Groot 1988

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   8  0.714  0.0614  0.1022  0.4336  0.2629  0.33
Anderszewski 2003   67  0.5172  0.0063  0.0454  0.0456  0.0472  0.04
Ashkenazy 1981   60  0.5656  0.0056  0.0468  0.0454  0.0583  0.04
Bacha 2000   36  0.6163  0.0047  0.0461  0.0427  0.2645  0.10
Badura 1965   70  0.4944  0.0067  0.0470  0.0465  0.0480  0.04
Barbosa 1983   39  0.6022  0.0031  0.1029  0.386  0.6012  0.48
Biret 1990   31  0.6470  0.0040  0.0540  0.1864  0.0551  0.09
Blet 2003   42  0.6064  0.0051  0.0550  0.0559  0.0473  0.04
Block 1995   20  0.679  0.027  0.1021  0.444  0.4918  0.46
Blumental 1952   80  0.4046  0.0078  0.0375  0.0375  0.0389  0.03
Boshniakovich 1969   35  0.6158  0.0039  0.0637  0.2242  0.1436  0.18
Brailowsky 1960   14  0.7032  0.0020  0.0718  0.483  0.616  0.54
Bunin 1987   49  0.5867  0.0061  0.0460  0.0427  0.3343  0.11
Bunin 1987b   52  0.5786  0.0062  0.0647  0.0630  0.3339  0.14
Chiu 1999   54  0.5759  0.0033  0.1032  0.3120  0.3827  0.34
Cohen 1997   84  0.3588  0.0086  0.0458  0.0445  0.0764  0.05
Cortot 1951   53  0.5775  0.0064  0.0463  0.0441  0.1656  0.08
Csalog 1996   66  0.5126  0.0041  0.0542  0.1034  0.1940  0.14
Czerny 1949   59  0.5630  0.0055  0.0462  0.0455  0.0578  0.04
Czerny 1990   24  0.6628  0.0034  0.0833  0.3042  0.1037  0.17
Duchoud 2007   55  0.5751  0.0059  0.0469  0.0442  0.1554  0.08
Ezaki 2006   13  0.7124  0.0022  0.0915  0.4930  0.2924  0.38
Falvay 1989   4  0.7413  0.0110  0.128  0.546  0.615  0.57
Farrell 1958   12  0.7141  0.0017  0.0716  0.495  0.5211  0.50
Ferenczy 1958   61  0.5527  0.0065  0.0453  0.0456  0.0576  0.04
Fliere 1977   9  0.7162  0.0018  0.0712  0.5238  0.1931  0.31
Fou 1978   18  0.6818  0.0119  0.086  0.5516  0.4014  0.47
Francois 1956   5  0.733  0.085  0.133  0.574  0.594  0.58
Friedman 1923   88  0.2668  0.0088  0.0466  0.0457  0.0665  0.05
Friedman 1923b   87  0.2790  0.0087  0.0457  0.0461  0.0584  0.04
Friedman 1930   82  0.3778  0.0081  0.0387  0.0364  0.0575  0.04
Garcia 2007   76  0.4652  0.0075  0.0386  0.0341  0.1463  0.06
Garcia 2007b   86  0.3233  0.0082  0.0383  0.0328  0.1860  0.07
Gierzod 1998   44  0.5943  0.0057  0.0456  0.0470  0.0479  0.04
Gornostaeva 1994   29  0.6535  0.0026  0.0930  0.3715  0.4521  0.41
Groot 1988   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Harasiewicz 1955   45  0.5866  0.0028  0.1027  0.3835  0.2032  0.28
Hatto 1993   83  0.3571  0.0084  0.0376  0.0383  0.0390  0.03
Hatto 1997   78  0.4169  0.0080  0.0382  0.0381  0.0388  0.03
Horowitz 1949   23  0.6640  0.0023  0.0826  0.4017  0.4619  0.43
Indjic 1988   81  0.3883  0.0083  0.0384  0.0360  0.0571  0.04
Kapell 1951   37  0.6176  0.0043  0.0444  0.1060  0.0462  0.06
Kissin 1993   26  0.6580  0.0032  0.0931  0.3556  0.0541  0.13
Kushner 1989   21  0.6710  0.0229  0.1024  0.4131  0.2628  0.33
Luisada 1991   50  0.5779  0.0058  0.0452  0.0450  0.0566  0.04
Lushtak 2004   27  0.6554  0.0025  0.0910  0.5320  0.3120  0.41
Malcuzynski 1961   30  0.6482  0.0038  0.0639  0.2028  0.2334  0.21
Magaloff 1978   10  0.7121  0.006  0.1513  0.514  0.5010  0.50
Magin 1975   65  0.5253  0.0045  0.0445  0.0851  0.0561  0.06
Michalowski 1933   85  0.3285  0.0085  0.0378  0.0378  0.0387  0.03
Milkina 1970   7  0.7139  0.0021  0.0825  0.4120  0.3822  0.39
Mohovich 1999   1  0.801  0.341  0.332  0.682  0.731  0.70
Moravec 1969   63  0.5445  0.0077  0.0377  0.0376  0.0385  0.03
Morozova 2008   58  0.5631  0.0037  0.0638  0.2042  0.1138  0.15
Neighaus 1950   6  0.7261  0.0013  0.1111  0.5226  0.3023  0.39
Niedzielski 1931   64  0.5336  0.0068  0.0465  0.0454  0.0467  0.04
Ohlsson 1999   51  0.5723  0.0060  0.0471  0.0453  0.0569  0.04
Osinska 1989   15  0.6934  0.0024  0.0923  0.4330  0.2726  0.34
Pachmann 1927   46  0.5877  0.0044  0.0543  0.1013  0.3835  0.19
Paderewski 1930   40  0.6047  0.0053  0.0372  0.0346  0.0668  0.04
Perlemuter 1992   11  0.7120  0.009  0.134  0.567  0.517  0.53
Pierdomenico 2008   34  0.636  0.0411  0.1120  0.457  0.4913  0.47
Poblocka 1999   57  0.5625  0.0050  0.0451  0.0483  0.0386  0.03
Rabcewiczowa 1932   56  0.5649  0.0054  0.0464  0.0442  0.1157  0.07
Rachmaninoff 1923   33  0.6317  0.0127  0.0928  0.3821  0.3425  0.36
Rangell 2001   48  0.5815  0.0130  0.1035  0.2617  0.3930  0.32
Richter 1976   62  0.5529  0.0052  0.0548  0.0545  0.1058  0.07
Rosen 1989   32  0.6338  0.0036  0.1036  0.2634  0.2333  0.24
Rosenthal 1930   71  0.4914  0.0169  0.0380  0.0336  0.2055  0.08
Rosenthal 1931   73  0.4891  0.0066  0.0459  0.0425  0.3742  0.12
Rosenthal 1931b   75  0.4673  0.0070  0.0467  0.0423  0.3244  0.11
Rosenthal 1931c   72  0.4874  0.0076  0.0373  0.0338  0.1859  0.07
Rosenthal 1931d   69  0.5081  0.0072  0.0381  0.0326  0.2652  0.09
Rossi 2007   79  0.4048  0.0074  0.0385  0.0325  0.2849  0.09
Rubinstein 1939   77  0.4337  0.0079  0.0379  0.0336  0.1953  0.08
Rubinstein 1952   25  0.668  0.0215  0.0819  0.458  0.589  0.51
Rubinstein 1966   17  0.6912  0.0112  0.115  0.563  0.722  0.63
Schilhawsky 1960   47  0.5850  0.0048  0.0549  0.0562  0.0474  0.04
Shebanova 2002   28  0.6565  0.0035  0.0934  0.2765  0.0447  0.10
Smith 1975   22  0.6616  0.0116  0.0714  0.4915  0.4316  0.46
Sokolov 2002   43  0.5942  0.0046  0.0455  0.0440  0.2048  0.09
Sztompka 1959   41  0.605  0.0449  0.0746  0.0745  0.1250  0.09
Tomsic 1995   3  0.7619  0.003  0.239  0.544  0.683  0.61
Uninsky 1932   74  0.4757  0.0073  0.0388  0.0352  0.0677  0.04
Uninsky 1971   68  0.5055  0.0071  0.0374  0.0351  0.0670  0.04
Wasowski 1980   38  0.6060  0.0042  0.0541  0.1143  0.0946  0.10
Zak 1937   19  0.687  0.048  0.1217  0.4813  0.4615  0.47
Zak 1951   16  0.6911  0.014  0.157  0.5510  0.488  0.51
Average   2  0.792  0.222  0.361  0.7230  0.3017  0.46
Random 1   91  -0.1689  0.0091  0.0191  0.0144  0.1381  0.04
Random 2   90  -0.1284  0.0089  0.0190  0.0185  0.0291  0.01
Random 3   89  -0.0387  0.0090  0.0189  0.0134  0.1682  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).