Guillaume Laffaye

RELIABILITY AND VALIDITY OF AN ACCELEROMETRIC SYSTEM FOR ASSESSING VERTICAL JUMPING PERFORMANCE

The validity of an accelerometric system (Myotest©) for assessing vertical jump height, vertical force and power, leg stiffness and reactivity index was examined. 20 healthy males performed 3ד5 hops in place”, 3ד1 squat jump” and 3× “1 countermovement jump” during 2 test-retest sessions. The variables were simultaneously assessed using an accelerometer and a force platform at a frequency of 0.5 and 1 kHz, respectively. Both reliability and validity of the accelerometric system were studied. No significant differences between test and retest data were found (p < 0.05), showing a high level of reliability. Besides, moderate to high intraclass correlation coefficients (ICCs) (from 0.74 to 0.96) were obtained for all variables whereas weak to moderate ICCs (from 0.29 to 0.79) were obtained for force and power during the countermovement jump. With regards to validity, the difference between the two devices was not significant for 5 hops in place height (1.8 cm), force during squat (-1.4 N · kg−1) and countermovement (0.1 N · kg−1) jumps, leg stiffness (7.8 kN · m−1) and reactivity index (0.4). So, the measurements of these variables with this accelerometer are valid, which is not the case for the other variables. The main causes of non-validity for velocity, power and contact time assessment are temporal biases of the takeoff and touchdown moments detection.

Repeated sprint ability in young basketball players: one vs. two changes of direction (Part 2)

Abstract The present study aimed to compare the changes of direction on repeated sprint ability (RSA) vs. intensive repeated sprint ability (IRSA) protocols in basketball. Eighteen young male basketball players performed on RSA [10 × 30-m (15 + 15-m, one change of direction)] and IRSA [10 × 30-m (10 + 10 + 10-m, two changes of direction)]. A correlation matrix between RSA, IRSA, “squat jump (SJ)–countermovement jump (CMJ)”, footstep analysis and total distance in Yo-Yo intermittent recovery level 1 was performed. The best time, worst time, total time and the number of footsteps were significantly smaller in the RSA test compared to IRSA test (P < 0.001), even though they were significantly correlated with each other (r > 0.80, P < 0.05). Blood lactate level and fatigue index did not show any difference between tests. The sensibility of the two tests assessed by the Bland–Altman analysis revealed a small bias (<1.5%) for almost all variables. Moreover, almost all time variables of the two tests were significantly correlated with the SJ (r > 0.478, P < 0.05), CMJ (r > 0.515, P < 0.05) and Yo-Yo (r > 0.489, P < 0.05) performances. The IRSA provided a reliable method for assessing specific sprint ability (with 10-m legs for IRSA ~2.3 s vs. 15 m for RSA ~3 s) with a closer link to basketball game’s actions (~2 s). Besides, IRSA could be an appropriate choice for assessing both RSA and changes of direction capacities in basketball players.

Gender bias in the effect of dropping height on jumping performance in volleyball players.

Laffaye, G and Choukou, MA. Gender bias in the effect of dropping height on jumping performence in volleyball players. J Strength Cond Res 24(8): 2143-2148, 2010-The goal of the present study is to investigate in skilled volleyball players (a) the effect of dropping height on womens and mens performance and (b) the drop jump technique with regard to gender. Nine male and 9 female skilled volleyball players were instructed to jump as high as they could, using a drop jump, from a box of 30 cm or from 2 boxes (60 cm). Kinematic and kinetic data were collected using 6 cameras and a force plate. The human body was summarized by using a 4-segment model (foot, shank, thigh, head-arms-trunk). Males performed higher jumps than females (46.6 ± 7.5 cm vs. 36 ± 5.4 cm; p < 0.05). This could be explained by higher mean power (56.9 ± 26 W/kg vs. 42.4 ± 19 W/kg; p < 0.05) and shorter eccentric time (−46.3%), both of which allowed a better stretch-shortening cycle. This study shows that women and men have different jump techniques when they drop from a higher position but without increasing the vertical performance. Women increase the values of force and stiffness (respectively +21.4% and +17.9%) without changing the temporal structure of the jump. Men reduce the eccentric time of the jump (41% vs. 31.8%) and keep the force parameters constant. The study findings indicate that it is necessary to find an optimal height for plyometric training for each athlete, allowing enhancement.

Concentric and eccentric: Muscle contraction or exercise?

1 Faculty of Medicine and Surgery, University of “Tor Vergata” Rome (Italy). 2 SPO Sport Performance Optimization Lab, CNMSS, Tunis (Tunisia) 3 UR CIAMS – Motor Control and Perception Group, Sport Sciences Department, Université Paris-Sud, Orsay (France). 4 School of Exercise and Sport Science, University of Verona (Italy). 5 Orthopaedic and Sports Medicine Hospital, Doha (Qatar). Authors submitted their contribution of the article to the editorial board. Accepted for printing in Journal of Human Kinetics vol. 37/2013 on June 2013. Concentric and Eccentric: Muscle Contraction or Exercise?

Eccentric rate of force development determines jumping performance

1. IntroductionCritical information can be directly extracted from theforce–time (F–T) curve during the vertical counter-movement jump (CMJ), such as time variables, forcevariables and variables linking both components [rate offorce development (RFD), impulse and power]. Consider-ing that the performance during CMJ is the result of thehigh level of efficiency of all these mechanisms, it isexpected that the vertical performance (VP) is stronglylinkedtothemechanicalvariablesresponsiblefortheforceproduction in concentric contraction and in elasticstructural elements. More specifically, the RFD seems toplay a crucial role in activities involving plyometricmuscular contractions, such as sprinting or jumping.This variable has been frequently studied but oftenduring the concentric phase or only when the peakoccurred (McLellan et al. 2011), but very rarely during theeccentric (ECC) phase.We hypothesised that ECC–RFD is a better candidateto predict VP during jumping because it summarises whathappens in the tendon-muscle system to optimise thestretch shortening cycle. The goal of this study is to (i)assess the role of selected variables of F–T curves on theVP during CMJ and (ii) predict vertical jump performancewith a high level of accuracy, using the method ofmultiregression analysis.2. MethodsThe sample was composed of 178 males, all skilledathletes (football, basket-ball and base-ball) evolving inthe national US championship. All testing was done withthe subject standing on a 0.6m

Shuttlecock velocity during a smash stroke in badminton evolves linearly with skill level

Highly ranked badminton players seem to have a different stroke technique compared to lower ranked players (Sørensen 2010). Up to now, no studies have analysed the evolution of this velocity with expertise. So, in this study it is hypothesised that the maximal velocity of the shuttlecock during a smash evolved linearly until a plateau corresponding to the optimal smash movement. Moreover, the aerodynamic of the trajectory was investigated to understand how this velocity evolves during the whole trajectory.

Is the ball velocity dependent on expertise? A multidimensional study in handball

The goals of this study are to 1) compare the differences in anthropometric and physical fitness characteristics between elite and skilled players, 2) investigate these parameters and ball velocity in three conditions (standing position, with a three-step run and the difference between them) and 3) predict ball-throwing velocity. We measured general anthropometric parameters and upper-limb dynamic strength using medicine ball throwing tests. Lower-limb power, strength and reactivity were assessed using a hopping-in-place jumping test and a squat-jump test. Elite players are taller (+7.75%) and heavier (+24%) than skilled players, and have greater upper-limb strength (+23%), all p< .05. The ANOVA revealed a significant effect of expertise (p < .001) and of the type of overarm throw (p < .0001) on ball velocity, but with no interaction effect. The improvement obtained through a three-step run is 2.19 ± 0.72 m.s-1. Additionally, the best multiple regression models explained 73% of total variability including at least an isotonic test and an anthropometric variable. Finally, we validate the equations found on a 24-player independent sample (T(46)<1, n.s.) and they all are very stable whatever the sample.

RETRACTED: Concentric and Eccentric Exercise

To the Editor: This contribution considers the use and possiblemisuse of the terms concentric and eccentric in several contexts: first, the origin of terms; second, different approaches; and third, the possible uses. To our knowledge, an article has been published in The Journal of Pain misusing the terms concentric/eccentric exercise. The purpose of this letter is to foster the use of the terminology positive/negative work together with concentric/ eccentric contraction to ease reference search (ie, through key words) and comprehension.

Fosbury flop: predicting performance with a three-variable model.

Laffaye, G. Fosbury flop: predicting performance with a three-variable model. J Strength Cond Res 25(8): 2143-2150, 2011—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.

Determinant factors in climbing ability: Influence of strength, anthropometry, and neuromuscular fatigue

The goal of this study was to (i) assess the physical and anthropometric differences between three levels of climbers and (ii) predict climbing ability by using a multiple regression model. The participants were divided into novice (n = 15), skilled (n = 16), and elite (n = 10) climbers. Anthropometric characteristics such as height, weight, percentage of body fat and muscle, bi‐acromial breath, arm span, and ape index were measured. General and specific strength were assessed through an arm jump test, a bench press test, and a hand and finger grip strength test in maximal and endurance conditions. All variables were combined into components via a principal component analysis (PCA) and the components used in a multiple regression analysis. The major finding of this study is that climbing ability is more related to specific rather than general strength. Only finger grip strength shows a higher level of initial strength between all samples while the arm jump test discriminates between climbers and non‐climbers. The PCA reveals three components, labeled as training, muscle, and anthropometry, which together explain 64.22% of the variance. The regression model indicates that trainable variables explained 46% of the total variance in climbing ability, whereas anthropometry and muscle characteristics explain fewer than 4%.