Identifying consistent and unique aspects of performances is an important aspect of modeling performance style. This paper presents a detailed analysis of inter-singer differences and intra-singer similarities using support vector machines to predict singer identity of a performance from pitch, timing, and dynamics performance parameters. The analysis was performed on a dataset of 72 recordings of the first verse of Schubert's "Ave Maria", the dataset consists of 3 a cappella and 3 accompanied performances by 6 professional and 6 non-professional singers.