Quantitative shotgun proteomics is dependent on the detection, identification, and quantitative analysis of peptides. An issue arises with peptides that are shared between multiple proteins. What protein did they originate from and how should these shared peptides be used in a quantitative proteomics workflow? To systematically evaluate shared peptides in label-free quantitative proteomics, we devised a well-defined protein sample consisting of known concentrations of six albumins from different species, which we added to a highly complex yeast lysate. We used the spectral counts based normalized spectral abundance factor (NSAF) as the starting point for our analysis and compared an exhaustive list of possible combinations of parameters to determine what was the optimal approach for dealing with shared peptides and shared spectral counts. We showed that distributing shared spectral counts based on the number of unique spectral counts led to the most accurate and reproducible results.