A central decision-maker, the principal, employs performance evaluation criteria consistent with an organization's overall goal(s) to measure the effectiveness of the agents who execute decisions and implement strategies within a specified period. The dataset of performance criteria spanning the performance space will change over time to reflect the principal's strategic modifications. This paper applies a Data Envelopment Analysis (DEA) based approach to reveals the dynamics of the performance space of Major League Baseball (MLB) pitchers with minimum subjective judgment imposed on the data. The proposed approach is applied to data on MLB pitchers from 1871 to 2006. We conclude that many of the findings are consistent with the observations of baseball's experts. The approach also suggests new directions for investigating a large dataset to identify revealed preferences or strategies by using historical and modern observations.