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Frontiers in Major League Baseball - Nonparametric Analysis of Performance Using Data Envelopment Analysis (Paperback, 2011 ed.)
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Frontiers in Major League Baseball - Nonparametric Analysis of Performance Using Data Envelopment Analysis (Paperback, 2011 ed.)
Series: Sports Economics, Management and Policy, 1
Expected to ship within 10 - 15 working days
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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. >
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