Groot 1988

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   38  0.4111  0.0215  0.1024  0.397  0.6024  0.48
Anderszewski 2003   81  0.1672  0.0081  0.0381  0.0360  0.0485  0.03
Ashkenazy 1981   1  0.623  0.122  0.202  0.788  0.802  0.79
Bacha 2000   74  0.2187  0.0076  0.0376  0.0361  0.0578  0.04
Badura 1965   67  0.2649  0.0072  0.0472  0.0454  0.0481  0.04
Barbosa 1983   57  0.3424  0.0047  0.0566  0.0518  0.4950  0.16
Biret 1990   71  0.2488  0.0079  0.0379  0.0347  0.0877  0.05
Blet 2003   18  0.4834  0.0025  0.0820  0.456  0.6816  0.55
Block 1995   30  0.4373  0.0031  0.0721  0.4220  0.5026  0.46
Blumental 1952   60  0.3256  0.0058  0.0663  0.0631  0.3059  0.13
Boshniakovich 1969   43  0.4042  0.0052  0.0754  0.0738  0.2460  0.13
Brailowsky 1960   82  0.1683  0.0083  0.0384  0.0379  0.0382  0.03
Bunin 1987   45  0.4027  0.0016  0.0832  0.2528  0.4138  0.32
Bunin 1987b   44  0.4044  0.0021  0.0835  0.2426  0.4039  0.31
Chiu 1999   31  0.4343  0.0033  0.0728  0.3425  0.4628  0.40
Cohen 1997   62  0.3077  0.0067  0.0568  0.0543  0.1170  0.07
Cortot 1951   79  0.1736  0.0078  0.0380  0.0369  0.0388  0.03
Csalog 1996   55  0.3669  0.0059  0.0665  0.0632  0.3155  0.14
Czerny 1949   80  0.1737  0.0084  0.0383  0.0348  0.0775  0.05
Czerny 1990   12  0.525  0.097  0.169  0.607  0.808  0.69
Duchoud 2007   29  0.4380  0.0037  0.0634  0.2417  0.5234  0.35
Ezaki 2006   64  0.3059  0.0063  0.0660  0.0632  0.3253  0.14
Falvay 1989   40  0.4120  0.0040  0.0640  0.208  0.5237  0.32
Farrell 1958   76  0.2081  0.0080  0.0473  0.0462  0.0579  0.04
Ferenczy 1958   89  -0.0389  0.0089  0.0289  0.0274  0.0389  0.02
Fliere 1977   2  0.614  0.113  0.254  0.7711  0.773  0.77
Fou 1978   50  0.3770  0.0056  0.0946  0.0941  0.1856  0.13
Francois 1956   61  0.3139  0.0068  0.0755  0.0730  0.4149  0.17
Friedman 1923   34  0.4262  0.0039  0.0839  0.2032  0.4440  0.30
Friedman 1923b   32  0.4331  0.0035  0.0830  0.2633  0.4932  0.36
Friedman 1930   24  0.4647  0.0028  0.0823  0.3917  0.6122  0.49
Garcia 2007   58  0.3460  0.0048  0.0753  0.0730  0.3751  0.16
Garcia 2007b   14  0.4921  0.0026  0.0827  0.3610  0.6823  0.49
Gierzod 1998   77  0.1745  0.0050  0.0569  0.0533  0.2762  0.12
Gornostaeva 1994   52  0.3616  0.0124  0.0838  0.2019  0.5935  0.34
Groot 1988   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Harasiewicz 1955   37  0.4228  0.0041  0.0641  0.1723  0.4042  0.26
Hatto 1993   8  0.5418  0.016  0.205  0.738  0.696  0.71
Hatto 1997   42  0.4052  0.0043  0.0743  0.1414  0.4741  0.26
Horowitz 1949   23  0.4738  0.0029  0.1033  0.2522  0.5430  0.37
Indjic 1988   9  0.5222  0.009  0.158  0.697  0.717  0.70
Kapell 1951   54  0.3684  0.0057  0.0662  0.0658  0.0672  0.06
Kissin 1993   15  0.4825  0.0018  0.0914  0.5315  0.6813  0.60
Kushner 1989   17  0.4832  0.0027  0.0826  0.3714  0.5725  0.46
Luisada 1991   3  0.611  0.191  0.191  0.801  0.831  0.81
Lushtak 2004   78  0.1740  0.0082  0.0286  0.0265  0.0587  0.03
Malcuzynski 1961   41  0.4135  0.0055  0.0847  0.0831  0.2257  0.13
Magaloff 1978   33  0.4226  0.0038  0.0737  0.2218  0.4936  0.33
Magin 1975   4  0.602  0.154  0.276  0.715  0.844  0.77
Michalowski 1933   13  0.5219  0.0017  0.0812  0.546  0.6415  0.59
Milkina 1970   68  0.2448  0.0065  0.0661  0.0633  0.3454  0.14
Mohovich 1999   59  0.3323  0.0051  0.0848  0.0825  0.3548  0.17
Moravec 1969   47  0.3954  0.0036  0.0631  0.2513  0.5231  0.36
Morozova 2008   26  0.4410  0.028  0.1311  0.565  0.6514  0.60
Neighaus 1950   21  0.489  0.0212  0.1615  0.5310  0.5220  0.52
Niedzielski 1931   28  0.4350  0.0044  0.0842  0.1524  0.3943  0.24
Ohlsson 1999   46  0.3964  0.0042  0.0744  0.1342  0.1064  0.11
Osinska 1989   63  0.3074  0.0066  0.0750  0.0756  0.0571  0.06
Pachmann 1927   35  0.4229  0.0054  0.0751  0.0731  0.4646  0.18
Paderewski 1930   16  0.4817  0.0120  0.1418  0.4612  0.6419  0.54
Perlemuter 1992   11  0.5261  0.0019  0.1116  0.534  0.7610  0.63
Pierdomenico 2008   49  0.3768  0.0062  0.0656  0.0632  0.2561  0.12
Poblocka 1999   25  0.458  0.0332  0.0736  0.2311  0.5233  0.35
Rabcewiczowa 1932   69  0.2446  0.0073  0.0475  0.0443  0.1468  0.07
Rachmaninoff 1923   36  0.4233  0.0045  0.1045  0.1020  0.5544  0.23
Rangell 2001   73  0.2285  0.0070  0.0567  0.0567  0.0576  0.05
Richter 1976   10  0.5214  0.0114  0.1413  0.5324  0.6912  0.60
Rosen 1989   53  0.3630  0.0046  0.0657  0.0638  0.2758  0.13
Rosenthal 1930   56  0.3515  0.0149  0.0658  0.0615  0.5447  0.18
Rosenthal 1931   86  0.0982  0.0074  0.0474  0.0440  0.2665  0.10
Rosenthal 1931b   85  0.0986  0.0077  0.0382  0.0344  0.1273  0.06
Rosenthal 1931c   72  0.2363  0.0064  0.0664  0.0629  0.4352  0.16
Rosenthal 1931d   83  0.1390  0.0069  0.0471  0.0429  0.3863  0.12
Rossi 2007   84  0.1171  0.0086  0.0385  0.0365  0.0483  0.03
Rubinstein 1939   65  0.2875  0.0060  0.0659  0.0642  0.1266  0.08
Rubinstein 1952   20  0.4851  0.0023  0.0819  0.453  0.6817  0.55
Rubinstein 1966   51  0.3755  0.0053  0.0749  0.0744  0.0769  0.07
Schilhawsky 1960   75  0.2076  0.0085  0.0378  0.0348  0.0680  0.04
Shebanova 2002   6  0.5613  0.0110  0.227  0.7018  0.669  0.68
Smith 1975   48  0.3857  0.0061  0.0752  0.0721  0.4645  0.18
Sokolov 2002   27  0.4453  0.0022  0.0825  0.375  0.6721  0.50
Sztompka 1959   5  0.607  0.045  0.213  0.776  0.775  0.77
Tomsic 1995   22  0.476  0.0711  0.1417  0.505  0.5818  0.54
Uninsky 1932   19  0.4841  0.0030  0.1022  0.4124  0.4227  0.41
Uninsky 1971   39  0.4165  0.0034  0.0729  0.3311  0.4729  0.39
Wasowski 1980   7  0.5512  0.0213  0.1810  0.5910  0.6611  0.62
Zak 1937   66  0.2758  0.0071  0.0470  0.0461  0.0674  0.05
Zak 1951   70  0.2466  0.0075  0.0377  0.0371  0.0384  0.03
Random 1   87  0.0167  0.0087  0.0287  0.0215  0.3567  0.08
Random 2   88  0.0078  0.0088  0.0288  0.0256  0.0586  0.03
Random 3   90  -0.0779  0.0090  0.0190  0.0190  0.0190  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).