Baseball Analytics : Further Modeling

Abstract

Color poster with text, images, charts, and graphs.Baseball has long served as a frontrunner for the integration of analytics with application, connected in part to the consistency of historical statistics as well as the widespread interest in the national professional and more local semi-professional sport leagues. This project builds on prior data-exploration and data-gathering for the local Northwoods League, with recognition of a reduced set of available technical information (as compared to MLB). The intention is to create a WAR calculation for the league using the available data. The original WAR statistic in the MLB uses data that is unattainable for the NWL. Therefore, this project attempts to modify the WAR statistic with reasonable substitutes to make it accessible for the NWL. The two primary focuses of the current project are modeling and coding generalization. Coding generalization summarizes the structure of the available data organization as well as discusses functions written to compute necessary inputs for the metrics, including different portions of the WAR analogy. With the adjustments and additional back-computations of metrics for individual players, we now have sufficient available information for modeling these player utilities. We summarize the modeling results found by connecting information about: player-by-game appearance, season-break information, refined player utility estimates, and use of reconfigured statistics.University of Wisconsin--Eau Claire Office of Research and Sponsored Program