The primary objective of this paper is to devise a ranking system for individual test batsmen (from different eras) considering all possible factors like the difficulty of opposition bowlers, the batsman’s consistency, the contribution of the batsman in the success of his team, the era in which he played, etc. Due to the presence of such numerous factors—each one of them having a significance of its own, it is imperative that a multivariate statistical approach is employed in the ranking of Test batsmen. A total of eight factors were zeroed in on which were thought to influence the performance of a batsman. An index was developed for each of the eight factors, and thus each of the batsmen got eight different scores for the eight different factors. Consequently, the eight scores of the batsman act as the coordinates of a point/cluster in an eight-dimensional plane. In this way, each of the batsmen under study is represented by a point in an eight-dimensional plane. Finally, to determine the most exceptional batsmen among the batsmen under study, the concept of multivariate statistical outlier detection using Mahalanobis distances was used. However, the concept of Outlier Detection only gives us an idea of the most exceptional batsmen when compared to the others. In order to determine the best batsmen, the process of outlier detection is followed up with the determination of the efficiencies of each of the batsmen under study. The efficiencies of the batsmen are calculated by adopting the approach of Data Envelopment Analysis (DEA), wherein each batsman is likened to a machine or a Decision-Making Unit (DMU). The higher the efficiency of a batsman, the greater his success in converting low inputs (difficult input parameters) to high outputs.