Table 1. *Redundancy*, *phenotype bias* and *components* in Polyomino, RNA and HP GP maps. Comparing the number of phenotypes (*N*_{P}) to the number of genotypes (*N*_{G}) for each GP map highlights large-scale redundancy present. Phenotype bias is demonstrated in each map with the measure of the fraction of phenotypes that covers 95% of the genotypes (*N*_{cov} is the number of phenotypes that covers the 95% of genotypes). In all cases the fraction of phenotypes is significantly smaller than the fraction of genotypes being covered, indicating the presence of a strong phenotype bias. The final column is the total number of genotype components (*N*_{C}) in each GP map. In all cases (non-computable values left out), the number of components is larger than the number of phenotypes, indicating phenotypes tend to be spread out over multiple disconnected components. RNA data for *L* = 12 were computed from the Vienna package [22] and taken from [41] for *L* = 15, 20. The value of *N*_{p} for the Polyomino *S*_{4,16} GP map is approximate as it is found from large-scale sampling of the GP map over multiple runs of the algorithm presented in [42]. All other Polyomino results were found by exhaustive enumeration. The HP results were calculated from the data made available by Irbäck & Troein [36]. Non-deterministic phenotypes and the trivial structure in RNA are excluded from the statistics.