-factor is actually a function of the number of rated games played by the new entrant.
Therefore, Elo ratings online still provide a useful mechanism for providing a rating based on the opponent's rating. Its overall credibility, however, needs to be seen in the context of at least the above two major issues described — engine abuse, and selective pairing of opponents.
The ICC has also recently introduced "auto-pairing" ratings which are based on random pairings, but with each win in a row ensuring a statistically much harder opponent who has also won x games in a row.