Basketball is a sport that relies heavily on an athlete’s ability to rapidly decelerate in order to change direction, avoid a defender, or create space. Recent literature has proposed novel ways of measuring maximal horizontal deceleration using radar technology. The aim of this study was to investigate the relationships between different countermovement jump (CMJ) force-time characteristics and metrics related to maximal horizontal deceleration for a sample of professional male basketball players. To gain further insight into performance qualities that influence horizontal deceleration performance, athletes were separated into high- and low-performance groups for all horizontal deceleration metrics, using a median split analysis, and differences in CMJ force-time metrics were investigated between groups. The results revealed no significant correlations between any CMJ force-time metrics and horizontal deceleration performance. However, athletes’ height and body mass were correlated with different deceleration performance measures, such as average deceleration, horizontal deceleration impulse, and time to stop. Higher performing athletes with regards to average horizontal deceleration and horizontal braking impulse relative to body mass generated greater concentric power (effect size (ES) = 1.04, ES = 0.86) and concentric velocities (ES = 1.17, ES = 0.97), as well as greater jump heights (ES = 1.19, ES = 0.99). Reactive Strength Index modified values were also greater in the higher performing group for horizontal braking impulse relative to body mass (ES = 1.06). On the other hand, higher-performing athletes with regard to horizontal braking impulse generated greater eccentric deceleration force (ES = 0.81) and eccentric power values (ES = 0.88) in the CMJ. Findings may be of interest to practitioners physically preparing basketball players for the sport-specific deceleration actions they may encounter.

Strength is one of the key physiological performance attributes related to optimal on-court basketball performance. However, there is a lack of scientific literature studying how strength relates to shooting proficiency, as a key basketball skill capable of discriminating winning from losing game outcomes. Thus, the purpose of the present study was to examine the relationship between maximal upper and lower body strength and free-throw, two-point, and three-point shooting accuracy. Ten males and seven females performed bench press and back squat one repetition maximum (1RM) and basketball shooting testing during two laboratory visits. The shooting protocol consisted of five sets of 15 free-throw, two-point, and three-point shots performed in sequential order. Each set was separated by a 30 min rest interval to minimize the influence of fatigue. Each subject attempted 225 shots, combining for a total of 3825 shots. The average free-throw, two-point, and three-point shooting accuracy for men were 74.5 ± 11.9, 68.4 ± 9.9, and 53.3 ± 14.9%, and for women 79.2 ± 11.2, 65.5 ± 8.4, and 51.2 ± 15.3%, respectively. The average bench press and back squat 1RM for men was 88.2 ± 18.6 and 117.0 ± 21.2 kg, and for women, 40.6 ± 7.5 and 66.9 ± 9.9 kg, respectively. The findings of the present study revealed no significant relationships between maximal upper and lower body strength and basketball shooting performance for both male and female participants. Neither bench press nor back squat 1RM was a good predictor of free-throw, two-point, and three-point shooting performance.

Shooting efficiency is one of the key performance parameters related to securing the desired game outcome at various levels of basketball competition, and it is largely influenced by the biomechanical adjustments incorporated during the preparatory and release phase of the shooting motion. Thus, the purpose of the present study was twofold: (a) to examine the differences in the kinematic characteristics between free-throw, two-point, and three-point shots, and (b) to examine the differences between shooters with excellent (≥80%) and good (<80%) levels of shooting proficiency. A total of 10 professional male basketball players performed 5 free-throw (4.57 m), two-point (5.18 m), and three-point (6.75 m) shots, combining for a total of 150 shots. A high-definition camera recording at 120 fps was used to capture the shooting motion from a sagittal point of view, and video analysis software was used to analyze the kinematic variables of interest. The findings of the present study reveal that the kinematic characteristics during the preparatory phase of the shooting motion remain unchanged between free-throw and two-point shots. Three-point shots required lower elbow positioning, influenced by greater knee and hip flexion when compared to free-throw and two-point shots. The release angle was notably lower for shots attempted beyond the three-point line but remained unchanged between the free-throw and two-point shooting motions. Release height and vertical displacement were significantly greater for two- and three-point shots when compared to free-throw shots, while no difference was observed between the two- and three-point shots. In addition, no significant differences in shooting kinematics were observed between those participants with excellent and good levels of shooting proficiency.

The primary aim of the present study was to investigate how the fatigue induced through a repeat sprint protocol acutely affected different measures of neuromuscular performance. Recreationally trained basketball players (n = 25) volunteered to participate in the study, and performed three countermovement jumps (CMJ), as well as three drop jumps (DJ) prior to a fatiguing repeat sprint protocol. These procedures were repeated two minutes, and 15 minutes, following the protocol. Various force-time metrics were extracted from the jump tasks, and linear mixed models with subject ID as the random factor, and time as the fixed factor were used to investigate changes across the three time points. To account for the performance during the repeat sprint protocol, a second, two factor model was performed with time and repeat sprint ability (RSA) as the fixed factors. Study results indicated that the sample as a whole merely experienced fatigue-induced decreases in jump height from pre-repeat sprint ability protocol (pre-RSA) within the CMJ compared to two minutes post-repeat sprint ability protocol (post-RSA1) and 15 minutes post-repeat sprint ability protocol (post-RSA2), while jump height within the DJ was only significantly different from pre-RSA at post-RSA1. Further, despite the implementation of the fatiguing RSA protocol, over the course of the three time-points, participants seemed to perform the two jump tasks more efficiently, seen through significantly lower contraction times, greater eccentric (ECC) peak power, and greater ECC mean deceleration force within the CMJ following the RSA task. The two-factor model revealed that several significant time*RSA interactions were found for metrics such as ECC peak velocity and peak power in the CMJ, as well as reactive strength index in the DJ. This suggests that the level of RSA influenced changes across CMJ and DJ characteristics and should be accounted for when interpreting fatigue-induced changes in neuromuscular performance.

With advancements in technology able to quantify wide-ranging features of human movement, the aim of the present study was to investigate the inter-device technological reliability of a three-dimensional markerless motion capture system (3D-MCS), quantifying different movement tasks. A total of 20 healthy individuals performed a test battery consisting of 29 different movements, from which 214 different metrics were derived. Two 3D-MCS located in close proximity were utilized to quantify movement characteristics. Independent sample t-tests with selected reliability statistics (i.e., intraclass correlation coefficient (ICC), effect sizes, and mean absolute differences) were used to evaluate the agreement between the two systems. The study results suggested that 95.7% of all metrics analyzed revealed negligible or small between-device effect sizes. Further, 91.6% of all metrics analyzed showed moderate or better agreement when looking at the ICC values, while 32.2% of all metrics showed excellent agreement. For metrics measuring joint angles (198 metrics), the mean difference between systems was 2.9 degrees, while for metrics investigating distance measures (16 metrics; e.g., center of mass depth), the mean difference between systems was 0.62 cm. Caution is advised when trying to generalize the study findings beyond the specific technology and software used in this investigation. Given the technological reliability reported in this study, as well as the logistical and time-related limitations associated with marker-based motion capture systems, it may be suggested that 3D-MCS present practitioners with an opportunity to reliably and efficiently measure the movement characteristics of patients and athletes. This has implications for monitoring the health/performance of a broad range of populations.