Search

Activity simulation protocols offer useful applications in research and practice; however, the specificity of such protocols to basketball game-play is currently lacking. Consequently, this study aimed to develop a game-specific basketball activity simulation protocol representative of typical playing durations and assess its reliability and discriminant validity. The simulation protocol was modified from an original version (i.e., Basketball Exercise Simulation Test) to incorporate regular breaks indicative of time-outs, free-throws, and substitutions. Twelve competitive male and female adult basketball players competing in the fourth or fifth Spanish basketball division underwent repeated trials of the simulation protocol (min. 4 to max. 14 days apart) for reliability analyses. In turn, 13 competitive male (fifth division), 9 competitive female (fourth division), and 13 recreational male adult basketball players completed the simulation protocol to assess discriminant validity via comparisons between sexes (competitive players) and playing levels (males). A range of physical, technical, and perceptual-physiological variables were collected during and following the simulation protocol. Several physical and heart rate variables displayed the strongest reliability (intraclass correlation coefficient [ICC] = 0.72-0.96; coefficient of variation [CV] = 1.78-6.75%), with physical decrement, technical, blood lactate concentration, and rating of perceived exertion (RPE) variables having the weakest (ICC = 0.52-0.75; CV = 10.34-30.85%). Regarding discriminant analyses between sexes, males demonstrated significantly greater physical outputs in several variables and lower RPE compared to females (p < 0.05, moderate-to-large effects). Comparisons between playing levels revealed competitive males had significantly greater physical outputs across many variables, alongside higher mean heart rate and lower RPE than recreational males (p < 0.05, moderate-to-large effects). This study presents a novel game-specific basketball activity simulation protocol replicating actual playing durations and game configurations that might be successfully applied for both training and research purposes. Reliability statistics are provided for several variables to inform end-users on potential measurement error when implementing the simulation protocol. Discriminant validity of the simulation protocol was supported for several variables, suggesting it may hold practical utility in benchmarking or selecting players. Future research on this topic is encouraged examining wider samples of male and female basketball players at different levels as well as additional forms of validity for the protocol. [ABSTRACT FROM AUTHOR]

This study aimed to assess and compare the physiological [percentage of maximal heart rate (%HRmax), blood lactate (BLa), creatine kinase (CK)], hormonal (testosterone, cortisol), psychological [rating of perceived exertion (RPE), enjoyment] and physical [percentage of moderate-to-vigorous physical activity (%MVPA) and vigorous activity (%VA)] responses of recreational 3 x 3 basketball (3 x 3BB) and high-intensity interval training (HIIT) in active young adults. Twelve apparently healthy male recreational basketball players (age: 23 ± 3 years; body mass: 82 ± 15 kg; stature: 188 ± 15 cm) completed a 3 x 3BB match and HIIT with similar duration. %HRmax, %MVPA and %VA were monitored during the protocols, while BLa, cortisol, and testosterone were measured before and after each protocol. CK was measured before the protocols and at 24 h, while RPE and enjoyment were assessed at the end of each protocol. 3 x 3BB elicited higher %HRmax (p < 0.001; d = -1.6, large), %MVPA (p < 0.001; d = 2.7, very large), %VA (p = 0.030; d = 0.8, moderate), enjoyment (p = 0.014; r-value = -0.500, large), and lower RPE (p = 0.024; r-value = -0.462, moderate) compared to the HIIT condition. Moreover, higher values of BLa were found in HIIT compared to 3 x 3BB at post-condition (p = 0.020; r-value = -0.601, large), while CK analysis showed only an increase within the HIIT condition (p = 0.020; r-value = -0.599, large). A time effect was found for both testosterone (p < 0.001, η² p = 0.526, moderate) and cortisol (p = 0.005, η² p = 0.743, strong), while no between-condition effect or interaction was found (p > 0.05). 3 x 3BB elicits higher %HRmax, enjoyment, and physical activity intensities but lower BLa and RPE compared to HIIT in active young adults and might be considered as a potentially suitable activity to increase participants' health status. [ABSTRACT FROM AUTHOR]

Background: The aims of this study were to (1) analyze the distribution of the player load (PLTOTAL) in 3 axes of movement (PLAP, anterior-posterior; PLML, medial-lateral; PLV, vertical) during elite soccer matches, (2) investigate the effect of playing position on PL-related variables, and (3) explore the association between PLTOTAL and distance covered by the players. Hypothesis: Despite different load distribution between axes of movement, PLTOTAL might be used as a body load indicator for all playing positions. Study Design: Longitudinal study. Level of Evidence: Level 3. Methods: Data were collected from elite soccer players using WIMU Pro tracking systems, which included inertial sensors. Results: The axis of movement had a significant effect on the distribution of the load (P < 0.001; conditional R 2 = 0.91), with the greatest contribution from the PLV (P < 0.001; d = 5.41-5.86). Moreover, no effect of playing position on PLTOTAL, PLV, PLML, or PLAP was observed (P > 0.05). Finally, a large correlation was found between PLTOTAL and distance covered, and the linear mixed model showed that distance may be predicted by the PLTOTAL (conditional R 2 = 0.81; P < 0.001). Conclusion: Differences in load distribution were based on the axis of movement, although playing position had no effect on any variable. The selection of either distance covered, which is representative of a 2-dimensional analysis, or PLTOTAL, which is representative of a 3-dimensional analysis, may be adequate for monitoring locomotor demands or accelerometer-derived load. Clinical Relevance: Training strategies that focus on the vertical component of match play should be adopted. In addition, given that PLTOTAL is an accelerometry-based metric, which combines the accelerations in anterior-posterior, medial-lateral, and vertical planes, strength and conditioning coaches may use this parameter as a measure of total body load. [ABSTRACT FROM AUTHOR]

Purpose. One factor affecting successful performance in beach handball is the efficiency of shootings. As only few studies evaluated gender-related differences in shooting performance, the aim of this study was to analyse variations of shooting efficiency between males (M) and females (F) during beach handball matches. Methods. Nine matches were analysed. Overall, there were 559 (M: 353; F: 206) shots, of which 54.7 ± 9.4% were successful and 19.9 ± 7.1% were goalkeepers' saves. Type of shot, shooting area, and goal area were recorded. Percentages of differences between genders were also computed. Players' efficiency was calculated as (frequency of goals*100)/frequency of shots. Goalkeepers' efficiency was calculated as (frequency of goalkeepers' saves*100)/frequency of shots. Gender differences were ascertained by Pearson's chi-squared test for independence with Bonferroni corrections. Statistical significance of the results was accepted at p < 0.05. Results. No statistically significant gender differences were found for any parameter. Goalkeepers were most efficient (M: 23.0 ± 6.1%; F: 25.9 ± 18.0%) when receiving inflight shots. The most frequent shooting area was the front (M: 328 shots; F: 194 shots) and most shots reached lower corners of the goal (M: 139 shots; F: 77 shots). Conclusions. No differences between genders were found during semifinal and final phases of the tournament. Notational analysis proved to be a valuable tool for better coaching through the interpretation of shots in beach handball and it may be useful to examine all the aspects related to shooting, such as the shooting area and the goal area. [ABSTRACT FROM AUTHOR]