Player performance in an intense sport such as basketball is known to be related to attributes such as speed, agility, and power. This study presents a comparative analysis of associations between anthropometric assessment and physical performance in different age groups of elite youth basketball players, while simultaneously identifying the predictors for speed and agility in these players. U14 (n = 44), U15 (n = 45), and U16 (n = 51) players were tested for anthropometry, lower-body power, speed, and agility. U16 players were found to be taller, heavier, more muscular than U14 and U15 players. In addition, the U16 group showed better performance in all performance tests. Age had a significant positive correlation with countermovement (CMJ) and drop jump (DJ) performance in U14 players, and a significant negative correlation with 15m and 20m sprint times in the U15 group. CMJ and DJ emerged as the most significant predictors for sprint and agility variables, respectively. Body fat percentage was found to be a significant predictor for the speed and agility tests in all age groups, but a negative lower-body power predictor. Therefore, besides all sport-specific and fitness tests, it is essential to place emphasis on the percentage of body fat when designing players’ individualized training programs, and during team selection.

The purpose of the research was to identify the impact of peripheral (unilateral and bilateral) vision on manual reaction time to visual stimuli in handball, basketball and volleyball players by implementing a 6-week experimental program of specific exercises and some adapted tests using Fitlight technology. The research included 412 players (212 male—51.5%; 200 female—48.5%) from three team sports: basketball—146 (35.4%), handball—140 (40%) and volleyball—126 (30.6%). The experimental program carried out over 6 weeks was identical for all handball, basketball and volleyball players participating in the study; two training sessions per week were performed, with each session lasting 30 min; 15 exercises were used for the improvement of manual reaction time to visual stimuli involving peripheral vision. Through the Analysis of Variance (ANOVA), we identified statistically significant differences between the arithmetic means of the samples of handball, basketball and volleyball players, as well as according to general samples also of gender (male and female), p = 0.000. Male and female handball samples achieved the greatest progress in manual reaction time to visual stimuli involving peripheral vision for the Reaction time test with a unilateral right visual stimulus (30 s) and the Reaction time test with a unilateral left visual stimulus (30 s), while general sample also of male and female basketball samples, for the Reaction time test with bilateral visual stimuli (30 s) and the Reaction time test with six Fitlights (1 min); male and female volleyball samples recorded the lowest progress in all tests compared to handball and basketball groups. According to our results, female samples made greater progress in reaction time than male groups for all four tests of the present study. The implemented experimental program led to an improvement in manual reaction time to visual stimuli due to the use of Fitlight technology and the involvement of peripheral vision for all research samples.

Player’s performance in an intense sport such as basketball is known to be related to attributes like speed, agility, and power. This study presents a comparative analysis of associations between anthropometric assessment and physical performance in different age-group elite youth basketball players, while simultaneously identifying the predictors for speed and agility in these players. U14 (n=44), U15 (n=45) and U16 (n=51) players were tested for anthropometry, lower body power, speed, and agility. U16 players were found to be taller, heavier, more muscular than U14 and U15 players. Also, the U16 group showed better performance in all performance tests. Age had a significant positive correlation with countermovement (CMJ) and drop jump (DJ) performance in U14 players, and a significant negative correlation with 10m and 20m sprint times in U15 group. CMJ and DJ emerged as the most significant predictors for sprint and agility variables, respectively. Body fat percentage was found to be a significant predictor for the speed and agility tests in all age groups, but a negative lower-body power predictor. Therefore, besides all sport-specific and fitness tests, it is essential to place emphasis on the percentage of body fat when designing players’ individualized training programs, and during team selection.

The purpose of this study was to evaluate the effect of 8-week β-alanine supplementation on C-Reactive Protein (CRP), interleukin-6 (IL-6), body composition, and bio-motor abilities in elite male basketball players. Twenty male basketball players (age: 23 + 0.6 years; body mass: 78.3 + 4.8 kg; height:185.3 + 5.4 cm, %BF, 15.2 ± 4.8) volunteered to participate in this study. They were divided into a β-alanine group (BG, N = 10) and a placebo group (PG, N = 10). All players were preparing for university competitions and had played for over five years. Players used 6.4 g/d of β-alanine in BG and maltodextrin in PG. The participants were involved in regular basketball training three months before the study. CRP, IL-6, body composition parameters, and bio-motor abilities were measured before starting the exercises and after completing the eight-week training period. The research findings showed a significant decrease in CRP and IL-6 and an increase in anaerobic peak power between the pre-test and post-test, as well as between BG and PG groups (p < 0.05). Although the other measured factors were a relative improvement compared to the pre-test and also compared to PG, these changes were not statistically significant (p < 0.05). Eight weeks of β-alanine supplementation ameliorated increases in IL-6 and CRP associated with in-season physical stressors in collegiate basketball players. These changes in pro-inflammatory cytokines suggest that β-alanine supplementation may be a useful nutritional strategy for immune regulation and can also improve anaerobic performance compared to PG.

The study purpose was to assess the relationship between Latent Myofascial Trigger Point and range of motion in the lower limb of athletes. A lower Pain pressure threshold (< 25 lbs/cm²) in muscles indicates the presence of a latent myofascial trigger point. Materials and methods. Initially, the study involved 46 male Athletes (aged 20-23 years) as participants. The pain pressure threshold was measured by the pressure algometer (FPX 25 Wagner Instruments, Greenwich, CT, USA) to detect latent myofascial trigger points on the hamstring and quadriceps muscles. Out of 46 participants, 23 tested positive with a latent myofascial trigger point, and rest of them tested negative with a latent myofascial trigger point. All the participants measured knee flexor and extensor range of motion with the Kinovea software (version 0.9.5). In descriptive statistics, mean and standard deviation were used, and Pearson correlation was used to determine the relationship between the variables. The level of significance was set at 0.05. Results. A significant correlation was found between Latent Myofascial Trigger Points and lower limb range of motion (p < 0.05), and it was also observed that the magnitude of correlation coefficient was very large (0.7–0.9). Conclusions. Latent Myofascial Trigger Points impair sports performance by decreasing the range of motion of knee flexors and extensors. In light of this, Latent Myofascial Trigger Point should be considered a serious musculoskeletal disorder, and appropriate preventative measures should be taken by health professionals.

Background/Objectives: Exercise-induced fatigue is a fundamental component of running performance and training, yet it is also implicated in altered movement mechanics and increased injury risk. While numerous studies have examined fatigue-related biomechanical changes during running, findings remain fragmented across biomechanical domains and fatigue modalities. The purpose of this systematic review was to synthesize contemporary evidence on the effects of fatigue on lower-limb biomechanics during running and to interpret the potential injury relevance of these adaptations. Methods: A systematic literature search was conducted in PubMed, Scopus, and Web of Science for original empirical studies published between January 2010 and December 2025. Eligible studies involved human participants performing running or running-related tasks, applied an explicit fatigue protocol, and reported quantitative lower-limb biomechanical outcomes. Study selection followed PRISMA 2020 guidelines. Data extraction included participant characteristics, fatigue protocols, biomechanical measures, instrumentation, and key findings. Methodological quality was assessed using the Cochrane Risk of Bias 2 (RoB-2) tool. Due to substantial methodological heterogeneity, findings were synthesized narratively. Results: Twenty-four studies met the inclusion criteria. Across studies, fatigue consistently altered spatiotemporal parameters, joint kinematic and kinetic variables, spring-mass behavior, impact loading, coordination variability, neuromuscular output, and inter-limb symmetry. Common adaptations included increased ground contact time, reduced ankle joint power and stiffness, increased joint range of motion, elevated impact loading, and greater movement variability. These changes reflected reduced mechanical efficiency and a redistribution of mechanical load from distal to proximal joints, particularly toward the knee and hip. Similar fatigue-related biomechanical patterns were observed in both laboratory-based and real-world endurance running conditions. Conclusions: Exercise-induced fatigue produces systematic and injury-relevant alterations in lower-limb biomechanics during running. These adaptations may preserve short-term performance but create mechanical conditions associated with increased susceptibility to overuse and non-contact injuries. Integrating fatigue-aware biomechanical assessment, neuromuscular conditioning, and individualized load management strategies may help mitigate adverse fatigue-related adaptations.