This book focuses on the application of Data Envelopment Analysis (DEA) to Major League
Baseball (MLB). DEA is a nonparametric linear programming model that is used across academic
disciplines. In sports economics authors have applied the technique primarily to assess team
and or managerial efficiency. The basis for performance analysis is economic production theory
where it is assumed that baseball can be viewed as a production process whereby inputs (player
quality measures) are transformed into outputs (wins attendance). The primary advantage that
DEA has over more traditional regression based approaches is the ability to handle multiple
inputs and multiple outputs. Further the approach is nonparametric and hence does not require
a priori specification of the production function. The book develops the theory of DEA in the
context of a production environment. A focal point is the assessment of technical and cost
efficiency of MLB teams. It is shown that previous frontier applications that measure
efficiency provide biased results given that the outcome of a game is zero-sum. If a team loses
a game due to inefficiency another team wins a lost game. A corrected frontier is presented to
overcome this problem. Free agent salary arbitration is analyzed using a dual DEA model. Each
free agent's contract zone is identified. The upper and lower bounds representing the player's
and team's perspective of value respectively are estimated. Player performance is estimated
using a modified DEA model to rank order players based on multiple attributes. This model will
be used to evaluate current Hall of Fame players. We provide arguments for other players who
are deserving of membership. We also use our measure of performance and evaluate
age-performance profilers for many ball players. Regression analysis is used to identify the
age of peak performance. The method is used to evaluate some of the all-time greats. We also
use the method to analyze admitted and implicated steroid users. The results clearly show that
performance was enhanced. This book will provide appropriate theoretical models with
methodological considerations and interesting empirical analyses and is intended to serve
academics and practitioners interested in applying DEA to baseball as well as other sports or
production processes. >
