Groot 1988

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   7  0.714  0.0613  0.1021  0.4335  0.2628  0.33
Anderszewski 2003   66  0.5171  0.0062  0.0453  0.0455  0.0472  0.04
Ashkenazy 1981   59  0.5655  0.0055  0.0467  0.0453  0.0582  0.04
Bacha 2000   35  0.6156  0.0046  0.0460  0.0426  0.2644  0.10
Badura 1965   69  0.4943  0.0066  0.0469  0.0464  0.0480  0.04
Barbosa 1983   38  0.6022  0.0030  0.1028  0.385  0.6012  0.48
Biret 1990   30  0.6469  0.0039  0.0539  0.1863  0.0550  0.09
Blet 2003   41  0.6063  0.0050  0.0549  0.0558  0.0473  0.04
Block 1995   19  0.679  0.026  0.1020  0.443  0.4917  0.46
Blumental 1952   79  0.4046  0.0077  0.0374  0.0374  0.0387  0.03
Boshniakovich 1969   34  0.6158  0.0038  0.0636  0.2241  0.1435  0.18
Brailowsky 1960   13  0.7031  0.0019  0.0717  0.482  0.616  0.54
Bunin 1987   48  0.5867  0.0060  0.0459  0.0426  0.3342  0.11
Bunin 1987b   51  0.5785  0.0061  0.0646  0.0629  0.3338  0.14
Chiu 1999   53  0.5759  0.0032  0.1031  0.3119  0.3826  0.34
Cohen 1997   83  0.3587  0.0085  0.0457  0.0444  0.0764  0.05
Cortot 1951   52  0.5775  0.0063  0.0462  0.0440  0.1655  0.08
Csalog 1996   65  0.5128  0.0040  0.0541  0.1033  0.1939  0.14
Czerny 1949   58  0.5630  0.0054  0.0461  0.0454  0.0578  0.04
Czerny 1990   23  0.6629  0.0033  0.0832  0.3041  0.1036  0.17
Duchoud 2007   54  0.5750  0.0058  0.0468  0.0441  0.1553  0.08
Ezaki 2006   12  0.7126  0.0021  0.0914  0.4929  0.2923  0.38
Falvay 1989   3  0.7415  0.019  0.127  0.546  0.615  0.57
Farrell 1958   11  0.7123  0.0016  0.0815  0.494  0.5211  0.50
Ferenczy 1958   60  0.5532  0.0064  0.0452  0.0455  0.0576  0.04
Fliere 1977   8  0.7164  0.0017  0.0711  0.5237  0.1930  0.31
Fou 1978   17  0.6816  0.0118  0.085  0.5515  0.4014  0.47
Francois 1956   4  0.732  0.104  0.132  0.573  0.594  0.58
Friedman 1923   87  0.2668  0.0087  0.0465  0.0456  0.0665  0.05
Friedman 1923b   86  0.2789  0.0086  0.0456  0.0460  0.0583  0.04
Friedman 1930   81  0.3778  0.0080  0.0386  0.0363  0.0575  0.04
Garcia 2007   75  0.4651  0.0074  0.0385  0.0340  0.1462  0.06
Garcia 2007b   85  0.3237  0.0081  0.0382  0.0327  0.1859  0.07
Gierzod 1998   43  0.5925  0.0056  0.0455  0.0469  0.0479  0.04
Gornostaeva 1994   28  0.6539  0.0025  0.0929  0.3714  0.4520  0.41
Groot 1988   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Harasiewicz 1955   44  0.5866  0.0027  0.1026  0.3834  0.2031  0.28
Hatto 1993   82  0.3570  0.0083  0.0375  0.0382  0.0389  0.03
Hatto 1997   77  0.4160  0.0079  0.0381  0.0380  0.0386  0.03
Horowitz 1949   22  0.6640  0.0022  0.0825  0.4016  0.4618  0.43
Indjic 1988   80  0.3883  0.0082  0.0383  0.0359  0.0571  0.04
Kapell 1951   36  0.6176  0.0042  0.0543  0.1059  0.0461  0.06
Kissin 1993   25  0.6580  0.0031  0.0930  0.3555  0.0540  0.13
Kushner 1989   20  0.6710  0.0228  0.1023  0.4130  0.2627  0.33
Luisada 1991   49  0.5774  0.0057  0.0451  0.0449  0.0566  0.04
Lushtak 2004   26  0.6554  0.0024  0.099  0.5319  0.3119  0.41
Malcuzynski 1961   29  0.6481  0.0037  0.0638  0.2027  0.2333  0.21
Magaloff 1978   9  0.713  0.065  0.1512  0.513  0.5010  0.50
Magin 1975   64  0.5253  0.0044  0.0444  0.0850  0.0560  0.06
Michalowski 1933   84  0.3284  0.0084  0.0377  0.0377  0.0385  0.03
Milkina 1970   6  0.7141  0.0020  0.0824  0.4119  0.3821  0.39
Mohovich 1999   1  0.801  0.451  0.451  0.681  0.731  0.70
Moravec 1969   62  0.5444  0.0076  0.0376  0.0375  0.0384  0.03
Morozova 2008   57  0.5634  0.0036  0.0637  0.2041  0.1137  0.15
Neighaus 1950   5  0.7262  0.0012  0.1110  0.5225  0.3022  0.39
Niedzielski 1931   63  0.5336  0.0067  0.0464  0.0453  0.0468  0.04
Ohlsson 1999   50  0.5724  0.0059  0.0470  0.0452  0.0569  0.04
Osinska 1989   14  0.6938  0.0023  0.0922  0.4329  0.2725  0.34
Pachmann 1927   45  0.5877  0.0043  0.0542  0.1012  0.3834  0.19
Paderewski 1930   39  0.6045  0.0052  0.0471  0.0445  0.0663  0.05
Perlemuter 1992   10  0.7121  0.008  0.133  0.566  0.517  0.53
Pierdomenico 2008   33  0.636  0.0410  0.1119  0.456  0.4913  0.47
Poblocka 1999   56  0.5627  0.0049  0.0550  0.0582  0.0367  0.04
Rabcewiczowa 1932   55  0.5648  0.0053  0.0463  0.0441  0.1156  0.07
Rachmaninoff 1923   32  0.6314  0.0126  0.0927  0.3820  0.3424  0.36
Rangell 2001   47  0.5818  0.0129  0.1034  0.2616  0.3929  0.32
Richter 1976   61  0.5533  0.0051  0.0547  0.0544  0.1057  0.07
Rosen 1989   31  0.6313  0.0135  0.1035  0.2633  0.2332  0.24
Rosenthal 1930   70  0.4917  0.0168  0.0379  0.0335  0.2054  0.08
Rosenthal 1931   72  0.4890  0.0065  0.0458  0.0424  0.3741  0.12
Rosenthal 1931b   74  0.4672  0.0069  0.0466  0.0422  0.3243  0.11
Rosenthal 1931c   71  0.4873  0.0075  0.0372  0.0337  0.1858  0.07
Rosenthal 1931d   68  0.5079  0.0071  0.0380  0.0325  0.2651  0.09
Rossi 2007   78  0.4047  0.0073  0.0384  0.0324  0.2848  0.09
Rubinstein 1939   76  0.4335  0.0078  0.0378  0.0335  0.1952  0.08
Rubinstein 1952   24  0.668  0.0214  0.0818  0.458  0.589  0.51
Rubinstein 1966   16  0.6912  0.0111  0.114  0.563  0.722  0.63
Schilhawsky 1960   46  0.5849  0.0047  0.0548  0.0561  0.0474  0.04
Shebanova 2002   27  0.6565  0.0034  0.0933  0.2764  0.0446  0.10
Smith 1975   21  0.6619  0.0115  0.0713  0.4914  0.4316  0.46
Sokolov 2002   42  0.5942  0.0045  0.0454  0.0439  0.2047  0.09
Sztompka 1959   40  0.605  0.0448  0.0745  0.0744  0.1249  0.09
Tomsic 1995   2  0.7620  0.002  0.238  0.544  0.683  0.61
Uninsky 1932   73  0.4757  0.0072  0.0387  0.0351  0.0677  0.04
Uninsky 1971   67  0.5052  0.0070  0.0373  0.0350  0.0670  0.04
Wasowski 1980   37  0.6061  0.0041  0.0540  0.1142  0.0945  0.10
Zak 1937   18  0.687  0.047  0.1216  0.4812  0.4615  0.47
Zak 1951   15  0.6911  0.013  0.156  0.559  0.488  0.51
Random 1   90  -0.1688  0.0090  0.0190  0.0144  0.1288  0.03
Random 2   89  -0.1282  0.0088  0.0189  0.0184  0.0290  0.01
Random 3   88  -0.0386  0.0089  0.0188  0.0134  0.1681  0.04

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).