Independence in College Golf Scores

Level of Education of Students Involved

Undergraduate

Faculty Sponsor

Tiffany Kolba

College

Arts and Sciences

Discipline(s)

Statistics

Presentation Type

Oral Presentation

Symposium Date

Spring 4-27-2023

Abstract

Two commonly-studied ideas in sports are the "hot hand" and "cold hand" phenomenon. The "hot hand" is when an athlete performs better than expected after a good outcome. For instance, a basketball player may be more likely to make a shot after making their two previous shots. In contrast, the "cold hand" is when an athlete performs worse than expected after a bad outcome. Both of these phenomena have been studied in a variety of sports including basketball and tennis, but only a couple of studies have examined their relation to golf. In golf, there is a widely-held idea that better players are more level-headed in the face of unusually good or bad outcomes, meaning that they theoretically exhibit less of a "hot hand" and "cold hand" effect. In statistical terms, this means that the scores of better players should exhibit greater independence than the scores of worse players. Using scores from college golf tournaments, I test this idea using a Chi-Square Test of Independence and a Two-Way ANOVA Test. Surprisingly, I find that better players actually exhibit less independence in their golf scores, and have an increased chance of following up a bad hole with another bad hole. In other words, better players are more likely to exhibit a "cold hand" effect than worse players. This suggests that, contrary to popular knowledge, mental calmness may not be a major determinant of a golfer’s skill level.

Biographical Information about Author(s)

Caleb VanArragon is an undergraduate student who is double-majoring in Biology and Statistics at Valpo. He is also on the Valpo Men's Golf Team, and his experience as a college golfer sparked his interest in investigating college golf scores through a statistical lens. Caleb has worked on several biology research projects at Valpo, and his career goal is to merge statistics and biology by becoming a biostatistician for a pharmaceutical or biotechnology company.

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