Indjic 1988

Performance0-Rank  0-Score1-Rank  1-Score2-Rank  2-Score3-Rank  3-Score3R-Rank  3R-Score4-Rank  4-Score  NED
Afanassiev 2001   51  0.3258  0.0033  0.0936  0.2731  0.3536  0.31
Anderszewski 2003   64  0.2359  0.0062  0.0568  0.0538  0.1852  0.09
Ashkenazy 1981   3  0.6815  0.003  0.373  0.884  0.873  0.87
Bacha 2000   26  0.413  0.0031  0.0928  0.376  0.6525  0.49
Badura 1965   66  0.2128  0.0069  0.0569  0.0575  0.0374  0.04
Barbosa 1983   20  0.4718  0.0013  0.1112  0.633  0.7312  0.68
Biret 1990   59  0.2560  0.0068  0.0570  0.0546  0.0959  0.07
Blet 2003   19  0.4761  0.0015  0.1024  0.5415  0.6021  0.57
Block 1995   54  0.2962  0.0052  0.0948  0.0948  0.0656  0.07
Blumental 1952   23  0.4629  0.0024  0.1022  0.565  0.7217  0.63
Boshniakovich 1969   57  0.2612  0.0049  0.0851  0.0859  0.0658  0.07
Brailowsky 1960   88  0.0016  0.0088  0.0289  0.0286  0.0387  0.02
Bunin 1987   49  0.3341  0.0025  0.1030  0.3518  0.5329  0.43
Bunin 1987b   48  0.3342  0.0028  0.1132  0.3418  0.5130  0.42
Chiu 1999   12  0.5063  0.0016  0.1211  0.6418  0.6316  0.63
Cohen 1997   72  0.1664  0.0079  0.0477  0.0477  0.0283  0.03
Cortot 1951   79  0.0965  0.0085  0.0384  0.0386  0.0289  0.02
Csalog 1996   65  0.2230  0.0067  0.0853  0.0876  0.0462  0.06
Czerny 1949   83  0.0766  0.0087  0.0383  0.0370  0.0481  0.03
Czerny 1990   17  0.4843  0.0020  0.1117  0.5915  0.7514  0.67
Duchoud 2007   27  0.4119  0.0029  0.1033  0.3228  0.3934  0.35
Ezaki 2006   74  0.1567  0.0075  0.0662  0.0668  0.0465  0.05
Falvay 1989   34  0.404  0.0042  0.0742  0.2016  0.4338  0.29
Farrell 1958   81  0.0844  0.0080  0.0478  0.0484  0.0278  0.03
Ferenczy 1958   89  -0.0120  0.0089  0.0287  0.0269  0.0480  0.03
Fliere 1977   32  0.4031  0.0037  0.0734  0.3147  0.1044  0.18
Fou 1978   41  0.3568  0.0051  0.0852  0.0858  0.0561  0.06
Francois 1956   70  0.1945  0.0070  0.0571  0.0549  0.0670  0.05
Friedman 1923   52  0.3069  0.0058  0.0756  0.0750  0.0955  0.08
Friedman 1923b   53  0.3032  0.0057  0.0664  0.0648  0.1154  0.08
Friedman 1930   21  0.4670  0.0022  0.1123  0.5516  0.6220  0.58
Garcia 2007   50  0.3371  0.0036  0.0737  0.2630  0.3837  0.31
Garcia 2007b   18  0.4833  0.008  0.2210  0.653  0.798  0.72
Gierzod 1998   73  0.1672  0.0056  0.0661  0.0664  0.0568  0.05
Gornostaeva 1994   78  0.1373  0.0077  0.0476  0.0473  0.0384  0.03
Groot 1988   9  0.5234  0.0011  0.168  0.719  0.699  0.70
Harasiewicz 1955   35  0.3974  0.0047  0.0757  0.0754  0.0664  0.06
Hatto 1993   1  0.961  0.991  0.981  0.991  0.991  0.99
Hatto 1997   2  0.832  0.002  0.872  0.961  0.962  0.96
Horowitz 1949   31  0.4075  0.0030  0.0729  0.3621  0.5528  0.44
Indjic 1988   target  targettarget  targettarget  targettarget  targettarget  targettarget  target
Kapell 1951   8  0.5676  0.009  0.199  0.703  0.757  0.72
Kissin 1993   13  0.4946  0.0019  0.1513  0.6312  0.7511  0.69
Kushner 1989   25  0.4277  0.0041  0.0743  0.2027  0.4239  0.29
Luisada 1991   6  0.5847  0.004  0.346  0.784  0.805  0.79
Lushtak 2004   77  0.1323  0.0076  0.0479  0.0485  0.0282  0.03
Malcuzynski 1961   29  0.4048  0.0032  0.0826  0.4122  0.4727  0.44
Magaloff 1978   69  0.1978  0.0061  0.0667  0.0679  0.0372  0.04
Magin 1975   5  0.588  0.007  0.365  0.812  0.874  0.84
Michalowski 1933   24  0.4579  0.0021  0.1021  0.565  0.6718  0.61
Milkina 1970   38  0.3835  0.0044  0.0940  0.2114  0.5732  0.35
Mohovich 1999   60  0.2413  0.0050  0.0849  0.0844  0.1649  0.11
Moravec 1969   44  0.3449  0.0046  0.0660  0.0629  0.2848  0.13
Morozova 2008   40  0.376  0.0035  0.1031  0.3536  0.2040  0.26
Neighaus 1950   30  0.4017  0.0043  0.0739  0.2244  0.1247  0.16
Niedzielski 1931   15  0.4836  0.0012  0.1114  0.637  0.6515  0.64
Ohlsson 1999   33  0.4010  0.0026  0.0927  0.3930  0.3133  0.35
Osinska 1989   75  0.1424  0.0073  0.0573  0.0581  0.0371  0.04
Pachmann 1927   55  0.2850  0.0053  0.1047  0.1053  0.0753  0.08
Paderewski 1930   16  0.4825  0.0010  0.1416  0.616  0.7313  0.67
Perlemuter 1992   58  0.2526  0.0065  0.0658  0.0659  0.0466  0.05
Pierdomenico 2008   42  0.3580  0.0039  0.0744  0.1919  0.4935  0.31
Poblocka 1999   67  0.2137  0.0066  0.0854  0.0872  0.0460  0.06
Rabcewiczowa 1932   80  0.0981  0.0084  0.0385  0.0369  0.0477  0.03
Rachmaninoff 1923   56  0.279  0.0059  0.0666  0.0650  0.0567  0.05
Rangell 2001   76  0.1482  0.0071  0.0572  0.0579  0.0376  0.04
Richter 1976   11  0.5051  0.0017  0.1015  0.6320  0.7510  0.69
Rosen 1989   61  0.2327  0.0063  0.0663  0.0686  0.0375  0.04
Rosenthal 1930   63  0.2352  0.0060  0.0659  0.0659  0.0569  0.05
Rosenthal 1931   82  0.0783  0.0081  0.0380  0.0373  0.0379  0.03
Rosenthal 1931b   84  0.0784  0.0082  0.0381  0.0382  0.0290  0.02
Rosenthal 1931c   71  0.1785  0.0072  0.0474  0.0479  0.0286  0.03
Rosenthal 1931d   86  0.0586  0.0078  0.0382  0.0377  0.0385  0.03
Rossi 2007   91  -0.1287  0.0091  0.0191  0.0191  0.0191  0.01
Rubinstein 1939   43  0.3414  0.0045  0.0745  0.1322  0.3043  0.20
Rubinstein 1952   37  0.3921  0.0038  0.0735  0.2919  0.5131  0.38
Rubinstein 1966   39  0.3753  0.0040  0.0741  0.2027  0.2742  0.23
Schilhawsky 1960   62  0.2354  0.0064  0.0665  0.0641  0.1751  0.10
Shebanova 2002   7  0.5722  0.005  0.247  0.7613  0.736  0.74
Smith 1975   68  0.2088  0.0074  0.0475  0.0461  0.0573  0.04
Sokolov 2002   36  0.3955  0.0048  0.0755  0.0720  0.4445  0.18
Sztompka 1959   28  0.4089  0.0027  0.0925  0.5027  0.4126  0.45
Tomsic 1995   22  0.467  0.0023  0.1520  0.574  0.6019  0.58
Uninsky 1932   10  0.5238  0.0018  0.1118  0.5815  0.5423  0.56
Uninsky 1971   45  0.345  0.0034  0.0738  0.2533  0.2541  0.25
Wasowski 1980   14  0.4939  0.0014  0.1019  0.5822  0.5522  0.56
Zak 1937   46  0.3356  0.0054  0.0850  0.0842  0.1350  0.10
Zak 1951   47  0.3357  0.0055  0.1346  0.1337  0.2546  0.18
Average   4  0.6111  0.006  0.214  0.8326  0.3624  0.55
Random 1   87  0.0440  0.0083  0.0288  0.0227  0.2757  0.07
Random 2   85  0.0690  0.0086  0.0286  0.0236  0.1763  0.06
Random 3   90  -0.0591  0.0090  0.0190  0.0171  0.0388  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).