Hatto 1993

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   57  0.4139  0.0071  0.0384  0.0319  0.4269  0.11
Anderszewski 2003   17  0.5440  0.0014  0.1016  0.5024  0.4818  0.49
Ashkenazy 1981   72  0.3641  0.0083  0.0467  0.0449  0.0585  0.04
Bacha 2000   56  0.4323  0.0075  0.0457  0.0412  0.4752  0.14
Badura 1965   52  0.4424  0.0055  0.0554  0.0517  0.4548  0.15
Barbosa 1983   18  0.5442  0.0033  0.0730  0.3362  0.0656  0.14
Biret 1990   12  0.5543  0.0015  0.0913  0.5415  0.5116  0.52
Blet 2003   71  0.3744  0.0049  0.0466  0.0418  0.3068  0.11
Block 1995   64  0.3915  0.0059  0.0473  0.0439  0.1777  0.08
Blumental 1952   7  0.5945  0.0010  0.139  0.627  0.709  0.66
Boshniakovich 1969   43  0.463  0.0028  0.0831  0.3334  0.2537  0.29
Brailowsky 1960   26  0.5146  0.0036  0.0835  0.2531  0.4034  0.32
Bunin 1987   51  0.4447  0.0056  0.0378  0.0318  0.3671  0.10
Bunin 1987b   55  0.4316  0.0063  0.0465  0.0421  0.3961  0.12
Chiu 1999   60  0.4048  0.0074  0.0474  0.0440  0.1774  0.08
Cohen 1997   74  0.3649  0.0048  0.0461  0.045  0.5449  0.15
Cortot 1951   75  0.359  0.0079  0.0556  0.0516  0.4750  0.15
Csalog 1996   46  0.4525  0.0030  0.0836  0.2325  0.3339  0.28
Czerny 1949   24  0.5226  0.0013  0.1211  0.5822  0.6311  0.60
Czerny 1990   10  0.5827  0.008  0.207  0.6921  0.667  0.67
Duchoud 2007   83  0.3050  0.0085  0.0459  0.0443  0.1776  0.08
Ezaki 2006   16  0.5451  0.0032  0.0727  0.3735  0.2436  0.30
Falvay 1989   13  0.5510  0.0022  0.1121  0.4731  0.4622  0.46
Farrell 1958   42  0.4628  0.0040  0.0644  0.1625  0.4141  0.26
Ferenczy 1958   28  0.5052  0.0038  0.0639  0.209  0.6330  0.35
Fliere 1977   14  0.544  0.0026  0.0924  0.4327  0.4025  0.41
Fou 1978   49  0.4412  0.0068  0.0475  0.0467  0.0483  0.04
Francois 1956   80  0.3353  0.0072  0.0383  0.0332  0.2673  0.09
Friedman 1923   66  0.3954  0.0058  0.0469  0.045  0.5751  0.15
Friedman 1923b   68  0.3829  0.0065  0.0646  0.0610  0.5445  0.18
Friedman 1930   63  0.4055  0.0064  0.0553  0.0511  0.5247  0.16
Garcia 2007   79  0.3356  0.0080  0.0471  0.0434  0.2970  0.11
Garcia 2007b   58  0.4130  0.0037  0.0937  0.2318  0.4833  0.33
Gierzod 1998   5  0.6357  0.005  0.296  0.729  0.626  0.67
Gornostaeva 1994   54  0.4358  0.0067  0.0468  0.0456  0.0586  0.04
Groot 1988   20  0.5317  0.0017  0.1119  0.495  0.5617  0.52
Harasiewicz 1955   6  0.6259  0.006  0.205  0.736  0.675  0.70
Hatto 1993   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Hatto 1997   2  0.972  0.222  0.962  0.992  0.992  0.99
Horowitz 1949   82  0.3160  0.0081  0.0381  0.0318  0.4267  0.11
Indjic 1988   1  0.981  0.771  0.771  1.002  0.991  0.99
Kapell 1951   53  0.438  0.0052  0.0555  0.0566  0.0580  0.05
Kissin 1993   44  0.4518  0.0043  0.0738  0.2141  0.3043  0.25
Kushner 1989   19  0.5361  0.0024  0.0720  0.4934  0.3426  0.41
Luisada 1991   41  0.4713  0.0045  0.0645  0.1221  0.4644  0.23
Lushtak 2004   15  0.5462  0.0020  0.0917  0.5015  0.5415  0.52
Malcuzynski 1961   31  0.5031  0.0025  0.0823  0.4432  0.3827  0.41
Magaloff 1978   11  0.575  0.0012  0.1214  0.532  0.6710  0.60
Magin 1975   47  0.4563  0.0062  0.0550  0.0549  0.0779  0.06
Michalowski 1933   88  0.1164  0.0088  0.0289  0.0282  0.0289  0.02
Milkina 1970   8  0.5932  0.009  0.1610  0.5924  0.4614  0.52
Mohovich 1999   23  0.5265  0.0018  0.0918  0.4922  0.4820  0.48
Moravec 1969   27  0.5166  0.0027  0.0926  0.4116  0.5023  0.45
Morozova 2008   67  0.3914  0.0061  0.0472  0.0460  0.0584  0.04
Neighaus 1950   78  0.3367  0.0069  0.0458  0.0419  0.4360  0.13
Niedzielski 1931   81  0.3119  0.0070  0.0386  0.0328  0.2872  0.09
Ohlsson 1999   40  0.4768  0.0039  0.0642  0.1721  0.4440  0.27
Osinska 1989   4  0.6620  0.004  0.224  0.7511  0.664  0.70
Pachmann 1927   87  0.2069  0.0087  0.0388  0.0368  0.0388  0.03
Paderewski 1930   86  0.2170  0.0084  0.0470  0.0423  0.3563  0.12
Perlemuter 1992   76  0.3471  0.0054  0.0463  0.0418  0.4258  0.13
Pierdomenico 2008   73  0.366  0.0051  0.0460  0.0421  0.4954  0.14
Poblocka 1999   22  0.5272  0.0021  0.1022  0.4720  0.4821  0.47
Rabcewiczowa 1932   45  0.4533  0.0031  0.0832  0.3121  0.3929  0.35
Rachmaninoff 1923   39  0.4873  0.0019  0.1028  0.3612  0.5224  0.43
Rangell 2001   70  0.3774  0.0076  0.0385  0.0336  0.2278  0.08
Richter 1976   77  0.3475  0.0082  0.0379  0.0355  0.0487  0.03
Rosen 1989   25  0.5234  0.0023  0.0925  0.4112  0.5819  0.49
Rosenthal 1930   50  0.4476  0.0057  0.0380  0.0321  0.4865  0.12
Rosenthal 1931   59  0.4177  0.0066  0.0462  0.0419  0.4459  0.13
Rosenthal 1931b   65  0.3935  0.0077  0.0476  0.0418  0.4657  0.14
Rosenthal 1931c   48  0.4478  0.0053  0.0647  0.0615  0.5246  0.18
Rosenthal 1931d   61  0.4079  0.0073  0.0382  0.0317  0.4766  0.12
Rossi 2007   85  0.2480  0.0086  0.0464  0.0459  0.0582  0.04
Rubinstein 1939   38  0.4821  0.0034  0.0834  0.2722  0.4332  0.34
Rubinstein 1952   37  0.4811  0.0029  0.0729  0.3530  0.3631  0.35
Rubinstein 1966   9  0.5881  0.007  0.148  0.6817  0.648  0.66
Schilhawsky 1960   33  0.5082  0.0035  0.0833  0.3020  0.4928  0.38
Shebanova 2002   29  0.5036  0.0016  0.0915  0.516  0.6113  0.56
Smith 1975   36  0.4883  0.0047  0.0552  0.0525  0.4053  0.14
Sokolov 2002   35  0.4984  0.0042  0.0640  0.2019  0.4935  0.31
Sztompka 1959   69  0.3885  0.0044  0.0841  0.1929  0.4138  0.28
Tomsic 1995   62  0.4086  0.0078  0.0551  0.0567  0.0581  0.05
Uninsky 1932   84  0.2787  0.0060  0.0377  0.0335  0.2375  0.08
Uninsky 1971   21  0.5388  0.0011  0.1112  0.558  0.6312  0.59
Wasowski 1980   34  0.4937  0.0041  0.0743  0.1730  0.3642  0.25
Zak 1937   30  0.5038  0.0046  0.0548  0.0529  0.3955  0.14
Zak 1951   32  0.507  0.0050  0.0549  0.0533  0.2762  0.12
Average   3  0.7322  0.003  0.723  0.8812  0.683  0.77
Random 1   90  -0.1089  0.0091  0.0191  0.0170  0.0291  0.01
Random 2   89  0.0890  0.0089  0.0387  0.034  0.5064  0.12
Random 3   91  -0.1091  0.0090  0.0190  0.0168  0.0390  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).