Abstract:
Many different anthropometric, physiological, and biomechanical factors contribute to human sprinting performance, but only a few can be reasonably measured on the field. To understand which of these measureable factors best explain sprinting velocity, we examined the relationship between sprinting kinematics, measures of joint power, strength, and anthropometrics and running time. Kinematic data was collected using 2D motion capture during a 60m run at a maximal sprint, 90% of max, 75% of max, and 60% of max. These data were used to calculate tibia angle with respect to horizontal and foot angle with respect to vertical during both the heel strike and toe off phases of gait. A step-wise linear regression was run to determine the predictive capability of sprinting kinematics (at a submaximal pace) for maximal sprint time. Another regression was run to determine the predictive capability of measures of strength and power on maximal sprint time. Results indicated that broad jump, left hip flexion, and foot angle at toe off when running at 75% of max were predictive of maximal sprint time. This information can provide coaches, trainers, and athletes with information about how to obtain the most predictive data for improvement of sprinting performance.
Description:
45 pages. A thesis presented to the Department of Human Physiology and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Science, Spring 2017