Optimizing basketball performance during the stages of long-term athlete development require to identify the trainability and variation of specific technical skills, when adjusting for anthropometric changes. The aim of this study was to describe differences in height, body mass, arm span, and technical-related fitness (movement, dribbling, shooting) along the long-term development of 7–17 years Lithuanian basketball players. This cross-sectional analysis involved a total of 1051 basketball players from the Sabonis Basketball Center in Lithuania. Testing sessions were performed during 1 day of the competition period in an indoor court. The participants performed technical-related fitness tests to assess dribbling (control dribble, 20 m dribble, two balls of 20 m dribble, Illinois agility dribble), shooting (30 free-throw shoots, 1 min shooting, modified medium and long-range shots, close range shots) and defensive movements. The dribbling skills had substantial improvements (7 to 8-years-old: 20 m sprint with dribbling, effect size = 1.86; control dribble effect size = 2.18; 9 to 10-year-old: 20 m sprint with dribbling, effect size = 1.85; Illinois agility test with dribbling effect size = 1.82). Changes in defensive movement occurred mostly at the 14–15-age period. The best periods to develop dribbling and shooting skills were between 7–10 and 12–13 years, whereas defensive movements can be trained in later adolescent years. Current results and consequent normative profiles, presented as percentile tables, allow to accurately follow the players’ development.

No abstract

Research  background  and  hypothesis. The  efficacy  of  athlete’s  sport  performance  depends  on  the  targeted training in certain periods, organization, management, individual adaptation of an athlete to the loads of training and competitions.  Research aim of this work was to determine the impact of intensive training on sport performance of 14–15 year old athletes in rhythmic gymnastics and their optimization.  Research methods. The experiment resulted in modeling two different training programs and establishing the structure of the content of the training programs, as well as athletes’ sports performance. The training loads protocols registered the time for choreography, element mastering, competitive routines and athletic training in each training session. The efficacy of the training programs was established registering the realization of competitive activities under competitive conditions according to the number of points received by the gymnast of each training program and according to the place won. When we tried to establish if the training sessions and competitive loads matched the specificity of competitive activities, we registered the changes in the athletes’ heart rate during different training sessions.Research  results.  Training  of  athletes  in  two  training  programs  was  different  –  their  training  loads  were  not significantly different – from 672 to 697 hours a year, as well as the indices of the training days – from 5.4 to 5.6 days a week, but the training content differed significantly. In most effective training program choreographic training dominated (30.9%). Statistically significant differences (p  < 0.05) were found in the indices of explosive strength and muscular power, specific endurance and coordination movement abilities. At the beginning of the season and at the end of it the realization of the body movement technique performing routines with different tools was not different (p > 0.05). Discussion and conclusion. Sports performance of 14–15-year-old athletes in rhythmic gymnastics was mostly influenced  by  the  time  for  mastering  competitive  routines  (r  =  0.836);  however,  the  research  did  not  establish differences  in  intensifying  training.  Besides  the  importance  of  integral  athletic  fitness,  explosive  strength,  and strength endurance, the research established the significance of aerobic fitness (r  = 0.704) for sports performance. Moreover, the significance of body composition indices increased in comparison with previous training years: body height (r = –0.819), body weight (r = –0.657), and BMI (r = –0.836).

Research background and hypothesis. Europeans have won Olympic and world gold medals since modern indoor men’s handball became an international sport (1938) and an Olympic sport (1972) (www. ihf.com). Nevertheless, no research has been carried out in order to find out the tendencies in European modern men’s handball. Research aim of this study was to illustrate discriminant indicators of sport performance between winners and losers in European men’s modern handball match activities. Research methods. Data sets were gathered from the European Handball Federation (EHF) website (http://www.eurohandball.com) covering the five European Men’s Handball Championships (EMHC): 2002, 2004, 2006, 2008 and 2010 (n = 239 matches). Each match was classified as successful and non-successful for each team, and then the number of analysed matches doubled to 478. We examined 28 variables of sport performance, but only 15 key indicators where significant discriminant between winners and losers at least in one EMHC was shown. Research results. Winners scored more goals (p < 0.01, p < 0.001), were better in total attack (p < 0.001) and positional attack (p < 0.01, p < 0.001), performed more efficiently in shooting total (p  < 0.001) and shooting from long distance (p < 0.01, p < 0.05), and goalkeepers saved more throws (p < 0.05, p < 0.001).Discussion and conclusions. Winning and losing teams played in the same pattern (p > 0.05). In many cases the separate match-play was determined by using temporal model of playing style. The phenomenon is that teams scored more goals in the second half than in the first one despite the fact that players’ activities decreased in the second half. Sport performance profile in European modern handball can generate a useful database.

Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoad™, accelerations, decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (ρ) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad™ as the independent variable, and players as random effect. Results: The lowest significant (P < .05) relationship was for high jumps with objective (ρ = .56) and subjective (ρ = .49) IL. The strongest relationship was for PlayerLoad™ with objective (ρ = .9) and subjective (ρ = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75–33.31); SE = 5.26, and R2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00–7330.6); SE = 21.87; and R2 = .71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.