Shebanova 2002

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Ashkenazy 1981   10  0.947  0.0213  0.1311  0.4221  0.2113  0.30
Bacha 1997   38  0.8920  0.0042  0.0831  0.0835  0.0940  0.08
Barbosa 1983   1  0.971  0.471  0.461  0.751  0.801  0.77
Biret 1990   40  0.8826  0.0043  0.0828  0.0831  0.1038  0.09
Block 1995   45  0.8646  0.0039  0.0549  0.0518  0.2634  0.11
Brailowsky 1960   13  0.9411  0.0112  0.1212  0.3713  0.4810  0.42
Chiu 1999   29  0.9136  0.0038  0.0735  0.0737  0.0651  0.06
Clidat 1994   9  0.953  0.104  0.197  0.539  0.378  0.44
Cohen 1997   25  0.9117  0.0033  0.0834  0.0823  0.2028  0.13
Cortot 1951   44  0.8632  0.0045  0.0547  0.0529  0.1242  0.08
Csalog 1996   30  0.9116  0.0131  0.0642  0.0632  0.1043  0.08
Czerny 1990   16  0.9325  0.0014  0.1213  0.3618  0.2712  0.31
Ezaki 2006   2  0.979  0.012  0.243  0.604  0.596  0.59
Ferenczy 1958   15  0.9338  0.0020  0.0820  0.2316  0.2815  0.25
Fliere 1977   5  0.964  0.038  0.149  0.496  0.527  0.50
Fou 1978   7  0.9510  0.019  0.166  0.572  0.713  0.64
Francois 1956   32  0.9112  0.0137  0.0640  0.0630  0.1244  0.08
Grinberg 1951   37  0.8947  0.0044  0.0830  0.0830  0.1137  0.09
Hatto 1993   23  0.9214  0.0123  0.1121  0.2035  0.0930  0.13
Hatto 1997   27  0.9148  0.0024  0.0922  0.1835  0.0831  0.12
Indjic 2001   28  0.9140  0.0025  0.0924  0.1836  0.0833  0.12
Jonas 1947   21  0.9223  0.0016  0.0914  0.3537  0.0824  0.17
Kapell 1951   20  0.9215  0.0122  0.0823  0.1828  0.1127  0.14
Kiepura 1999   24  0.9218  0.0015  0.1118  0.301  0.619  0.43
Kushner 1989   42  0.8744  0.0046  0.0736  0.0735  0.0847  0.07
Luisada 1991   35  0.9050  0.0036  0.0546  0.0538  0.0850  0.06
Lushtak 2004   39  0.8945  0.0041  0.0643  0.0641  0.0552  0.05
Magaloff 1978   31  0.9133  0.0034  0.0833  0.0810  0.4321  0.19
Meguri 1997   33  0.9141  0.0029  0.0829  0.0829  0.1139  0.09
Milkina 1970   17  0.9328  0.0026  0.1226  0.128  0.4918  0.24
Mohovich 1999   22  0.9242  0.007  0.1917  0.3124  0.1917  0.24
Niedzielski 1931   43  0.8627  0.0035  0.0548  0.0529  0.0945  0.07
Ohlsson 1999   18  0.9322  0.0028  0.0832  0.0821  0.2029  0.13
Olejniczak 1990   8  0.9543  0.0010  0.1310  0.4417  0.3711  0.40
Osinska 1989   3  0.972  0.183  0.282  0.711  0.802  0.75
Rangell 2001   46  0.8352  0.0047  0.0641  0.0632  0.0948  0.07
Richter 1976   6  0.965  0.036  0.204  0.592  0.644  0.61
Rubinstein 1938   47  0.8251  0.0040  0.0545  0.0524  0.2036  0.10
Rubinstein 1952   41  0.886  0.0330  0.0738  0.074  0.5820  0.20
Rubinstein 1961   49  0.7839  0.0049  0.0737  0.0723  0.4125  0.17
Rubinstein 1966   48  0.7821  0.0048  0.0644  0.0618  0.4426  0.16
Shebanova 2002   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Smidowicz 1948   12  0.9429  0.0017  0.1015  0.3132  0.1023  0.18
Smidowicz 1948b   14  0.9430  0.0018  0.1516  0.3132  0.1022  0.18
Smith 1975   36  0.908  0.0227  0.0927  0.091  0.6716  0.25
Sofronitsky 1949   34  0.9019  0.0021  0.0725  0.1531  0.0932  0.12
Sztompka 1959   4  0.9613  0.015  0.265  0.582  0.645  0.61
Tomsic 1995   11  0.9437  0.0011  0.178  0.5023  0.1814  0.30
Uninsky 1971   26  0.9131  0.0032  0.0739  0.0733  0.0749  0.07
Wasowski 1980   19  0.9224  0.0019  0.1119  0.2822  0.1719  0.22
Random 1   51  0.0134  0.0050  0.0251  0.029  0.2646  0.07
Random 2   52  -0.0735  0.0052  0.0252  0.0210  0.3441  0.08
Random 3   50  0.0649  0.0051  0.0350  0.038  0.3735  0.11

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).