Gierzod 1998

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   20  0.4349  0.0022  0.0816  0.489  0.6214  0.55
Anderszewski 2003   11  0.467  0.025  0.155  0.683  0.751  0.71
Ashkenazy 1981   39  0.3844  0.0050  0.0567  0.0544  0.1665  0.09
Bacha 2000   21  0.4325  0.0025  0.0919  0.443  0.7211  0.56
Badura 1965   33  0.3918  0.0028  0.0829  0.314  0.6622  0.45
Barbosa 1983   29  0.4162  0.0038  0.0831  0.2941  0.2038  0.24
Biret 1990   85  0.1874  0.0085  0.0381  0.0377  0.0388  0.03
Blet 2003   81  0.2245  0.0082  0.0386  0.0377  0.0384  0.03
Block 1995   55  0.3532  0.0030  0.0732  0.2828  0.3532  0.31
Blumental 1952   14  0.4427  0.0015  0.1615  0.5213  0.5815  0.55
Boshniakovich 1969   9  0.475  0.027  0.166  0.6611  0.638  0.64
Brailowsky 1960   19  0.4313  0.0118  0.1123  0.408  0.7116  0.53
Bunin 1987   73  0.2673  0.0078  0.0478  0.0485  0.0386  0.03
Bunin 1987b   74  0.2681  0.0077  0.0476  0.0479  0.0381  0.03
Chiu 1999   58  0.3369  0.0064  0.0655  0.0660  0.0574  0.05
Cohen 1997   68  0.3063  0.0071  0.0750  0.0733  0.4047  0.17
Cortot 1951   69  0.2975  0.0065  0.0474  0.0429  0.3060  0.11
Csalog 1996   75  0.2588  0.0076  0.0477  0.0474  0.0477  0.04
Czerny 1949   56  0.3561  0.0060  0.0562  0.0531  0.4550  0.15
Czerny 1990   61  0.3382  0.0052  0.0659  0.0656  0.0670  0.06
Duchoud 2007   84  0.1891  0.0087  0.0289  0.0275  0.0485  0.03
Ezaki 2006   4  0.5116  0.018  0.184  0.706  0.684  0.69
Falvay 1989   27  0.4236  0.0031  0.0735  0.2540  0.1739  0.21
Farrell 1958   83  0.2287  0.0080  0.0382  0.0373  0.0380  0.03
Ferenczy 1958   34  0.3919  0.0053  0.0561  0.0516  0.6845  0.18
Fliere 1977   16  0.4438  0.0014  0.1313  0.5434  0.3125  0.41
Fou 1978   6  0.496  0.0210  0.229  0.637  0.667  0.64
Francois 1956   80  0.2380  0.0081  0.0383  0.0360  0.0489  0.03
Friedman 1923   79  0.2378  0.0083  0.0387  0.0376  0.0490  0.03
Friedman 1923b   78  0.2371  0.0084  0.0380  0.0369  0.0487  0.03
Friedman 1930   70  0.2950  0.0070  0.0653  0.0662  0.0576  0.05
Garcia 2007   67  0.3026  0.0051  0.0658  0.0625  0.3551  0.14
Garcia 2007b   82  0.2258  0.0072  0.0471  0.0473  0.0478  0.04
Gierzod 1998   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Gornostaeva 1994   25  0.4254  0.0020  0.0918  0.4613  0.5918  0.52
Groot 1988   65  0.3079  0.0039  0.0641  0.1542  0.1153  0.13
Harasiewicz 1955   10  0.4711  0.0112  0.1712  0.6024  0.4320  0.51
Hatto 1993   23  0.4248  0.0027  0.0820  0.4430  0.2827  0.35
Hatto 1997   38  0.3951  0.0037  0.0733  0.2831  0.2633  0.27
Horowitz 1949   87  0.1889  0.0086  0.0385  0.0386  0.0382  0.03
Indjic 1988   31  0.4084  0.0035  0.0627  0.3431  0.3031  0.32
Kapell 1951   71  0.2985  0.0068  0.0570  0.0566  0.0575  0.05
Kissin 1993   22  0.4342  0.0034  0.0636  0.2431  0.4728  0.34
Kushner 1989   2  0.528  0.013  0.262  0.759  0.652  0.70
Luisada 1991   62  0.3233  0.0069  0.0568  0.0567  0.0572  0.05
Lushtak 2004   8  0.473  0.036  0.158  0.654  0.705  0.67
Malcuzynski 1961   5  0.504  0.034  0.343  0.724  0.683  0.70
Magaloff 1978   15  0.4412  0.0113  0.1114  0.5412  0.5317  0.53
Magin 1975   49  0.3764  0.0041  0.0643  0.1334  0.3241  0.20
Michalowski 1933   88  0.1665  0.0088  0.0384  0.0374  0.0383  0.03
Milkina 1970   41  0.3852  0.0043  0.0642  0.1339  0.2444  0.18
Mohovich 1999   3  0.512  0.122  0.2810  0.6213  0.619  0.61
Moravec 1969   42  0.3822  0.0045  0.0545  0.1043  0.1357  0.11
Morozova 2008   24  0.4215  0.0117  0.1221  0.4325  0.4324  0.43
Neighaus 1950   53  0.3557  0.0061  0.0660  0.0648  0.0671  0.06
Niedzielski 1931   64  0.3114  0.0157  0.0565  0.0531  0.2755  0.12
Ohlsson 1999   46  0.3790  0.0055  0.0752  0.0748  0.0669  0.06
Osinska 1989   17  0.4466  0.0029  0.0922  0.4029  0.3526  0.37
Pachmann 1927   59  0.3346  0.0067  0.0472  0.0442  0.1467  0.07
Paderewski 1930   72  0.2683  0.0073  0.0564  0.0541  0.2163  0.10
Perlemuter 1992   54  0.3556  0.0058  0.0563  0.0529  0.3352  0.13
Pierdomenico 2008   66  0.3021  0.0066  0.0475  0.0440  0.1366  0.07
Poblocka 1999   47  0.3730  0.0056  0.0946  0.0945  0.1261  0.10
Rabcewiczowa 1932   52  0.3667  0.0040  0.0640  0.1528  0.4236  0.25
Rachmaninoff 1923   86  0.1831  0.0079  0.0379  0.0370  0.0479  0.03
Rangell 2001   40  0.3823  0.0044  0.0644  0.1131  0.4140  0.21
Richter 1976   36  0.3959  0.0046  0.0566  0.0536  0.2756  0.12
Rosen 1989   13  0.4443  0.0026  0.0825  0.3823  0.3029  0.34
Rosenthal 1930   51  0.3629  0.0062  0.0748  0.0726  0.5543  0.20
Rosenthal 1931   18  0.4424  0.0016  0.1417  0.488  0.7510  0.60
Rosenthal 1931b   26  0.4234  0.0023  0.0826  0.357  0.7619  0.52
Rosenthal 1931c   28  0.419  0.0119  0.1224  0.3912  0.5821  0.48
Rosenthal 1931d   60  0.3370  0.0049  0.0749  0.0718  0.4746  0.18
Rossi 2007   76  0.2437  0.0075  0.0473  0.0427  0.3454  0.12
Rubinstein 1939   57  0.3440  0.0063  0.0747  0.0737  0.1562  0.10
Rubinstein 1952   37  0.3935  0.0032  0.0637  0.2236  0.3035  0.26
Rubinstein 1966   7  0.4820  0.009  0.1611  0.6218  0.5012  0.56
Schilhawsky 1960   45  0.3728  0.0059  0.0657  0.0622  0.3749  0.15
Shebanova 2002   30  0.4176  0.0036  0.0730  0.2940  0.2434  0.26
Smith 1975   35  0.3960  0.0033  0.0628  0.3210  0.6123  0.44
Sokolov 2002   48  0.3710  0.0148  0.0654  0.0626  0.4148  0.16
Sztompka 1959   50  0.3653  0.0042  0.0539  0.1640  0.2542  0.20
Tomsic 1995   44  0.3741  0.0021  0.0834  0.2616  0.4330  0.33
Uninsky 1932   63  0.3255  0.0024  0.0738  0.1926  0.3437  0.25
Uninsky 1971   12  0.4617  0.0011  0.247  0.657  0.666  0.65
Wasowski 1980   77  0.2477  0.0074  0.0656  0.0664  0.0573  0.05
Zak 1937   43  0.3839  0.0054  0.0751  0.0753  0.0568  0.06
Zak 1951   32  0.4047  0.0047  0.0569  0.0528  0.2558  0.11
Average   1  0.591  0.631  0.621  0.8528  0.3713  0.56
Random 1   91  -0.0368  0.0091  0.0191  0.0176  0.0291  0.01
Random 2   89  0.1072  0.0089  0.0288  0.022  0.5659  0.11
Random 3   90  0.0086  0.0090  0.0290  0.0211  0.4264  0.09

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).