Term of Award
Master of Science in Kinesiology (M.S.)
Document Type and Release Option
Thesis (open access)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department of Health and Kinesiology
Committee Member 1
Committee Member 2
Committee Member 3
The aim of this study was to examine the ability of anthropometrics (AP) to predict both performance testing (P) (n = 14) and game performance (GP) (n = 10) in female collegiate volleyball players; the relationship between AP and both P and GP. AP consisted of segment lengths and ratios, body height, weight, and fat mass. For P, sport-specific performance tests were conducted assessing power and agility. Attacking and defensive GP statistics were transcribed from Volleymetrics for analysis purposes. AP, P, and GP were normalized through the use of Z-scores by team (T), front row (FR), and back row players (BR). From this an AP (APZ), P (PZ), and GP Z-score (GPZ) were established. Pearson correlations between AZ and GPZ as well as AZ and PZ by group were run. In addition, a multiple stepwise regression (MSR) was run to determine the ability of AP to predict GPZ and PZ by group. Pearson correlation presented with no significant relationships. Regression analysis presented with the ability of the thigh/shank ratio to predict PZ for T (r = 0.582, p = .029) and BR (r = 0.831, p < 0.021). Hand width was the greatest predictor of PZ for FR (r = 0.878, p = 0.009). For GP, Brachium/Antebrachium, height, and achilles tendon length AP predicted GPZ for the T group (r = 0.997, p < .001), and hand length and thigh/shank AP predicted GPZ for the FR group (r = 0.99, p = 0.01). These data indicate that segment ratios predict GP and P in collegiate volleyball players. In addition, further research should explore AP ability to predict GP across various sports.
Chrysosferidis, Peter, "Using Anthropometrics to Predict Performance in Division I Female Volleyball Athletes" (2018). Electronic Theses and Dissertations. 1724.
Research Data and Supplementary Material