Date of Award
10-31-2022
Document Type
Thesis
Degree Name
Exercise Science, MS
First Advisor
Eric Scudamore
Committee Members
Eric O'Neal; Veronika Pribyslavska
Call Number
LD 251 .A566t 2022 C37
Abstract
Division I cross country (XC) running has many factors that influence performance and is extremely difficult to predict. Consequently, coaches often struggle to identify performance potential in athletes. In this study, personal best race times, VO2max, triceps skinfold, and a series of counter movement jump assessments were performed by female (n=15) and male (n=17) NCAA XC runners to predict XC performance. Simple regression modeling identified 3200-m high school (HS) personal best (PB) time as best predictor for men’s 8-km performance (r = 0.85; p = 0.005, SEE = ± 0.65 min). For women, a model including triceps skinfold, vertical jump, reactive strength index, and maximal volume of oxygen consumption approached significance (r = 0.75; p = 0.009 SEE = ± 0.71 min). When recruiting high school or transfer XC runners, coaches should consider assessing these aforementioned variables to assist them with determining how they will perform during an 8-km XC race.
Rights Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Carder III, Mac John, "Predictors Of NCAA Division I Women’s and Men’s Cross-Country Performance" (2022). Student Theses and Dissertations. 237.
https://arch.astate.edu/all-etd/237
Included in
Health and Physical Education Commons, Kinesiology Commons, Sports Medicine Commons, Sports Sciences Commons
