Authors: Owen P. Hall Jr., Samuel L. Seaman
Addresses: The Graziadio School of Business and Management, Pepperdine University, Malibu, CA 90263, USA. ' The Graziadio School of Business and Management, Pepperdine University, Malibu, CA 90263, USA
Abstract: With an annual payroll of more than US$2 billion, major league baseball is big business. That being the case, it is not surprising that baseball|s general managers are looking for ways to improve organisational performance. Neural networks have seen growing use in a variety of management applications, including finance, marketing, and operations. The purpose of this paper is to show how neural networks can be used to forecast individual and team outcomes as a means to help management improve overall organisational performance. The analytical paradigm described in this paper consists of a three-tiered hierarchical design that combines a number of specific on-field and off-field factors in predicting team performance. The results reveal that the developed model estimated the Runs Scored (RS) and the Runs Against (RA) within 5% of the actual performance over a five-year period. The paper also discusses some of the economic implications of implementing changes in the overall team structure.
Keywords: organisational management; professional baseball; neural networks; hierarchical models; winning teams; organisational performance; sport management; team structure.
International Journal of Sport Management and Marketing, 2009 Vol.5 No.3, pp.277 - 294
Published online: 15 Feb 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article