Publication Date

5-2009

Date of Final Oral Examination (Defense)

4-1-2009

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Exercise and Sports Studies, Biophysical

Department

Kinesiology

Major Advisor

Ronald P. Pfeiffer, Ed.D.

Major Advisor

Michelle B. Sabick , Ph.D.

Advisor

Shawn Simonson, Ed.D.

Advisor

Kevin Shea, M.D.

Abstract

As an alternative to natural grass playing fields, the installation of artificial turf surfaces has grown exponentially over the past several decades. Despite the growing popularity of artificial turf, little is known about the interaction between the player’s shoe and the turf surface. Previous research has sited the difficulty in maximizing performance (high traction), yet minimizing the risk of injury (low traction). Due to seemingly countless factors that affect the turf-shoe interaction, determining safe traction ranges for artificial turf is very difficult. Safe ranges between performance and risk of injury need to be found. The purpose of this study was to investigate whether traction characteristics vary based on a particular cleated athletic shoe on artificial turf at various angles of internal rotation during a linear translational motion. 4 U.S. Men’s size 12 cleated athletic shoes with a variety of stud styles from several different commonly used brands were tested on the artificial turf. Each cleated athletic shoe was set at various angles (0º, 30º, 60º, 90º) of internal rotation, and experienced linear translational motion while data was being collected. Significant differences were found within each cleated athletic shoe at various angles of internal rotation across all dependent variables (p=0.000). This could be attributed to a phenomenon termed the trench effect. There were no significant differences between cleated athletic shoes on artificial turf. Shoe-turf interactions are a very important consideration in athletics. This interaction is a determinant of the level of athletic performance and risk of injury. Shoe-turf interaction is a very stochastic process, and results should only be evaluated within the context of the test conditions.

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