Groot 1988

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Ashkenazy 1981   47  0.6019  0.0144  0.0742  0.0754  0.0658  0.06
Ax 1995   7  0.7113  0.014  0.142  0.5830  0.1912  0.33
Bacha 1998   59  0.5566  0.0054  0.0557  0.0543  0.0661  0.05
Barbosa 1983   57  0.5511  0.0130  0.0632  0.1249  0.0646  0.08
BenOr 1989   39  0.6339  0.0013  0.0920  0.2822  0.4211  0.34
Biret 1990   5  0.724  0.058  0.198  0.507  0.693  0.59
Brailowsky 1960   6  0.723  0.083  0.153  0.553  0.642  0.59
Chiu 1999   53  0.5858  0.0052  0.0652  0.0632  0.2139  0.11
Clidat 1994   37  0.6336  0.0043  0.0743  0.0754  0.0655  0.06
Cohen 1997   61  0.4463  0.0063  0.0651  0.0654  0.0562  0.05
Cortot 1951   63  0.4224  0.0062  0.0555  0.059  0.4929  0.16
Csalog 1996   9  0.7142  0.0011  0.1310  0.465  0.634  0.54
Czerny 1989   21  0.6826  0.0032  0.0731  0.1330  0.2027  0.16
Ezaki 2006   25  0.6733  0.0042  0.0645  0.0647  0.0648  0.06
Falvay 1989   1  0.771  0.461  0.451  0.7711  0.531  0.64
Fiorentino 1962   8  0.712  0.102  0.255  0.5516  0.535  0.54
Fliere 1977   45  0.6147  0.0036  0.0740  0.0749  0.0649  0.06
Fou 1978   29  0.6617  0.0116  0.0817  0.3329  0.1920  0.25
Francois 1956   38  0.6331  0.0028  0.0729  0.1517  0.3722  0.24
Goldenweiser 1946   41  0.6344  0.0045  0.0835  0.081  0.7321  0.24
Gornostaeva 1994   62  0.4359  0.0059  0.0648  0.0646  0.0563  0.05
Groot 1988   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Hatto 1993   15  0.6952  0.0024  0.0824  0.2445  0.0637  0.12
Hatto 1997   13  0.6951  0.0026  0.0825  0.2251  0.0640  0.11
Horszowski 1983   54  0.5655  0.0060  0.0461  0.0461  0.0465  0.04
Indjic 2001   11  0.6957  0.0023  0.0722  0.2538  0.0931  0.15
Katin 1996   10  0.6914  0.0117  0.1014  0.3628  0.1918  0.26
Kiepura 1999   48  0.605  0.0515  0.0726  0.2019  0.3815  0.28
Korecka 1992   52  0.5932  0.0053  0.0460  0.0411  0.5032  0.14
Kushner 1990   33  0.649  0.0114  0.1012  0.3714  0.547  0.45
Lilamand 2001   55  0.5535  0.0058  0.0463  0.0424  0.2342  0.10
Luisada 1990   36  0.6415  0.0146  0.0737  0.0728  0.2733  0.14
Luisada 2008   46  0.6140  0.0051  0.0556  0.0530  0.1843  0.09
Lushtak 2004   31  0.6527  0.0020  0.0721  0.2848  0.0734  0.14
Malcuzynski 1951   34  0.6448  0.0025  0.0823  0.2548  0.0638  0.12
Malcuzynski 1961   51  0.5937  0.0027  0.0727  0.1660  0.0444  0.08
Magaloff 1977   50  0.5953  0.0050  0.0553  0.0520  0.2736  0.12
Magin 1975   43  0.6221  0.0148  0.0650  0.0657  0.0652  0.06
Meguri 1997   27  0.6625  0.0041  0.1133  0.115  0.4023  0.21
Milkina 1970   22  0.6820  0.0121  0.0815  0.3531  0.1917  0.26
Mohovich 1999   30  0.6543  0.0035  0.0741  0.0751  0.0657  0.06
Nezu 2005   35  0.6460  0.0018  0.1019  0.2941  0.0830  0.15
Ohlsson 1999   18  0.6945  0.0039  0.0738  0.0735  0.0945  0.08
Olejniczak 1990   14  0.6918  0.0122  0.0918  0.3027  0.2416  0.27
Osinska 1989   16  0.6941  0.009  0.146  0.5228  0.2013  0.32
Perlemuter 1992   56  0.5554  0.0061  0.0554  0.0537  0.0660  0.05
Poblocka 1999   26  0.6749  0.0040  0.0834  0.0856  0.0550  0.06
Rangell 2001   49  0.6050  0.0055  0.0462  0.0443  0.0764  0.05
Richter 1960   58  0.5522  0.0157  0.0739  0.0744  0.0653  0.06
Richter 1961   60  0.5456  0.0056  0.0559  0.0538  0.0751  0.06
Rosen 1989   20  0.687  0.0219  0.0813  0.378  0.519  0.43
Rubinstein 1939   19  0.6810  0.0112  0.0916  0.3432  0.1919  0.25
Rubinstein 1952   40  0.6328  0.0038  0.0646  0.0646  0.0659  0.06
Rubinstein 1966   32  0.6512  0.0137  0.0647  0.0639  0.0847  0.07
Rudanovskaya 2007   17  0.6934  0.0031  0.0730  0.144  0.6014  0.29
Shebanova 2002   42  0.6262  0.0049  0.0558  0.0540  0.0754  0.06
Smith 1975   28  0.6646  0.0034  0.0649  0.0619  0.4126  0.16
Sztompka 1959   24  0.6738  0.0033  0.0644  0.069  0.5324  0.18
Tanyel 1992   12  0.696  0.045  0.157  0.5129  0.2910  0.38
Tsujii 2005   3  0.7229  0.0010  0.1211  0.4257  0.0628  0.16
Uninsky 1959   2  0.738  0.027  0.204  0.5515  0.396  0.46
Vardi 1988   4  0.7223  0.006  0.149  0.4917  0.408  0.44
Wasowski 1980   44  0.6230  0.0047  0.0736  0.0720  0.3825  0.16
Zimerman 1975   23  0.6716  0.0129  0.0628  0.1537  0.0841  0.11
Random 1   65  -0.0264  0.0065  0.0265  0.0220  0.1856  0.06
Random 2   66  -0.1061  0.0066  0.0166  0.0166  0.0166  0.01
Random 3   64  0.0365  0.0064  0.0364  0.032  0.5435  0.13

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).