Eliot Hearst and John Knott blog about blindfold chess
Wednesday, June 02, 2010

Intriguing, First-Ever Comparison: Grandmaster Rankings in Blindfold, Rapid, and Regular (FIDE) Play

Grandmaster tournaments and matches are much more varied today than they were throughout most of the 20th century. The “old-fashioned” events had slow time limits and players rarely had to play more than one game a day. More recent tourneys are often played at a much faster overall pace, frequently have sudden-death blitz playoffs after a relatively slow start, and may involve computers or humans-plus-computer as entries. One of the most interesting new varieties has consistently attracted the top grandmasters in the world to its venue – the annual Amber tournaments in Monaco or Nice during March or April. There the contestants play two games a day with a single opponent, one at a rapid speed (25 minutes for the entire game, with a bonus of 10 sec for each move made) with a standard chessboard and pieces to move in front of them, and the other at basically the same speed with both players “blindfolded”, in the sense that they enter their moves on a computer keyboard but can see only a blank chessboard and their opponent’s last move on the monitor facing them.

The Amber tourneys allow an eventual comparison of each player’s world ranking at blindfold chess with his or her ranking in rapid chess or in chess at the traditional slow speed (“classical”, FIDE-rated games). Would the FIDE rankings of grandmasters correlate best with their blindfold play or with their rapid play, and would players’ rankings in blindfold and rapid chess differ significantly? Supposedly obvious predictions about these correlations might prove false if data were available to test them.

Elmer Sangalang of the Philippines volunteered to calculate ratings based on the 2,376 games played in the rapid and blindfold modes over all the 18 Amber tourneys that started in 1993, including the most recent event in March of 2010. Sangalang was the editor of the 2nd edition of Arpad Elo’s “The Rating of Chess Players, Past and Present”, published in 1986, which extended and corrected material in the first edition. Now retired, Sangalang worked mainly as an engineer, actuary, and applied mathematician. He has been a consultant for FIDE on the ELO rating system since 1984.

It was not an easy job to collect complete scoretables for every Amber tourney but ultimately Sangalang was successful and he could include all games from the blindfold and rapid halves of those events. On the other hand, FIDE ratings appear regularly every 2 months and he waited for the publication of the May 1, 2010 ratings and rankings to have the most recent results available for his analysis.

His method for calculating the Amber rapid and blindfold ratings followed the standard ELO procedure (Method of Successive Approximations). The calculations began by assigning every player an initial rating of 2600, to keep the numerical values completely independent of players’ different FIDE ratings. Starting with the players’ actual FIDE ratings seemed less reasonable and would bias the results in favor of the more highly-ranked individuals. So all the numerical ratings for the three groups presented below (Blindfold, Rapid, and FIDE) are independent of each other and cannot be compared in terms of their numerical values, that is, one cannot conclude that, say, Anand’s FIDE rating of 2789 means that he is better at slow chess than rapid chess (rating of 2688) or blindfold chess (rating of 2667). However, the rankings of the players (from 1 to 29) have no such limitations or restrictions and a comparison of these in the three groups is entirely justified. To increase the statistical reliability of the results, only players who participated in at least two Amber tourneys were included below, a total of 29 competitors.

Here are the results for the three types of play. We reiterate that each of the three sets of data are independent of each other, and the numerical values of the ratings cannot be legitimately compared. Before looking at the results, readers might like to guess, for example, whether FIDE rankings would correlate best with rankings in blindfold play or sighted rapid play.

RankingNameNumber of
Amber Tourneys
1Morozevich, Alexander82739
2Kramnik, Vladimir 162704
3Grischuk, Alexander22703
4Anand, Viswanathan162667
5Topalov, Veselin122644
6Shirov, Alexei112633
7Leko, Peter92628
8Carlsen, Magnus42628
9Aronian, Levon52620
10Ivanchuk, Vassily182615
11Svidler, Peter52614
12Radjabov, Teimor22594
13Kamsky, Gata42586
14Karpov, Anatoly92586
15Almasi, Zoltan32581
16Gelfand, Boris 112575
17Karjakin, Sergey32573
18Lautier, Joel62569
19Bareev, Evgeny42536
20Vallejo Pons, Francisco42531
21Nikolic, Predrag62516
22Polgar, Judit42515
23Polgar, Susan22513
24Piket, Jeroen102510
25Van Wely, Loek122503
26Ljubojevic, Ljubomir112486
27Seirawan, Yasser 22481
28Nunn, John22431
29Korchnoi, Viktor22350

RankingNameNumber of
Amber Tourneys
1Aronian, Levon52703
2Anand, Viswanathan162688
3Bareev, Evgeny42683
4Carlsen, Magnus42667
5Ivanchuk, Vassily182655
6Kramnik, Vladimir162650
7Leko, Peter92648
8Kamsky, Gata42644
9Topalov, Veselin122642
10Shirov, Alexei112638
11Karjakin, Sergey32628
12Svidler, Peter52617
13Morozevich, Alexander82617
14Gelfand, Boris112613
15Karpov, Anatoly92608
16Polgar, Judit42591
17Radjabov, Teimor22553
18Grischuk, Alexander22546
19Piket, Jeroen102545
20Van Wely, Loek122534
21Almasi, Zoltan 32527
22Vallejo Pons, Francisco42515
23Korchnoi, Viktor22508
24Lautier, Joel 62498
25Ljubojevic, Ljubomir112494
26Nikolic, Predrag62478
27Seirawan, Yasser22474
28Polgar, Susan22454
29Nunn, John22432

1Carlsen, Magnus2813
2Topalov, Veselin2812
3Kramnik, Vladimir2790
4Anand, Viswanathan2789
5Aronian, Levon2783
6Grischuk, Alexander2760
7Shirov, Alexei2742
8Gelfand, Boris2741
9Ivanchuk, Vassily2741
10 Radjabov. Teimor2740
11 Karjakin, Sergey2739
12 Leko, Peter2735
13Svidler, Peter2735
14 Almasi, Zoltan2725
15Morozevich, Alexander2715
16Vallejo Pons, Francisco2703
17 Kamsky, Gata2702
18 Polgar, Judit2682
19Bareev, Evgeny2663
20 Lautier, Joel2658
21 Van Wely, Loek2653
22Seirawan, Yasser2644
23Piket, Jeroen2624
24 Karpov, Anatoly2619
25 Nikolic, Predrag2606
26 Nunn, John2602
27 Polgar, Susan2577
28 Ljubojevic, Ljubomir2572
29 Korchnoi, Viktor2564

After all the above rankings had been tabulated, statistically-determined correlations were calculated for each of the three possible pairs of comparisons: Blindfold vs. Rapid, Blindfold vs. FIDE, and Rapid vs. FIDE. Somewhat surprisingly, the FIDE rankings correlated most strongly with the Blindfold rather than with the Rapid rankings, even though both the FIDE and Rapid results involved games played with sight of a chessboard and the Blindfold games did not. All the different correlations were highly statistically reliable, but the strongest one was between FIDE and Blindfold; the next highest was between FIDE and Rapid, and the weakest was between Blindfold and Rapid. For those readers who are familiar with correlational techniques in statistics , the FIDE vs. Blindfold correlation for player rankings was +.84, for FIDE vs. Rapid +.76, and for Blindfold vs. Rapid +.72.

It is intriguing to speculate as to why a player’s world ranking (FIDE) in regular, “classical” chess would correlate best with his or her blindfold ranking, rather than with his or her regular rapid play. We offer one possibility and we welcome other suggestions from readers: Players may well be more cautious or careful in blindfold play than in rapid play with sight of the chessboard and thus try riskier lines of play in the latter, leading to more variable outcomes. (Recall the advice of world-class blindfold players like Alekhine who recommended that one “keep it simple” when playing without sight of the board). The fact that in the Amber tourneys the correlation between the Blindfold and Rapid conditions was relatively low (+.72) would be consistent with essentially the same kind of argument. At any rate, and speaking more loosely, you can predict a grandmaster’s FIDE ranking better from his Blindfold ranking than from his Rapid ranking.

We thank Mr. Sangalang for his careful and extensive work making the above calculations. Readers with questions or critical comments should send them to him or us via the “Comments” boxes below this blog. All of them will be published and answered.

Permalink  |  Posted by Eliot Hearst at 06:25 PM


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