Gel-based matrix-assisted laser desorption ionization-time of flight tandem mass spectrometer (MALDI TOF/TOF MS) is one of the dominant methods of current proteomics, utilizing both peptide mass fingerprinting (PMF) and peptide fragment fingerprinting (PFF) for protein identification on a spot-to-spot basis. However, the unique impact of the quality of the corresponding mass spectrometry spectra remains largely unreported, and has motivated the development and use of an automatic spectra-assessment method. In this study, a multi-variant regression approach has been utilized to assess spectral quality for both PMF and PFF spectra obtained from MALDI TOF/TOF MS. The assessment index has been applied to investigations of MASCOT search results. Systematic examination of two large-scale sets of human liver tissue data has proved that spectral quality was a key factor in significant matching. Based on large-scale investigations on individual PMF search, individual PFF search and their combination, respectively, the filtering of bad quality spectra or spots proves to be an efficient way to improve search efficiency of all search modes in MASCOT. Meanwhile, a validation method based on score differences between normal and decoy (reverse or random) database searches is proposed to precisely define the positive matches. Further analysis showed that spectral quality assessment was also efficient in representing the quality of 2-DE gel spots and promoted the discovery of potential post-translation modifications.