A new physical performance classification system for elite handball players: cluster analysis.

The aim of the present study was to identify different cluster groups of handball players according to their physical performance level assessed in a series of physical assessments, which could then be used to design a training program based on individual strengths and weaknesses, and to determine which of these variables best identified elite performance in a group of under-19 [U19] national level handball players. Players of the U19 National Handball team (n=16) performed a set of tests to determine: 10 m (ST10) and 20 m (ST20) sprint time, ball release velocity (BRv), countermovement jump (CMJ) height and squat jump (SJ) height. All players also performed an incremental-load bench press test to determine the 1 repetition maximum (1RMest), the load corresponding to maximum mean power (LoadMP), the mean propulsive phase power at LoadMP (PMPPMP) and the peak power at LoadMP (PPEAKMP). Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST20, 1RMest, PPEAKMP and PMPPMP. These variables could help coaches identify talent or monitor the physical performance of athletes in their team. Each cluster of players has a particular weakness related to physical performance and therefore, the cluster results can be applied to a specific training programmed based on individual needs.

Concurrent Validity of a Velocity Perception Scale to Monitor Back Squat Exercise Intensity in Young Skiers.

Execution velocity is among the main variables used to quantify resistance exercise intensity. The velocity at which a given load is displaced is one of the factors, which determine the training adaptations induced in the muscles. The purpose of this study was to assess the validity of the scale of perceived velocity (SPV) applied to the back squat. The study participants were 11 international level young elite skiers (8 men and 3 women) of mean age, height, weight, and estimated 1-repetition maximum/body weight ratio (1RMest/BW) 15.4 ± 1.12 years, 166.8 ± 8.83 cm, 63.6 ± 11.56 kg, and 1.61 ± 0.40, respectively. Participants performed a 2-stage protocol. In the first stage (familiarization), subjects were instructed on how to use the scale and performed an incremental load test to determine their 1RMest. In the second, or validation stage (72 hours later), exercises were executed at 6 relative intensities (20, 30, 40, 50, 60, and 70% of 1RMest) in random order in 2 sessions separated by 72 hours. Real velocity (Velreal) and perceived velocity (Velscale) values were linearly distributed showing excellent coefficients of determination (R(2) = 0.98 and R(2) = 0.99 for the 2-session trial). A 2-way repeated measures analysis of variance (scale [2] × session [2] × intensity [6]) revealed significant differences in the factor intensity and the interaction scale × intensity (no significant differences were detected in scale, session, scale × session, or scale × session × intensity). These data support the validity of SPV to monitor exercise intensity during lower-body strength training.

Predicting Power Output of Upper Body using the OMNI-RES Scale.

The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.