Gornostaeva 1994

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   33  0.3032  0.0030  0.0829  0.3943  0.1633  0.25
Anderszewski 2003   46  0.2723  0.0036  0.1037  0.2831  0.2532  0.26
Ashkenazy 1981   72  0.1655  0.0078  0.0285  0.0278  0.0483  0.03
Bacha 2000   60  0.2069  0.0065  0.0559  0.0563  0.0554  0.05
Badura 1965   71  0.1670  0.0066  0.0464  0.0453  0.0470  0.04
Barbosa 1983   58  0.2085  0.0053  0.0554  0.0583  0.0367  0.04
Biret 1990   14  0.4316  0.0115  0.1220  0.599  0.6712  0.63
Blet 2003   82  0.1271  0.0081  0.0286  0.0277  0.0387  0.02
Block 1995   21  0.3846  0.0025  0.1321  0.5641  0.1528  0.29
Blumental 1952   76  0.1556  0.0068  0.0369  0.0380  0.0382  0.03
Boshniakovich 1969   53  0.2463  0.0039  0.0839  0.2147  0.0744  0.12
Brailowsky 1960   38  0.2820  0.0037  0.1434  0.3139  0.2431  0.27
Bunin 1987   69  0.1644  0.0074  0.0371  0.0355  0.0671  0.04
Bunin 1987b   70  0.1652  0.0075  0.0467  0.0465  0.0564  0.04
Chiu 1999   29  0.3235  0.0056  0.0558  0.0572  0.0459  0.04
Cohen 1997   9  0.478  0.029  0.1111  0.667  0.6410  0.65
Cortot 1951   11  0.4721  0.0011  0.1513  0.653  0.739  0.69
Csalog 1996   27  0.3336  0.0049  0.0846  0.0844  0.1445  0.11
Czerny 1949   7  0.4919  0.0010  0.118  0.735  0.864  0.79
Czerny 1990   75  0.1564  0.0076  0.0379  0.0363  0.0572  0.04
Duchoud 2007   32  0.3126  0.0034  0.1130  0.3949  0.0736  0.17
Ezaki 2006   15  0.4117  0.0014  0.1316  0.6315  0.6411  0.63
Falvay 1989   30  0.3242  0.0027  0.1127  0.4533  0.2226  0.31
Farrell 1958   34  0.3047  0.0033  0.0836  0.2939  0.1735  0.22
Ferenczy 1958   35  0.3045  0.0031  0.1028  0.4515  0.7516  0.58
Fliere 1977   28  0.3331  0.0046  0.0749  0.0763  0.0551  0.06
Fou 1978   47  0.2678  0.0047  0.0748  0.0766  0.0455  0.05
Francois 1956   8  0.4839  0.008  0.177  0.774  0.787  0.77
Friedman 1923   74  0.1562  0.0082  0.0287  0.0278  0.0389  0.02
Friedman 1923b   80  0.1448  0.0083  0.0377  0.0378  0.0384  0.03
Friedman 1930   54  0.2213  0.0157  0.0461  0.0458  0.0657  0.05
Garcia 2007   78  0.1472  0.0052  0.0555  0.0577  0.0369  0.04
Garcia 2007b   87  0.0686  0.0090  0.0190  0.0186  0.0290  0.01
Gierzod 1998   50  0.2537  0.0028  0.1126  0.4527  0.4023  0.42
Gornostaeva 1994   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Groot 1988   25  0.365  0.0321  0.1919  0.5938  0.2025  0.34
Harasiewicz 1955   12  0.453  0.115  0.209  0.719  0.5514  0.62
Hatto 1993   63  0.1849  0.0064  0.0462  0.0478  0.0473  0.04
Hatto 1997   26  0.3380  0.0032  0.0735  0.3050  0.0639  0.13
Horowitz 1949   65  0.1757  0.0079  0.0283  0.0257  0.0676  0.03
Indjic 1988   81  0.1381  0.0071  0.0372  0.0375  0.0480  0.03
Kapell 1951   73  0.1550  0.0080  0.0378  0.0369  0.0563  0.04
Kissin 1993   88  0.0465  0.0087  0.0282  0.0276  0.0579  0.03
Kushner 1989   37  0.2866  0.0054  0.0553  0.0576  0.0462  0.04
Luisada 1991   59  0.2087  0.0070  0.0373  0.0376  0.0474  0.03
Lushtak 2004   43  0.2758  0.0045  0.0650  0.0661  0.0558  0.05
Malcuzynski 1961   56  0.2173  0.0059  0.0560  0.0571  0.0465  0.04
Magaloff 1978   13  0.459  0.0117  0.1315  0.6420  0.4719  0.55
Magin 1975   62  0.1951  0.0067  0.0374  0.0356  0.0661  0.04
Michalowski 1933   55  0.2253  0.0062  0.0557  0.0563  0.0656  0.05
Milkina 1970   42  0.2759  0.0023  0.1223  0.5321  0.4620  0.49
Mohovich 1999   18  0.4012  0.0119  0.1717  0.6216  0.5018  0.56
Moravec 1969   45  0.2724  0.0029  0.1033  0.3539  0.1734  0.24
Morozova 2008   31  0.3218  0.0035  0.1031  0.3574  0.0442  0.12
Neighaus 1950   10  0.4714  0.0112  0.2112  0.6522  0.3621  0.48
Niedzielski 1931   79  0.1474  0.0077  0.0284  0.0278  0.0385  0.02
Ohlsson 1999   16  0.4125  0.0022  0.1232  0.3574  0.0440  0.12
Osinska 1989   1  0.621  0.431  0.431  0.881  0.852  0.86
Pachmann 1927   61  0.1975  0.0073  0.0375  0.0377  0.0478  0.03
Paderewski 1930   77  0.1460  0.0069  0.0466  0.0477  0.0377  0.03
Perlemuter 1992   17  0.4028  0.0020  0.1610  0.6629  0.5017  0.57
Pierdomenico 2008   52  0.2479  0.0058  0.0463  0.0466  0.0460  0.04
Poblocka 1999   41  0.2833  0.0048  0.0845  0.0858  0.0552  0.06
Rabcewiczowa 1932   2  0.622  0.182  0.352  0.841  0.901  0.87
Rachmaninoff 1923   51  0.2429  0.0043  0.0743  0.1747  0.0646  0.10
Rangell 2001   48  0.2667  0.0026  0.1125  0.4739  0.1829  0.29
Richter 1976   40  0.2843  0.0061  0.0465  0.0461  0.0566  0.04
Rosen 1989   4  0.567  0.024  0.333  0.823  0.765  0.79
Rosenthal 1930   20  0.3834  0.0018  0.1418  0.6010  0.6413  0.62
Rosenthal 1931   64  0.1861  0.0051  0.0651  0.0641  0.2341  0.12
Rosenthal 1931b   66  0.1782  0.0055  0.0652  0.0640  0.1549  0.09
Rosenthal 1931c   39  0.2883  0.0040  0.0738  0.2330  0.3927  0.30
Rosenthal 1931d   68  0.1615  0.0141  0.0741  0.1924  0.4230  0.28
Rossi 2007   23  0.3711  0.0138  0.0940  0.215  0.6224  0.36
Rubinstein 1939   19  0.4030  0.0013  0.1622  0.5510  0.4022  0.47
Rubinstein 1952   22  0.3840  0.0016  0.1214  0.6513  0.5615  0.60
Rubinstein 1966   24  0.3754  0.0024  0.1424  0.5367  0.0438  0.15
Schilhawsky 1960   84  0.0976  0.0088  0.0288  0.0284  0.0288  0.02
Shebanova 2002   67  0.1727  0.0084  0.0380  0.0383  0.0381  0.03
Smith 1975   3  0.574  0.073  0.256  0.773  0.823  0.79
Sokolov 2002   5  0.5410  0.017  0.315  0.781  0.776  0.77
Sztompka 1959   36  0.2922  0.0044  0.0944  0.1743  0.1437  0.15
Tomsic 1995   49  0.2584  0.0042  0.0742  0.1853  0.0547  0.09
Uninsky 1932   57  0.2077  0.0060  0.0556  0.0575  0.0468  0.04
Uninsky 1971   6  0.516  0.036  0.264  0.791  0.688  0.73
Wasowski 1980   44  0.2788  0.0050  0.0847  0.0869  0.0550  0.06
Zak 1937   85  0.0989  0.0086  0.0281  0.0277  0.0386  0.02
Zak 1951   83  0.1068  0.0085  0.0376  0.0380  0.0375  0.03
Random 1   89  0.0090  0.0072  0.0370  0.0325  0.2848  0.09
Random 2   86  0.0641  0.0063  0.0368  0.0311  0.4743  0.12
Random 3   90  -0.0138  0.0089  0.0189  0.0122  0.3353  0.06

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).