Neighaus 1950

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   19  0.6129  0.0021  0.0921  0.4211  0.4725  0.44
Anderszewski 2003   69  0.4286  0.0063  0.0468  0.0431  0.2366  0.10
Ashkenazy 1981   22  0.6032  0.0026  0.0729  0.2823  0.3534  0.31
Bacha 2000   58  0.4938  0.0072  0.0467  0.0422  0.4057  0.13
Badura 1965   78  0.3687  0.0077  0.0470  0.0464  0.0487  0.04
Barbosa 1983   54  0.5150  0.0032  0.0728  0.286  0.5627  0.40
Biret 1990   16  0.6233  0.0024  0.1127  0.366  0.5624  0.45
Blet 2003   26  0.5962  0.0028  0.0818  0.463  0.5521  0.50
Block 1995   46  0.5511  0.0329  0.0733  0.216  0.5430  0.34
Blumental 1952   79  0.3644  0.0074  0.0474  0.0441  0.1180  0.07
Boshniakovich 1969   12  0.6520  0.0122  0.0915  0.503  0.6911  0.59
Brailowsky 1960   56  0.5074  0.0071  0.0476  0.0433  0.1773  0.08
Bunin 1987   30  0.5888  0.0048  0.0557  0.0523  0.3658  0.13
Bunin 1987b   29  0.5861  0.0049  0.0845  0.0823  0.3547  0.17
Chiu 1999   40  0.5513  0.0220  0.1117  0.468  0.6217  0.53
Cohen 1997   81  0.3451  0.0079  0.0285  0.0242  0.1183  0.05
Cortot 1951   55  0.5123  0.0142  0.0537  0.1624  0.3337  0.23
Csalog 1996   73  0.4058  0.0086  0.0464  0.0461  0.0586  0.04
Czerny 1949   41  0.5564  0.0035  0.0632  0.2114  0.5629  0.34
Czerny 1990   42  0.5575  0.0038  0.0644  0.1132  0.2250  0.16
Duchoud 2007   32  0.5865  0.0040  0.0542  0.1313  0.4736  0.25
Ezaki 2006   4  0.695  0.064  0.1113  0.553  0.668  0.60
Falvay 1989   31  0.5849  0.0031  0.0830  0.2513  0.3932  0.31
Farrell 1958   20  0.6110  0.0416  0.1122  0.411  0.7015  0.54
Ferenczy 1958   76  0.3871  0.0085  0.0475  0.0450  0.0682  0.05
Fliere 1977   7  0.6818  0.0112  0.1212  0.555  0.6310  0.59
Fou 1978   18  0.6214  0.0218  0.1020  0.426  0.5222  0.47
Francois 1956   15  0.638  0.047  0.1211  0.562  0.667  0.61
Friedman 1923   84  0.3380  0.0067  0.0380  0.038  0.4663  0.12
Friedman 1923b   80  0.3577  0.0066  0.0472  0.046  0.5156  0.14
Friedman 1930   66  0.4570  0.0054  0.0560  0.0513  0.5049  0.16
Garcia 2007   82  0.3463  0.0081  0.0286  0.0217  0.4371  0.09
Garcia 2007b   85  0.3284  0.0084  0.0382  0.0319  0.3669  0.10
Gierzod 1998   25  0.6078  0.0033  0.0831  0.248  0.4231  0.32
Gornostaeva 1994   3  0.6912  0.025  0.124  0.604  0.665  0.63
Groot 1988   8  0.6722  0.0114  0.168  0.574  0.5912  0.58
Harasiewicz 1955   33  0.582  0.132  0.152  0.651  0.569  0.60
Hatto 1993   70  0.4268  0.0069  0.0465  0.0435  0.1876  0.08
Hatto 1997   65  0.4624  0.0153  0.0653  0.0630  0.2264  0.11
Horowitz 1949   34  0.5834  0.0045  0.0559  0.0512  0.3953  0.14
Indjic 1988   71  0.4259  0.0068  0.0381  0.0338  0.1579  0.07
Kapell 1951   49  0.5455  0.0061  0.0558  0.0545  0.0978  0.07
Kissin 1993   36  0.5752  0.0037  0.0640  0.1324  0.3242  0.20
Kushner 1989   39  0.5689  0.0056  0.0654  0.0628  0.2559  0.12
Luisada 1991   43  0.5528  0.0034  0.0639  0.1419  0.3438  0.22
Lushtak 2004   17  0.6215  0.0119  0.1019  0.455  0.5819  0.51
Malcuzynski 1961   2  0.7060  0.0011  0.089  0.579  0.5116  0.54
Magaloff 1978   5  0.6821  0.0113  0.125  0.603  0.5513  0.57
Magin 1975   62  0.4846  0.0064  0.0466  0.0431  0.2170  0.09
Michalowski 1933   68  0.4337  0.0059  0.0561  0.0530  0.3060  0.12
Milkina 1970   44  0.5530  0.0051  0.0846  0.0820  0.3646  0.17
Mohovich 1999   6  0.6817  0.019  0.127  0.571  0.742  0.65
Moravec 1969   64  0.4748  0.0065  0.0471  0.0440  0.1177  0.07
Morozova 2008   45  0.5519  0.0125  0.0824  0.3711  0.4028  0.38
Neighaus 1950   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Niedzielski 1931   75  0.4053  0.0080  0.0287  0.0256  0.0488  0.03
Ohlsson 1999   10  0.664  0.0717  0.1223  0.3812  0.4426  0.41
Osinska 1989   24  0.6016  0.0123  0.1025  0.377  0.5623  0.46
Pachmann 1927   52  0.5235  0.0050  0.0747  0.0713  0.5343  0.19
Paderewski 1930   53  0.5166  0.0044  0.0741  0.1319  0.3440  0.21
Perlemuter 1992   37  0.579  0.0410  0.0916  0.496  0.6114  0.55
Pierdomenico 2008   48  0.5442  0.0052  0.0650  0.067  0.5245  0.18
Poblocka 1999   38  0.5669  0.0039  0.0536  0.1734  0.2044  0.18
Rabcewiczowa 1932   23  0.6027  0.0027  0.0726  0.364  0.7020  0.50
Rachmaninoff 1923   57  0.4972  0.0030  0.0735  0.1912  0.4735  0.30
Rangell 2001   27  0.5936  0.0047  0.0651  0.0610  0.4351  0.16
Richter 1976   72  0.4043  0.0082  0.0384  0.0350  0.0585  0.04
Rosen 1989   1  0.731  0.201  0.201  0.711  0.771  0.74
Rosenthal 1930   67  0.4573  0.0070  0.0477  0.0430  0.3562  0.12
Rosenthal 1931   83  0.3467  0.0078  0.0469  0.0435  0.1874  0.08
Rosenthal 1931b   77  0.3879  0.0075  0.0378  0.0323  0.3468  0.10
Rosenthal 1931c   51  0.5241  0.0058  0.0655  0.0614  0.4948  0.17
Rosenthal 1931d   74  0.4081  0.0076  0.0379  0.0327  0.2275  0.08
Rossi 2007   86  0.2482  0.0083  0.0383  0.0313  0.3665  0.10
Rubinstein 1939   87  0.2476  0.0087  0.0473  0.0469  0.0484  0.04
Rubinstein 1952   61  0.4845  0.0073  0.0563  0.0536  0.1672  0.09
Rubinstein 1966   50  0.5239  0.0062  0.0749  0.0730  0.3054  0.14
Schilhawsky 1960   60  0.4983  0.0060  0.0562  0.0533  0.2267  0.10
Shebanova 2002   35  0.5856  0.0055  0.0748  0.0732  0.3055  0.14
Smith 1975   14  0.643  0.073  0.113  0.643  0.616  0.62
Sokolov 2002   21  0.6054  0.0041  0.0643  0.1229  0.3441  0.20
Sztompka 1959   28  0.5847  0.0046  0.0556  0.0514  0.4552  0.15
Tomsic 1995   9  0.6725  0.0015  0.1314  0.527  0.5318  0.52
Uninsky 1932   59  0.4931  0.0057  0.0652  0.0622  0.2661  0.12
Uninsky 1971   47  0.5526  0.0036  0.0734  0.2116  0.4533  0.31
Wasowski 1980   63  0.4840  0.0043  0.0638  0.1525  0.3039  0.21
Zak 1937   11  0.666  0.068  0.1310  0.572  0.704  0.63
Zak 1951   13  0.657  0.056  0.116  0.582  0.703  0.64
Random 1   88  0.0257  0.0088  0.0288  0.0230  0.2081  0.06
Random 2   90  -0.0685  0.0090  0.0190  0.0178  0.0290  0.01
Random 3   89  0.0190  0.0089  0.0189  0.0173  0.0389  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).