Hatto 1997

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   23  0.4346  0.0032  0.0725  0.3411  0.5724  0.44
Anderszewski 2003   47  0.3847  0.0040  0.0539  0.1431  0.3837  0.23
Ashkenazy 1981   32  0.4042  0.0048  0.0480  0.0438  0.2265  0.09
Bacha 2000   35  0.4032  0.0054  0.0647  0.0617  0.4941  0.17
Badura 1965   70  0.3249  0.0070  0.0469  0.0437  0.1667  0.08
Barbosa 1983   13  0.4768  0.0016  0.1311  0.5712  0.5812  0.57
Biret 1990   8  0.5020  0.0013  0.128  0.606  0.698  0.64
Blet 2003   38  0.3952  0.0027  0.0829  0.3015  0.4929  0.38
Block 1995   81  0.2773  0.0072  0.0481  0.0467  0.0484  0.04
Blumental 1952   10  0.4823  0.0012  0.129  0.596  0.737  0.66
Boshniakovich 1969   72  0.3027  0.0050  0.0552  0.0558  0.0580  0.05
Brailowsky 1960   74  0.2984  0.0085  0.0551  0.0568  0.0574  0.05
Bunin 1987   55  0.3678  0.0024  0.0736  0.2217  0.5031  0.33
Bunin 1987b   57  0.3579  0.0025  0.0737  0.2115  0.4832  0.32
Chiu 1999   29  0.4124  0.0043  0.0542  0.1137  0.1746  0.14
Cohen 1997   64  0.3474  0.0058  0.0556  0.0516  0.5842  0.17
Cortot 1951   73  0.2911  0.0077  0.0464  0.0430  0.2763  0.10
Csalog 1996   61  0.3531  0.0069  0.0471  0.0448  0.0779  0.05
Czerny 1949   24  0.439  0.0023  0.0824  0.3522  0.6021  0.46
Czerny 1990   18  0.4635  0.0019  0.1315  0.5322  0.6213  0.57
Duchoud 2007   63  0.3450  0.0063  0.0559  0.0534  0.2261  0.10
Ezaki 2006   22  0.4312  0.0037  0.0735  0.2340  0.3335  0.28
Falvay 1989   7  0.516  0.0014  0.1118  0.499  0.4917  0.49
Farrell 1958   67  0.3475  0.0061  0.0648  0.0632  0.2351  0.12
Ferenczy 1958   56  0.3576  0.0064  0.0562  0.0520  0.6540  0.18
Fliere 1977   39  0.3961  0.0052  0.0467  0.0485  0.0388  0.03
Fou 1978   36  0.4063  0.0046  0.0463  0.0450  0.0676  0.05
Francois 1956   65  0.3451  0.0047  0.0473  0.0416  0.5944  0.15
Friedman 1923   79  0.2725  0.0080  0.0386  0.0362  0.0587  0.04
Friedman 1923b   83  0.2680  0.0082  0.0383  0.0353  0.0685  0.04
Friedman 1930   52  0.3638  0.0053  0.0557  0.0534  0.2456  0.11
Garcia 2007   80  0.2718  0.0074  0.0550  0.0542  0.1069  0.07
Garcia 2007b   40  0.397  0.0017  0.1521  0.4615  0.6215  0.53
Gierzod 1998   41  0.3969  0.0033  0.0831  0.2633  0.2836  0.27
Gornostaeva 1994   45  0.3828  0.0062  0.0466  0.0442  0.0972  0.06
Groot 1988   14  0.4753  0.009  0.1210  0.579  0.5614  0.56
Harasiewicz 1955   9  0.4839  0.0015  0.1217  0.5227  0.4122  0.46
Hatto 1993   2  0.882  0.122  0.952  0.982  0.982  0.98
Hatto 1997   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Horowitz 1949   71  0.3154  0.0071  0.0477  0.0428  0.4249  0.13
Indjic 1988   1  0.911  0.861  0.851  0.992  0.991  0.99
Kapell 1951   17  0.464  0.0021  0.1514  0.5315  0.4219  0.47
Kissin 1993   51  0.3681  0.0051  0.0555  0.0539  0.3450  0.13
Kushner 1989   27  0.4264  0.0042  0.0538  0.1449  0.0758  0.10
Luisada 1991   11  0.4813  0.0011  0.1213  0.5510  0.6310  0.59
Lushtak 2004   49  0.3758  0.0055  0.0646  0.0648  0.0671  0.06
Malcuzynski 1961   43  0.388  0.0030  0.0726  0.3435  0.2934  0.31
Magaloff 1978   58  0.3555  0.0041  0.0641  0.1449  0.0566  0.08
Magin 1975   30  0.4140  0.0031  0.0728  0.3119  0.5027  0.39
Michalowski 1933   86  0.2156  0.0086  0.0558  0.0552  0.0678  0.05
Milkina 1970   5  0.513  0.006  0.246  0.657  0.725  0.68
Mohovich 1999   33  0.4077  0.0010  0.1320  0.4722  0.4820  0.47
Moravec 1969   28  0.4259  0.0036  0.0932  0.2519  0.3833  0.31
Morozova 2008   53  0.3682  0.0056  0.0478  0.0456  0.0583  0.04
Neighaus 1950   54  0.3670  0.0057  0.0553  0.0538  0.2062  0.10
Niedzielski 1931   77  0.2857  0.0075  0.0476  0.0447  0.0675  0.05
Ohlsson 1999   37  0.3910  0.0045  0.0445  0.0840  0.1853  0.12
Osinska 1989   15  0.4716  0.0020  0.1019  0.4724  0.4718  0.47
Pachmann 1927   87  0.1685  0.0087  0.0385  0.0366  0.0582  0.04
Paderewski 1930   84  0.2587  0.0073  0.0475  0.0433  0.3552  0.12
Perlemuter 1992   85  0.2465  0.0081  0.0387  0.0347  0.0773  0.05
Pierdomenico 2008   59  0.3566  0.0059  0.0465  0.0419  0.4647  0.14
Poblocka 1999   50  0.3714  0.0039  0.0543  0.1042  0.2045  0.14
Rabcewiczowa 1932   34  0.4044  0.0034  0.0927  0.3118  0.5525  0.41
Rachmaninoff 1923   48  0.3748  0.0044  0.0544  0.0941  0.1948  0.13
Rangell 2001   82  0.2643  0.0083  0.0479  0.0461  0.0586  0.04
Richter 1976   69  0.3245  0.0076  0.0482  0.0458  0.0677  0.05
Rosen 1989   26  0.4233  0.0035  0.0834  0.2432  0.2138  0.22
Rosenthal 1930   42  0.3936  0.0060  0.0561  0.0527  0.5443  0.16
Rosenthal 1931   75  0.2883  0.0079  0.0384  0.0336  0.3659  0.10
Rosenthal 1931b   78  0.2871  0.0084  0.0560  0.0534  0.3155  0.12
Rosenthal 1931c   60  0.3521  0.0065  0.0474  0.0426  0.3357  0.11
Rosenthal 1931d   76  0.2867  0.0078  0.0470  0.0423  0.3854  0.12
Rossi 2007   88  0.1088  0.0089  0.0388  0.0382  0.0289  0.02
Rubinstein 1939   12  0.4729  0.008  0.1412  0.567  0.6011  0.58
Rubinstein 1952   19  0.4672  0.007  0.187  0.618  0.669  0.63
Rubinstein 1966   4  0.5241  0.004  0.265  0.6711  0.666  0.66
Schilhawsky 1960   62  0.345  0.0068  0.0472  0.0439  0.1468  0.07
Shebanova 2002   31  0.4130  0.0022  0.1122  0.4529  0.3826  0.41
Smith 1975   20  0.4462  0.0029  0.0733  0.2520  0.5030  0.35
Sokolov 2002   21  0.4419  0.0028  0.0730  0.2813  0.5128  0.38
Sztompka 1959   66  0.3422  0.0038  0.0740  0.1439  0.2639  0.19
Tomsic 1995   25  0.4226  0.0026  0.0823  0.379  0.5523  0.45
Uninsky 1932   68  0.3389  0.0049  0.0554  0.0537  0.1764  0.09
Uninsky 1971   6  0.5134  0.005  0.174  0.703  0.694  0.69
Wasowski 1980   16  0.4715  0.0018  0.1316  0.5215  0.5316  0.52
Zak 1937   44  0.3890  0.0067  0.0549  0.0550  0.0770  0.06
Zak 1951   46  0.3860  0.0066  0.0468  0.0457  0.0581  0.04
Average   3  0.6617  0.003  0.723  0.899  0.603  0.73
Random 1   90  -0.0591  0.0090  0.0190  0.0175  0.0291  0.01
Random 2   89  0.0837  0.0088  0.0289  0.028  0.4660  0.10
Random 3   91  -0.0886  0.0091  0.0191  0.0173  0.0390  0.02

Note: To load data table give above into Excel, copy and paste the data into a text editor (such as WordPad) first, then copy the text in the editor and past into Excel. You should remove the "target" line from the data before pasting into Excel so that plotting graphs of the data is done properly.

Column descriptions

  • Performance:
  • 0-Rank/0-Score: 0-Score is equivalent to Pearson correlation of the entire data sequence between the reference performance and a test performance. 0-Rank is the sorting order of the 0-scores (highest score has a rank of 1).
  • 1-Rank/1-Score: 1-Score is the area fraction covered by a particular performance in the scape plot (see image above). These values should not be taken literally, since they are sensitive to the Hatto Effect.
  • 2-Rank/2-Score: 2-Score values are equivalent to 1-Score values with all higher-ranking performances removed before the calculation of the area of coverage in the scape is calculated. Improvment over the 1-Rank scores, but still somewhat sensitive to the Hatto Effect.
  • 3-Rank/3-Score: Similar to 2-Rank calculations. The bottom 1/2 of the 2-rank performances are kept constant as a noise floor for the similarity measurement. Then one-by-one the top 1/2 of the 2-rank performances are superimposed with the noise-floor performances, and a 3-score is measured as the area covered in the scape. This measure is not sentisive to the Hatto Effect.
  • 3R-Rank/3R-Score: Reverse 3-rank/3-scores. 3-rankings and scores are not symmetric (A->B values are different from B->A values). So this column represents similarity measures in the opposite direction.
  • 4-Rank/4-Score: The geometric mean between 3-scores and 3R-scores. This column gives the best overall similarity ranking between the various performances (see color codes below).
  • NED: Noise Equivalient Distance (not yet implemented)

Color codes for 3-rank listings:

  • red = strongly similar performance to target
  • orange = moderately similar performance
  • yellow = weakly similar performance
  • green = marginally similar/dissimilar performance
  • white = dissimilar to target
  • blue = false positive (has high 3-rank score but low 3R-rank score)

3-rank/scores are not symmetric, so the 3R-rank/score columns give the 3-rank/scores going in the opposite direction. More matches in the 3-rank column than in the 3R-rank column indicates an individualistic performance, while more matches in the 3R-rank column indicates a mainstream performance.

If a 3-rank and a 3R-rank are both marked as similar to each other, then there is a possible direct relation between the performances. If one is similar to the other but not in the reverse direction, then the similarity is more likely to be by chance (performers randomly chose a similar interpretation).