ABSTRACT
The current study purpose examined the vertical height-anthropometry relationship with jump data obtained from an instrumented platform. Our methods required college-aged (n = 177) subjects to make 3 visits to our laboratory to measure the following anthropometric variables: height, body mass, upper arm length (UAL), lower arm length, upper leg length, and lower leg length. Per jump, maximum height was measured in 3 ways: from the subjects' takeoff, hang times, and as they landed on the platform. Standard multivariate regression assessed how well anthropometry predicted the criterion variance per gender (men, women, pooled) and jump height method (takeoff, hang time, landing) combination. Z-scores indicated that small amounts of the total data were outliers. The results showed that the majority of outliers were from jump heights calculated as women landed on the platform. With the genders pooled, anthropometry predicted a significant (p < 0.05) amount of variance from jump heights calculated from both takeoff and hang time. The anthropometry-vertical jump relationship was not significant from heights calculated as subjects landed on the platform, likely due to the female outliers. Yet anthropometric data of men did predict a significant amount of variance from heights calculated when they landed on the platform; univariate correlations of men's data revealed that UAL was the best predictor. It was concluded that the large sample of men's data led to greater data heterogeneity and a higher univariate correlation. Because of our sample size and data heterogeneity, practical applications suggest that coaches may find our results best predict performance for a variety of college-aged athletes and vertical jump enthusiasts.
Subject(s)
Anthropometry , Athletic Performance , Arm/anatomy & histology , Body Height , Body Mass Index , Female , Humans , Leg/anatomy & histology , Male , MovementABSTRACT
To examine the effects of resistance exercise (REX) mode on jump performance, subjects were assigned to one of three groups over a 6-week period with no cross-over. Subjects were assigned to leg and calf press REX on either a standard (n = 10) or ergometer (n = 9) device while a third group (n = 9) served as controls (CTRL). REX subjects worked out twice per week, which consisted of a three-set, 10-repetition paradigm for leg and calf press exercises. Immediately before and after the 6-week period, subjects performed tests that assessed jump (standing vertical jump, four-jump test protocol, depth jump) ability, while a fourth estimated knee extensor fast-twitch percentage (FT%) from fatigue incurred through a 50-repetition isokinetic protocol. Data analyses utilized 3 x 2 (group x time) repeated-measures ANCOVAs. Several dependent variables showed effects by group (standard REX, ergometer REX > CTRL) and time (post > pre). An interaction occurred for explosive leg power factor, a four-jump test variable, with standard REX post-test values as the interaction source. A trend for an interaction occurred for depth jump hang time, as ergometer REX values improved over time. Results suggest that mode-specific adaptations occur with REX training. Thus, athletes are best served with the selection of a REX device that is most specific to the demands of their jump performance task.