The purpose of the present study was to examine differences in game-related statistical parameters between National Basketball Association (NBA) regular and post-season competitive periods and to determine which variables have the greatest contribution in discriminating between winning and losing game outcomes. The data scraping technique was used to obtain publicly available NBA game-related statistics over a three-year span (2016–2019). The total number of games examined in the present investigation was 3933 (3690 regular season and 243 post-season games). Despite small to moderate effect sizes, the findings suggest that NBA teams’ style of play (i.e., tactical strategies) changes when transitioning from the regular to post-season competitive period. It becomes more conservative (i.e., fewer field goal attempts, assists, steals, turnovers, and points scored), most likely due to greater defensive pressure. Discriminant function analysis correctly classified winning and losing game outcomes during the regular and post-season competitive periods in 82.8% and 87.2% of cases, respectively. Two key game-related statistics capable of discriminating between winning and losing game outcomes were field goal percentage and defensive rebounding, accounting for 13.6% and 14.2% of the total percentage of explained variance during the regular season and 11.5% and 14.7% during post-season competitive periods. Also, overall shooting efficiency (i.e., free-throw, 2-point, and 3-point combined) accounted for 23–26% of the total percentage of explained variance.

The countermovement vertical jump (CVJ) is one of the most commonly implemented non-invasive and time-efficient testing modalities for lower-body neuromuscular performance assessment. With more practitioners having access to portable force plates, the purpose of this study was to examine position-specific differences in CVJ force-time metrics within a cohort of elite professional male basketball athletes. Twenty-eight athletes competing in top-tier European basketball leagues volunteered to participate in the present study. Following familiarization with testing procedures and a standardized warm-up protocol, each athlete performed three maximal-effort CVJ on a uni-axial force plate system with hands on the hips during the entire movement. To minimize the possible influence of fatigue, each jump trial was separated by an approximately 15-s rest interval. The mean value across three jumps was used for performance analysis purposes. The findings of the present study reveal notable position-specific differences during the eccentric phase of the CVJ, with centers having greater braking impulse, mean force, and mean power when compared to guards. However, when normalized by body mass, the observed differences during the eccentric phase of the CVJ were nonexistent. On the other hand, no significant differences in absolute mean and peak force and power were detected during the concentric phase of the CVJ. Yet, when normalized by the player’s body mass, centers demonstrated inferior performance than guards for the same force-time metrics. Overall, these findings may help practitioners obtain a better insight into position-specific differences with regards to CVJ force-time characteristics as well as aid with individually tailored training regimen design.

Introduction: This research sought to establish the impact of the change-event of COVID-19 on college athletes and members of other campus groups (eg, marching band, eSports, Reserve Officers Training Corps). The specific purpose was to assess the perceived impact and impact on mental health (eg, depression, anxiety, and stress). Methods: The survey battery presented a total of 37 items. Demographic, sport or groupspecific, and academic-related questions were included alongside the assessment of psychological well-being coming from the Depression Anxiety Stress Scale-21. Results: There were 249 participants completing some or all of the survey battery. It is notable that 172 participants (69.1%) indicated "a lot has changed". Common one-word responses to the experience surrounding this change-event were feeling disappointment, upset, frustrated, sadness, annoyance, and depression. Life events that conjured similar magnitude of emotion included significant injury, surgery, and losing a loved one. There were no differences by sport for the depression subscale, but 110 participants reported elevated scores and females had a higher mean depression subscale score compared with males. Differences between sports for the anxiety subscale were negated when evaluating Bonferroni correction for multiple tests, but 69 participants reported elevated scores and females had a higher mean anxiety subscale score compared with males. There was no difference by sport for the stress subscale, but 77 participants reported elevated scores and females had a higher mean stress subscale score compared with males. Discussion: Authors urge the campus and athletics community to be diligent in monitoring the holistic wellness of college athletes and members of other campus groups. Mainly, we contend it is important to consider that COVID-19 is a significant and widespread changeevent, and other change-events are known to have significant impact. We should consider that COVID-19 may be acutely and longitudinally impactful to the American college student.

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.

Despite exponential growth in popularity over the last decade and recently becoming an Olympic sport, the amount of scientific literature focused on depicting a profile of successful 3×3 basketball players is sparse. Thus, the purpose of this study was to present the physical and performance characteristics of professional 3×3 male basketball players and how they differ between elite and non-elite athletes. The anthropometrics, vertical jump, agility, and sprint performance parameters collected from ten players during regular training sessions were (x¯ ± SD): height (193.7 ± 4.5 cm), weight (89.2 ± 4.1 cm), wingspan (196.5 ± 5.2 cm), squat jump (43.5 ± 4.6 cm), countermovement jump with (53.3 ± 4.4 cm) and without an arm swing (46.3 ± 4.0 cm), reactive strength index (2.4 ± 0.3 m/s), t-test (10.3 ± 0.3 s), 505 drill (2.4 ± 0.2 s), 10 m sprint (1.5 ± 0.1 s), 30 m sprint (4.0 ± 0.3 s), shuttle run (27.7 ± 1.7 s), and bench press (98.2 ± 10.0 kg) and back squat (139.5 ± 17.6 kg) one repetition maximum. Additionally, the average and maximal heart rate (HR) responses during simulated games were 160.6 ± 8.0 and 188.5 ± 6.3 bpm, with players spending 6.3 ± 4.2, 11.4 ± 5.2, 13.9 ± 3.5, 26.4 ± 10.4, and 42.1 ± 10.0% of the total time in HR Zones 1–5, respectively. Interestingly, no statistically significant differences in the aforementioned physical and performance parameters were noted between elite and non-elite players. Overall, the findings of the present study provide coaches, sports scientists, and strength and conditioning practitioners with information that can aid in the athlete selection process, detection of areas for further improvement, and development of training regimens that resemble 3×3 basketball on-court competitive demands.