Groot 1988

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   39  0.4110  0.0116  0.1025  0.398  0.6025  0.48
Anderszewski 2003   82  0.1673  0.0082  0.0382  0.0361  0.0486  0.03
Ashkenazy 1981   2  0.6219  0.003  0.203  0.789  0.802  0.79
Bacha 2000   75  0.2188  0.0077  0.0377  0.0362  0.0578  0.04
Badura 1965   68  0.2645  0.0073  0.0473  0.0455  0.0482  0.04
Barbosa 1983   58  0.3421  0.0048  0.0567  0.0519  0.4950  0.16
Biret 1990   72  0.2489  0.0080  0.0380  0.0348  0.0877  0.05
Blet 2003   19  0.4843  0.0026  0.0821  0.457  0.6817  0.55
Block 1995   31  0.4374  0.0032  0.0722  0.4221  0.5027  0.46
Blumental 1952   61  0.3250  0.0059  0.0664  0.0632  0.3060  0.13
Boshniakovich 1969   44  0.4039  0.0053  0.0755  0.0739  0.2461  0.13
Brailowsky 1960   83  0.1684  0.0084  0.0385  0.0380  0.0383  0.03
Bunin 1987   46  0.4027  0.0017  0.0833  0.2529  0.4139  0.32
Bunin 1987b   45  0.4041  0.0022  0.0836  0.2427  0.4040  0.31
Chiu 1999   32  0.4340  0.0034  0.0729  0.3426  0.4629  0.40
Cohen 1997   63  0.3077  0.0068  0.0569  0.0544  0.1171  0.07
Cortot 1951   80  0.1731  0.0079  0.0381  0.0370  0.0389  0.03
Csalog 1996   56  0.3670  0.0060  0.0666  0.0633  0.3156  0.14
Czerny 1949   81  0.1732  0.0085  0.0384  0.0349  0.0775  0.05
Czerny 1990   13  0.523  0.048  0.1610  0.608  0.809  0.69
Duchoud 2007   30  0.4381  0.0038  0.0535  0.2418  0.5235  0.35
Ezaki 2006   65  0.3058  0.0064  0.0661  0.0633  0.3254  0.14
Falvay 1989   41  0.4125  0.0041  0.0641  0.209  0.5238  0.32
Farrell 1958   77  0.2082  0.0081  0.0474  0.0463  0.0579  0.04
Ferenczy 1958   90  -0.0390  0.0090  0.0290  0.0275  0.0390  0.02
Fliere 1977   3  0.617  0.024  0.245  0.7712  0.773  0.77
Fou 1978   51  0.3771  0.0057  0.0947  0.0942  0.1857  0.13
Francois 1956   62  0.3137  0.0069  0.0656  0.0631  0.4153  0.16
Friedman 1923   35  0.4262  0.0040  0.0840  0.2033  0.4441  0.30
Friedman 1923b   33  0.4326  0.0036  0.0731  0.2634  0.4933  0.36
Friedman 1930   25  0.4646  0.0029  0.0824  0.3918  0.6123  0.49
Garcia 2007   59  0.3461  0.0049  0.0754  0.0731  0.3751  0.16
Garcia 2007b   15  0.4918  0.0027  0.0828  0.3611  0.6824  0.49
Gierzod 1998   78  0.1742  0.0051  0.0570  0.0534  0.2763  0.12
Gornostaeva 1994   53  0.3615  0.0125  0.0839  0.2020  0.5936  0.34
Groot 1988   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Harasiewicz 1955   38  0.4229  0.0042  0.0642  0.1724  0.4043  0.26
Hatto 1993   9  0.5456  0.007  0.196  0.739  0.697  0.71
Hatto 1997   43  0.4049  0.0044  0.0744  0.1415  0.4742  0.26
Horowitz 1949   24  0.4734  0.0030  0.1034  0.2523  0.5431  0.37
Indjic 1988   10  0.5220  0.0010  0.159  0.698  0.718  0.70
Kapell 1951   55  0.3685  0.0058  0.0663  0.0659  0.0673  0.06
Kissin 1993   16  0.4823  0.0019  0.0915  0.5316  0.6814  0.60
Kushner 1989   18  0.4828  0.0028  0.0827  0.3715  0.5726  0.46
Luisada 1991   4  0.619  0.012  0.192  0.802  0.831  0.81
Lushtak 2004   79  0.1736  0.0083  0.0287  0.0266  0.0588  0.03
Malcuzynski 1961   42  0.4135  0.0056  0.0848  0.0832  0.2258  0.13
Magaloff 1978   34  0.4247  0.0039  0.0738  0.2219  0.4937  0.33
Magin 1975   5  0.602  0.105  0.277  0.715  0.844  0.77
Michalowski 1933   14  0.5217  0.0018  0.0813  0.547  0.6416  0.59
Milkina 1970   69  0.2464  0.0066  0.0662  0.0634  0.3455  0.14
Mohovich 1999   60  0.3322  0.0052  0.0849  0.0826  0.3549  0.17
Moravec 1969   48  0.3951  0.0037  0.0632  0.2514  0.5232  0.36
Morozova 2008   27  0.4416  0.009  0.1312  0.566  0.6515  0.60
Neighaus 1950   22  0.4833  0.0013  0.1616  0.5311  0.5221  0.52
Niedzielski 1931   29  0.4348  0.0045  0.0843  0.1525  0.3944  0.24
Ohlsson 1999   47  0.3965  0.0043  0.0745  0.1343  0.1065  0.11
Osinska 1989   64  0.3075  0.0067  0.0751  0.0757  0.0572  0.06
Pachmann 1927   36  0.4224  0.0055  0.0752  0.0732  0.4647  0.18
Paderewski 1930   17  0.4814  0.0121  0.1419  0.4613  0.6420  0.54
Perlemuter 1992   12  0.5260  0.0020  0.1117  0.535  0.7611  0.63
Pierdomenico 2008   50  0.3769  0.0063  0.0657  0.0633  0.2562  0.12
Poblocka 1999   26  0.454  0.0233  0.0737  0.2312  0.5234  0.35
Rabcewiczowa 1932   70  0.2444  0.0074  0.0476  0.0444  0.1469  0.07
Rachmaninoff 1923   37  0.4230  0.0046  0.0946  0.0921  0.5545  0.22
Rangell 2001   74  0.2286  0.0071  0.0568  0.0568  0.0576  0.05
Richter 1976   11  0.5211  0.0115  0.1414  0.5325  0.6913  0.60
Rosen 1989   54  0.3638  0.0047  0.0658  0.0639  0.2759  0.13
Rosenthal 1930   57  0.3512  0.0150  0.0659  0.0616  0.5448  0.18
Rosenthal 1931   87  0.0983  0.0075  0.0475  0.0441  0.2666  0.10
Rosenthal 1931b   86  0.0987  0.0078  0.0383  0.0345  0.1274  0.06
Rosenthal 1931c   73  0.2363  0.0065  0.0665  0.0630  0.4352  0.16
Rosenthal 1931d   84  0.1391  0.0070  0.0472  0.0430  0.3864  0.12
Rossi 2007   85  0.1172  0.0087  0.0286  0.0266  0.0484  0.03
Rubinstein 1939   66  0.2878  0.0061  0.0660  0.0643  0.1268  0.08
Rubinstein 1952   21  0.4857  0.0024  0.0820  0.454  0.6818  0.55
Rubinstein 1966   52  0.3752  0.0054  0.0750  0.0745  0.0770  0.07
Schilhawsky 1960   76  0.2076  0.0086  0.0379  0.0349  0.0681  0.04
Shebanova 2002   7  0.5613  0.0111  0.218  0.7019  0.6610  0.68
Smith 1975   49  0.3853  0.0062  0.0753  0.0722  0.4646  0.18
Sokolov 2002   28  0.4454  0.0023  0.0826  0.376  0.6722  0.50
Sztompka 1959   6  0.606  0.026  0.214  0.777  0.775  0.77
Tomsic 1995   23  0.475  0.0212  0.1418  0.506  0.5819  0.54
Uninsky 1932   20  0.4859  0.0031  0.0923  0.4125  0.4228  0.41
Uninsky 1971   40  0.4166  0.0035  0.0730  0.3312  0.4730  0.39
Wasowski 1980   8  0.558  0.0114  0.1711  0.5911  0.6612  0.62
Zak 1937   67  0.2755  0.0072  0.0471  0.0462  0.0580  0.04
Zak 1951   71  0.2467  0.0076  0.0378  0.0372  0.0385  0.03
Average   1  0.681  0.641  0.631  0.907  0.656  0.76
Random 1   88  0.0168  0.0088  0.0288  0.0214  0.3767  0.09
Random 2   89  0.0079  0.0089  0.0289  0.0256  0.0587  0.03
Random 3   91  -0.0780  0.0091  0.0191  0.0191  0.0191  0.01

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).