We have analyzed sequence covariation in an alignment of 266 non-redundant SH3 domain sequences using chi-squared statistical methods. Artifactual covariations arising from close evolultionary relationships among certain sequence subgroups were eliminated using empirically derived sequence diversity thresholds. This covariation detection method was able to predict residue-residue contacts (side-chain centres of mass within 8 Å) in the structure of the SH3 domain with an accuracy of 85 %, which is greater than that achieved in many previous covariation studies. In examining the positions involved most frequently in covariations, we discovered a dramatic over-representation of a subset of five hydrophobic core positions. This covariation information was used to design second and third site substitutions that could compensate for highly destabilizing hydrophobic core substitutions in the Fyn SH3 domain, thus providing experimental data to validate the covariation analysis. The testing of our covariation detection method on 15 other alignments showed that the accuracy of contact prediction is highly variable depending on which sequence alignment is used, and useful levels of prediction accuracy were obtained with only approximately one-third of alignments. The results presented here provide insight into the difficulties inherent in covariation analysis, and suggest that it may have limited usefulness in tertiary structure prediction. On the other hand, our ability to use covariation analysis to design stabilizing combinations of hydrophobic core substitutions attests to its potential utility for gaining deeper insight into the stability determinants and functional mechanisms of proteins with known three-dimensional structures.