Frontiers in Major League Baseball

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 performance of team managers using recent MLB data. Using DEA, free agent salary arbitration is analyzed and the book updates the data to provide current estimates. Another interesting application addresses technology changes across time. In baseball, we have observed differences in offensive production at various points in time. Some explanations given include the "juiced ball" era and steroid use. Using DEA, productivity shifts at different points in time are indentified. A hybrid DEA model, which considers only outcomes and not inputs, to rank order players based on multiple attributes is developed to identify a ranking of player quality for a given season and across time. A final summarizing chapter highlights the management and policy implications of the model. 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 baseball as well as other sports or production processes.