Gierzod 1998

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   16  0.348  0.0315  0.1514  0.6418  0.5114  0.57
Anderszewski 2003   8  0.3914  0.018  0.167  0.732  0.744  0.73
Ashkenazy 1981   30  0.2553  0.0032  0.1023  0.4658  0.0632  0.17
Bacha 2000   1  0.492  0.212  0.261  0.841  0.822  0.83
Badura 1965   13  0.365  0.0613  0.1517  0.623  0.6910  0.65
Barbosa 1983   43  0.2087  0.0057  0.0655  0.0657  0.0562  0.05
Biret 1990   91  -0.1888  0.0091  0.0191  0.0191  0.0191  0.01
Blet 2003   79  0.0121  0.0080  0.0287  0.0275  0.0388  0.02
Block 1995   18  0.3224  0.0018  0.1216  0.6235  0.3518  0.47
Blumental 1952   15  0.3535  0.0014  0.1511  0.6812  0.5812  0.63
Boshniakovich 1969   23  0.3131  0.0021  0.1619  0.5742  0.1626  0.30
Brailowsky 1960   9  0.399  0.0211  0.1612  0.666  0.687  0.67
Bunin 1987   76  0.0773  0.0079  0.0285  0.0280  0.0390  0.02
Bunin 1987b   74  0.0744  0.0078  0.0283  0.0279  0.0385  0.02
Chiu 1999   65  0.1562  0.0066  0.0560  0.0575  0.0469  0.04
Cohen 1997   45  0.2063  0.0046  0.0562  0.0537  0.3439  0.13
Cortot 1951   17  0.3236  0.0025  0.0822  0.5120  0.5316  0.52
Csalog 1996   88  -0.0379  0.0089  0.0288  0.0287  0.0287  0.02
Czerny 1949   75  0.0764  0.0073  0.0467  0.0453  0.0664  0.05
Czerny 1990   84  0.0080  0.0082  0.0373  0.0376  0.0379  0.03
Duchoud 2007   86  -0.0189  0.0083  0.0279  0.0287  0.0289  0.02
Ezaki 2006   6  0.4217  0.0010  0.188  0.7223  0.598  0.65
Falvay 1989   53  0.1839  0.0058  0.0652  0.0675  0.0370  0.04
Farrell 1958   78  0.0228  0.0074  0.0376  0.0389  0.0184  0.02
Ferenczy 1958   25  0.2915  0.0137  0.0637  0.2521  0.7121  0.42
Fliere 1977   37  0.2216  0.0140  0.0835  0.2676  0.0441  0.10
Fou 1978   12  0.3612  0.0116  0.1715  0.6423  0.4215  0.52
Francois 1956   77  0.0360  0.0076  0.0278  0.0266  0.0480  0.03
Friedman 1923   64  0.1561  0.0068  0.0470  0.0466  0.0575  0.04
Friedman 1923b   67  0.1365  0.0071  0.0469  0.0472  0.0474  0.04
Friedman 1930   61  0.1554  0.0065  0.0561  0.0568  0.0473  0.04
Garcia 2007   57  0.1725  0.0029  0.0733  0.2940  0.2329  0.26
Garcia 2007b   87  -0.0255  0.0081  0.0280  0.0263  0.0581  0.03
Gierzod 1998   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Gornostaeva 1994   31  0.2534  0.0027  0.0828  0.4027  0.4522  0.42
Groot 1988   54  0.1719  0.0031  0.0934  0.2770  0.0540  0.12
Harasiewicz 1955   36  0.2356  0.0048  0.0563  0.0557  0.0565  0.05
Hatto 1993   41  0.2167  0.0051  0.0848  0.0859  0.0750  0.07
Hatto 1997   66  0.1374  0.0061  0.0653  0.0666  0.0463  0.05
Horowitz 1949   83  0.0047  0.0085  0.0284  0.0283  0.0386  0.02
Indjic 1988   60  0.1690  0.0056  0.0564  0.0561  0.0661  0.05
Kapell 1951   85  0.0091  0.0086  0.0286  0.0277  0.0476  0.03
Kissin 1993   42  0.2133  0.0054  0.0847  0.0855  0.0748  0.07
Kushner 1989   7  0.4129  0.009  0.179  0.7213  0.589  0.65
Luisada 1991   71  0.0940  0.0072  0.0374  0.0367  0.0566  0.04
Lushtak 2004   11  0.3711  0.0112  0.1513  0.659  0.5913  0.62
Malcuzynski 1961   4  0.464  0.094  0.355  0.7710  0.606  0.68
Magaloff 1978   20  0.3145  0.0020  0.1721  0.5433  0.3619  0.44
Magin 1975   68  0.1281  0.0063  0.0656  0.0658  0.0651  0.06
Michalowski 1933   73  0.0768  0.0075  0.0375  0.0375  0.0477  0.03
Milkina 1970   70  0.1082  0.0069  0.0472  0.0458  0.0572  0.04
Mohovich 1999   2  0.483  0.163  0.264  0.789  0.645  0.71
Moravec 1969   49  0.1913  0.0150  0.0654  0.0672  0.0457  0.05
Morozova 2008   19  0.3123  0.0017  0.1424  0.4449  0.0634  0.16
Neighaus 1950   34  0.2369  0.0042  0.0840  0.2067  0.0445  0.09
Niedzielski 1931   27  0.2641  0.0034  0.1031  0.3748  0.0733  0.16
Ohlsson 1999   44  0.2083  0.0053  0.0749  0.0783  0.0360  0.05
Osinska 1989   62  0.1584  0.0064  0.0566  0.0565  0.0467  0.04
Pachmann 1927   35  0.2375  0.0044  0.0743  0.1570  0.0543  0.09
Paderewski 1930   47  0.2085  0.0052  0.0846  0.0867  0.0553  0.06
Perlemuter 1992   32  0.2542  0.0033  0.1129  0.4041  0.2725  0.33
Pierdomenico 2008   72  0.0918  0.0070  0.0468  0.0468  0.0471  0.04
Poblocka 1999   58  0.1750  0.0038  0.0642  0.1773  0.0446  0.08
Rabcewiczowa 1932   40  0.2166  0.0043  0.0744  0.1434  0.3330  0.21
Rachmaninoff 1923   89  -0.0532  0.0084  0.0282  0.0287  0.0283  0.02
Rangell 2001   33  0.2330  0.0041  0.0839  0.2167  0.0542  0.10
Richter 1976   50  0.1951  0.0060  0.0565  0.0557  0.0659  0.05
Rosen 1989   26  0.2770  0.0028  0.0827  0.4260  0.0438  0.13
Rosenthal 1930   29  0.266  0.0323  0.0926  0.4323  0.4420  0.43
Rosenthal 1931   3  0.471  0.231  0.232  0.824  0.861  0.84
Rosenthal 1931b   5  0.457  0.035  0.323  0.805  0.843  0.82
Rosenthal 1931c   14  0.3620  0.007  0.1510  0.6811  0.6311  0.65
Rosenthal 1931d   24  0.2957  0.0026  0.0825  0.4313  0.5517  0.49
Rossi 2007   80  0.0058  0.0077  0.0377  0.0353  0.0568  0.04
Rubinstein 1939   51  0.1938  0.0035  0.1138  0.2353  0.0737  0.13
Rubinstein 1952   52  0.1859  0.0047  0.0750  0.0754  0.0556  0.06
Rubinstein 1966   22  0.3137  0.0022  0.1220  0.5740  0.1328  0.27
Schilhawsky 1960   56  0.1722  0.0059  0.0657  0.0648  0.0655  0.06
Shebanova 2002   28  0.2676  0.0039  0.0736  0.2653  0.0835  0.14
Smith 1975   39  0.2246  0.0030  0.0830  0.4029  0.4023  0.40
Sokolov 2002   46  0.2026  0.0036  0.0841  0.1866  0.0347  0.07
Sztompka 1959   59  0.1677  0.0049  0.0751  0.0760  0.0654  0.06
Tomsic 1995   38  0.2243  0.0024  0.0832  0.3632  0.2127  0.27
Uninsky 1932   55  0.1771  0.0045  0.0645  0.1174  0.0449  0.07
Uninsky 1971   21  0.3127  0.0019  0.1318  0.6232  0.2624  0.40
Wasowski 1980   90  -0.1086  0.0090  0.0289  0.0285  0.0282  0.02
Zak 1937   63  0.1572  0.0062  0.0659  0.0667  0.0558  0.05
Zak 1951   48  0.2048  0.0055  0.0658  0.0648  0.0752  0.06
Average   10  0.3710  0.026  0.176  0.7572  0.0431  0.17
Random 1   81  0.0078  0.0088  0.0290  0.0264  0.0478  0.03
Random 2   69  0.1252  0.0067  0.0471  0.0410  0.4836  0.14
Random 3   82  0.0049  0.0087  0.0281  0.0218  0.3944  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).