Handball is a globally popular and physically demanding sport that requires high-intensity intermittent activities, with a particular emphasis on frequent ball throwing or shooting. The primary aim of this systematic review was to identify the risk factors for shoulder injuries in professional male handball players. The secondary aim is to propose preventive measures for reducing shoulder injuries in professional or elite handball players. This study followed the guidelines provided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Web of Science, PubMed, Science Direct, and Google Scholar were used to identify relevant studies. Only 8 studies met the eligibility requirements and were incorporated into the review. The Physiotherapy Evidence Database (PEDro) was assessed for the methodological quality of studies. Seven of the total eight studies were considered moderate quality, however, only one study was considered low quality. Based on this review findings, the following risk factors for shoulder injury are prominent among professional and elite male handball players. The primary factors for eventual shoulder injury are shoulder muscle imbalances, range of motion (ROM) discrepancies, glenohumeral internal rotation deficit (GIRD), and scapular dyskinesis. Also, in one study authors specified player position as a potential risk factor.

Swimming speed depends on anthropometric characteristics, biomechanics factors, physical fitness, physiological components, and genetics. Therefore, this study aimed to identify which anthropometric characteristics influence swimming speed in adolescent competitive swimmers. Thirty-eight male swimmers (aged 16.94 ± 0.8 years; body height: 178.3 ± 5.4 cm; body weight 67.7 ± 9.6 kg) and thirty-five female swimmers (aged 17.12 ± 0.7 years; body height: 175.1 ± 6.6 cm; body weight 59.9 ± 7.1 kg) participated in the study. All swimmers have competed at the national level in Serbia for at least three years and have at least five years of training experience. Fifteen variables were measured: arm length, hand length, leg length, foot length, seat height, wrist diameter, ankle joint diameter, elbow diameter, chest circumference, triceps skinfold, forearm skinfold, abdominal skinfold, subscapular skinfold, thigh skinfold, calf skinfold. The measurements were taken by the Martin anthropometer, Omron digital scale BF511, and John Bull caliper. Swimming speed was measured during 50-m and 100-m front crawl swimming. Multiple regression analysis revealed that arm length, wrist diameter, and chest circumference, all together, accounted for 77% of 100-m front crawl swimming speed in male swimmers, while abdominal skinfold accounted for 90% of 100-m front crawl swimming speed in female swimmers. Results showed that anthropometric characteristics could not account for adolescent swimmers' 50-m front crawl swimming speed. However, anthropometric characteristics can influence the result in swimming (100-m front crawl swimming speed) in adolescents and thus should be considered a diagnostic tool in selecting young swimmers.

CrossFit is recognized as one of the fastest-growing high-intensity functional training modes in the world. The study aimed to compare the effects of the CrossFit training program and traditional gym training on anthropometric measurements in healthy, active men. The study sample consisted of 50 participants who were divided into two groups, 22 participants who practiced the CrossFit training program (CFT group; 28.64±2.04 years; body height 181.74±6.96 cm; body mass: 72.75±5.53 kg), and 28 participants who applied traditional gym training (GT group; 26.89±2.99 years; body height: 184.52±7.80 cm; body mass: 74.86±8.48 kg). A total of ten anthropometric measurements (Body height, Body mass, BMI, Subscapular, Abdominal and Triceps skinfolds, Chest, Forearm, Upper arm, and Thigh circumferences) were monitored before and after twelve weeks. The Shapiro-Wilk test was used to test the normality of distribution. The multivariate analysis covariance (MANCOVA) and analysis of covariance (ANCOVA) were used to analyze the data. The results of this study indicated that there were statistically significant differences between groups in the Circumference of the upper arm (p=0.02), Thigh circumference (p=0.00), Chest circumference (p=0.03), and Subscapular skinfold (p=0.00). The findings of this study demonstrated that healthy, active males who participated in the 12-week CrossFit training program improved their anthropometric measurements more than those who trained in the traditional gym training.