title: Fosbury flop: predicting performance with a three-variable model.
abstract: The goal of this study is to (a) find the most predictive anthropometric factors, (b) check the predictability of a new jumping motor test, and (c) predict Fosbury-flop (FFP) performance by using a multiregression analysis. The participants of this study were 49 girls (age 13.6 ± 0.48 years; height = 1.61 ± 0.07 m) and 68 boys (age 13.6 ± 0.47 years; height = 1.64 ± 0.10 m). We measured the height, the sitting height), the highest position touched by the hand in a standing position (HEIGHTARM), the highest position touched by the hand during a running 1-leg vertical jump with a semirestricted curved run-up (HMAX), and the best performance in the FFP. We then calculated the leg length (LEGLENGTH), the skelic index (ratio of legs length to the abdomen length, SKEL), the vertical performance (VP, difference between HMAX and HEIGHTARM). The ability level was deducted from the difference between (LEGLENGTH + VP) and FFP. Pearson correlation coefficients were calculated, and a multiple-regression analysis technique was applied to find the most predictive model (p < 0.05). The FFP was correlated with standing height (HEIGHT; r = 0.398; p < 0.05), HMAX (r = 0.707; p < 0.0005), ABILITY (r = 0.391; p < 0.005) but not with SKEL (r = 0.161; p = 0.01). The best multiple-regression model included HEIGHT, HMAX, and ABILITY with a high level of prediction (r2 = 0.94). In conclusion, the FFP performance can be predicted with equation: FFP = -0.618 HEIGHT + 0.898 HMAX + 0.669 ABILITY - 0.08. This equation is quite similar for both sexes, showing that 13-year-old girls and boys use the same method to jump high, which implies that the way to increase coordination or lower limb strength during training can be the same for junior boys and girls in high jump.
authors.affiliation: UR CIAMS-Motor Control and Perception Group, Sport Sciences Department, University of Paris XI, Orsay Cedex, France. guillaume.laffaye@u-psud.fr
authors.forename: Guillaume
authors.initials: G
authors.lastname: Laffaye
mesh_terms: D000293:Adolescent; D056352:Athletes; D054874:Athletic Performance / Q000502:physiology*; D001696:Biomechanical Phenomena; D001827:Body Height / Q000502:physiology; D002648:Child; D005260:Female; D006801:Humans; D007866:Leg / Q000033:anatomy & histology / Q000502:physiology; D008124:Locomotion / Q000502:physiology*; D008297:Male; D008954:Models, Biological; D012044:Regression Analysis; D012399:Rotation; D013177:Sports / Q000502:physiology*