The energy parametrization of geometrically simplified versions of polypeptides, better known as polypeptide or protein coarse-grained models, is obtained from molecular dynamics and statistical methods. Residue pairwise interactions are derived by performing atomic-level simulations in explicit water for all 210 pairs of amino acids, where the amino acids are modified to closer match their structure and charges in polypeptides. Radial density functions are computed from equilibrium simulations for each pair of residues, from which statistical energies are extracted using the Boltzmann inversion method. The resulting models are compared to similar potentials obtained by knowledge based methods and to hydrophobic scales, resulting in significant similarities in spite of the model simplicity. However, it was found that glutamine, asparagine, lysine, and arginine are more attractive to other residues than anticipated, in part, due to their amphiphilic nature. In addition, equally charged residues appear more repulsive than expected. Difficulties in the calculation of knowledge based potentials and hydrophobicity scale for these cases, as well as sensitivity of the force field to polarization effects are suspected to cause this discrepancy. It is also shown that the coarse-grained model can identify native structures in decoy databases nearly as well as more elaborate knowledge based methods, in spite of its resolution limitations. In a test conducted with several proteins and corresponding decoys, the coarse-grained potential was able to identify the native state structure but not the original atomic force field.