Optimizing baseball defensive alignments through integer programming and simulation. (3rd April 2017)

• Record Type: Journal Article
• Authors: Easton, Todd; Becker, Kyle
• Is Part Of: International journal of modelling & simulation. Volume 37:Number 2(2017)
• Page Start: 82
• Page End: 87
• Publication Date: 2017-04-03
• Subjects: Baseball -- integer programming -- simulation; Mathematical models -- Periodicals; Simulation methods -- Periodicals; Mathematical models; Simulation methods; Periodicals; 003.3
• DOI: 10.1080/02286203.2016.1243950
• Languages: English
• ISSNs: 0228-6203

Abstract

Abstract: Baseball is an incredibly complex game in which the manager makes numerous difficult decisions. This paper describes a stochastic integer program that determines the best defensive starting positions to minimize the expected batting average of a particular player. To test this optimal defense against other standard Major League Baseball ® defenses, a simulation is created. A computational study demonstrates how the optimal defense can be used to decrease Derek Jeter's batting average in a statistically significant manner.