Equitable handicapping of scramble golf tournaments

Oberhelman Dennis, Galbreth Michael () and Fry Timothy
Additional contact information
Oberhelman Dennis: University of South Carolina, Moore School of Business, Columbia, South Carolina, USA
Galbreth Michael: University of South Carolina, Moore School of Business, Columbia, South Carolina, USA
Fry Timothy: University of South Carolina, Moore School of Business, Columbia, South Carolina, USA

Journal of Quantitative Analysis in Sports, 2013, vol. 9, issue 4, 285-300

Abstract: Recreational golf events differ from professional events in that the primary goal is not simply to identify the best golfer, but rather for all golfers to enjoy and participate meaningfully in the competition. For this reason, it can be beneficial in recreational events to employ “handicapping” systems which enable players of varying skill levels to compete on a level playing field. In this paper we use a stochastic model of the most common recreational event format, the scramble competition, to develop a formula for handicapping scramble tournaments. The formula involves only simple arithmetic, enabling its implementation by tournament organizers in a spreadsheet or other user-friendly platform. In theory, the proposed handicapping system provides all scramble teams with an equal expectation of winning the tournament. Data from actual scramble tournaments are used to assess how well this objective is met, using a scramble handicapping system recommended by the USGA as a basis for comparison. We show that the handicap developed in this paper achieves its goal of providing a more equitable tournament.

Keywords: data analysis; estimation; recreation and sports; stochastic model applications (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/jqas-2013-0030 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jqsprt:v:9:y:2013:i:4:p:285-300:n:5

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jqas/html

DOI: 10.1515/jqas-2013-0030

Access Statistics for this article

Journal of Quantitative Analysis in Sports is currently edited by Mark Glickman

More articles in Journal of Quantitative Analysis in Sports from De Gruyter
Bibliographic data for series maintained by Peter Golla ().