A benchmark approach for baseball evaluation

This research proposes a new analytical approach for baseball evaluation, referred to as ‚A Benchmark Approach’ by combining Data Envelopment Analysis (DEA) with Offensive Earned-Run Average (OERA). An important feature of the proposed approach is that it can select a best performer among many baseball players and their ranking scores. The DEA is an evaluation technique of various entities in public and private sectors, whose production activities are characterized by multiple inputs and outputs. The DEA technique has a shortcoming in evaluating baseball performance because it produces many efficient baseball players. To overcome such a shortcoming of DEA baseball evaluation, this research extends an original DEA model to a Slack-Adjusted DEA model and then proposes a new use of its combination with OERA. As a real application, this work applies the benchmark approach for the evaluation of offensive records of Japanese baseball players to obtain their ranking scores.