Competitive Basketball Research Articles

Physiological characteristics of students during the functional state "pre-start fever"

The article is devoted to determining the physiological characteristics of a trained and untrained organism during the functional state of " pre- start fever". The pre-start state is the increasing of a number of physiological functions before the start of competitive work, despite the fact that the organism is still in a state of rest at this time. Subjectively, it is perceived by the athlete as a feeling of excitement at the start. According to the physiological characteristics of the central nervous system functional state and its reflex excitability, the pre-start state is divided into the following types: pre-start fever, state of readiness and pre-start apathy. The research contingent consisted of 40 male and female students of Lutsk Pedagogical College aged 16-20. On the other hand the control group consisted of 20 students of the "Primary Education" specialty, who are not professionally engaged in sports, the experimental group consisted of 20 students of the "Physical Culture and Sports" specialty. The experiment took place during basketball competitions between academic groups at the college, which brought the results as close as possible to real competitive activity. Significant increasing in heart rate and decreasing in the time of breathing during inhalation and exhalation immediately before the start of the competition indicates the body transformation to the pre-start state. Such dynamics of functional indicators is expressed somewhat less in trained students, than in the control group of untrained students, which is clearly consistent with the pre-start self-assessment indicators of three different components. Among the students of the control and experimental groups, most were in a state of "readiness". More individuals in the control group than in the experimental group were in the state of "pre-start fever". Among the most important physiological signs of the state of "pre-start fever" in trained and untrained students were the increasing in heart rate and the increasing in breathing rate.

Kunci Sukses Timnas Bola Basket Putra Sea Games 2021 Vietnam (Literature Review)

The purpose of this research is as the main study material. on the achievements of the Men's Basketball National Team in winning a gold medal at the 2022 Sea Games. The study in this research is the keys to success in the Men's Basketball National Team as seen from nursery, coaching and organizational management at Perbasi. So it is hoped that the results of this research can be used as one of the study materials to develop basketball in Indonesia. This research was conducted at the 2022 sea games multi-event event which took place on May 16-22 2022. The data source used is secondary data from the statistical results of the 2022 sea games basketball competition on the website https://www.sofascore.com/ id/philippines-indonesia/Zgxsbhx, secondary data used for field goal match analysis, 2 points made, 3 point field goals, free throws, total rebounds, assists, steals, blocks, turn overs, and points from turn overs. the results of the analysis regarding the statistical analysis of the final sea games basketball match which has been discussed in the discussion, the conclusion in this study states that. There are 3 winning factors, namely field goals, turnover and assists.

Impacts of mental fatigue and sport specific film sessions on basketball shooting tasks

ABSTRACT Purpose The aim of this investigation was to examine the impact of mental fatigue on basketball specific shooting performance, utilising the newly developed basketball Standardized Shooting Task (SST). Methods Fifteen male elite NCAA Division 1 collegiate basketball players (Age 20.2 ± 1.2 y, height 199.3 ± 7.1 cm, body mass 93.1 ± 8.6 kg) volunteered to participate in a randomised, counterbalanced crossover design undergoing three conditions (Control, Stroop, and Film). The task, performed on three consecutive days, was comprised of 60 free throw attempts followed by a 4-minute spot-to-spot shooting. Results Visual Analog Scales revealed significantly higher levels of mental fatigue following the Stroop (54.2 ± 24.5) condition compared to the Control (24.5 ± 16.2) and higher levels of mental effort in the Stroop (61.0 ± 31.3) and Film (49.9 ± 27.7) compared to the Control (14.0 ± 18.5). No significant differences were observed for Motivation among groups (p > 0.05). There was a significant decrease (p = 0.006) in number of shots made in 4-minutes (MAKE4MIN; control = 49.5 ± 10.2, Stroop = 44.0 ± 10.6, and Film = 45.1 ± 11.7) and shots missed in 4-minutes (MISS4MIN; control = 27.3 ± 7.0, Stroop = 30.9 ± 7.1, and Film = 30.9 ± 7.6). No significant differences were detected for any other performance variables. Conclusion These data demonstrate that mental fatigue negatively impacts basketball shooting performance in elite collegiate basketball players. We suggest that practitioners and coaches encourage athletes to abstain from cognitively demanding tasks prior to basketball competition.

DIFFERENCES IN GAME-RELATED STATISTICS BETWEEN WINNING AND LOSING TEAMS IN NCAA DIVISION-II MEN’S BASKETBALL

Knowing how to design training regimens and modify offensive and defensive strategies to accurately resemble on-court competitive demands can help the team secure the winning game outcome. Thus, the purpose of the present study was to examine differences in game-related statistics between winning and losing teams at the National Collegiate Athletic Association (NCAA) Division-II level of men’s basketball competition and determine which performance parameters have the greatest impact in differentiating between winning and losing game outcomes. The data scraping technique was used to obtain publicly available box scores during the 2018-19 competitive season. The total number of games examined in the present investigation was 4630. The findings of the present study indicate that winning teams: a) made more field-goal and three-point shots; b) attempted and made more free-throw shots; c) attained superior free-throw, two-point, and three-point shooting efficiency; d) accumulated more assists, steals, blocks, and offensive, defensive, and total rebounds; e) had fewer turnovers and personal fouls. Moreover, field-goal percentage, defensive rebounds, and assists showed to be the top three game-related statistics capable of discriminating winning from losing game outcomes on the NCAA Division-II level of competition, accounting for 17.0%, 12.7%, and 12.6% of the total percentage of the explained variance, respectively.

Research on the Development Mode Status Analysis and Optimization Strategy of the NBA

In 1949, the National Basketball League became the National Basketball Association (NBL). The league’s corporate offices, located at 645 Fifth Avenue in New York City’s Olympic Tower, serve as the base of operations for its numerous corporate executives. The All-Star Game, an amateur basketball competition held in February by the National Basketball Association, features 24 of the best players in the league. It is the main event of the three-day NBA All-Star Week, which runs from Friday to Sunday. However, what makes these athletes practice so much? In essence, Basketball is both livelihood & occupation of choice for such athletes. These players enjoy playing the game but are well compensated for their labor. They must also practice daily to keep great basketball talents at a high level if players want to maintain their NBA professions successfully. The research on the NBA’s development mode status analysis and optimization approach is explained in detail in this paper.

Research on the Fan Composition and Consumption Behaviour of CUBA and NCAA

Since China successfully hosted the CUBA China University Basketball League for the first time in 1998, China’s college basketball development has achieved breakthrough achievements. Among the major colleges and universities in all regions of the country, the CUBA league has brought Basketball, a sport full of competitive sports charm and passion, into the lives of more and more students. However, because the league has only a history of more than 20 years since its establishment, the level of basketball competition among universities in various regions in China is seriously uneven. The gap is large, and the CUBA league is still in its infancy and early development stages. The various competition systems of the league, Management approaches, and how talent is introduced and balanced still need to be improved. This paper deeply analyzes the problems existing in CUBA through specific typical case analysis methods, literature research methods, and other methods. The results show that CUBA lacks venue interiors, technology, and other hardware facilities. The league system is too chaotic and inconvenient to manage; the difference in strength between leagues at all levels and universities is too great, resulting in low fans watching the game and other issues that CUBA should learn from the NCAA. This paper also makes strategic analyses and suggestions for the CUBA league, such as adjusting the competition system, delegating power to the government, increasing the infrastructure construction of venues, and balancing the average strength of players in various colleges and universities.

Application of Shear-Wave Elastography in the Evaluation of Hamstring Stiffness in Young Basketball Athletes.

Previous literature has postulated a relationship between greater hamstring stiffness and a higher risk of sustaining injury. Shear wave elastography (SWE) presents a relatively new means for non-invasive evaluation of soft tissue elasticity pre- and post- injury or intervention. 1. To establish baseline hamstring stiffness measures for young competitive athletes and (2) determine effect of targeted neuromuscular training (TNMT) on shear wave stiffness of the hamstring. Un-blinded, prospective, non-randomized, cohort study. Six-hundred forty-two lower extremities from 321 high school and collegiate basketball athletes (177 F: 139 M) were examined for hamstring stiffness prior to the start of their competitive basketball season. Teams were cluster assigned to either the control or intervention (TNMT) group. Subjects in the control group underwent regular season activities as directed, with no influence from the research team. For the TNMT group, the research team introduced a hamstring targeted dynamic warm-up program as an intervention focused on activating the hamstring musculature. Collegiate status was significant to hamstring stiffness for both sexes (p ≤ 0.02), but hamstring stiffness did not correlate to age or sex (r2 ≤ 0.08). Intervention was a significant factor to hamstring stiffness when the hip was positioned in extension (p ≤ 0.01), but not in deeper flexion (p = 0.12). This effect was sex-specific as TNMT influenced hamstring stiffness in females (p = 0.03), but not in males (p ≥ 0.13). Control athletes suffered three HAM injuries; TNMT athletes suffered 0 hamstring injuries. Higher SWE measurements correlated with increased risk of injury, male sex, and collegiate athletics. TNMT intervention can lessen muscle stiffness which may reduce relate to injury incidence. Intervention effectiveness may be sex specific. II.

Evaluation of differences in the performance strategies of top and bottom basketball teams utilizing rank-sum ratio comprehensive.

This study aimed to explore common characteristics among top basketball teams, differentiate attacking and defensive performance between top and bottom teams, and correlate attacking and defensive performance with final competition rankings during the 2019 Men's Basketball World Cup, as well as to determine the relationship between performance indicators and the attacking and defensive performance. In addition, the study aimed to determine the attacking and defensive level of the top and bottom eight teams and find their existing problems and shortcomings, to further improve their competitive basketball strength, and also provided valid and reliable information for coaches to conduct targeted training in the future. The rank-sum ratio (RSR) was employed to evaluate the attack, defense, and overall attacking and defensive performance between the top and bottom teams during the 2019 Men's Basketball World Cup. Additionally, an independent sample T-test was conducted to test the difference in performance indicators of attack and defense between the top eight and bottom eight teams. Spearman Rho Correlation was conducted to determine the relationship between the attacking and defensive RSR value and the final competition ranking at the 0.05 confidence level. Pearson Correlation was employed to test the relationship between the performance indicators and the attacking and defensive RSR value at the 0.05 confidence level. According to Spearman and Pearson Correlation, the indicators which contributed most to the attacking and defensive performance, as well as the correlation between attack and defense and the final ranking, can thus be determined. The results showed that the attacking performance of the top eight teams was far better than the bottom eight teams in terms of average points (p = 0.000), 2-point shoot percentage (p = 0.001), 3-point shoot percentage (p = 0.003), free throw percentage (p = 0.001), turnovers (p = 0.012), and assists (p = 0.000), and there was a significant difference (p < 0.05). However, second attack (p = 0.484), fast-break (p = 0.174), and offensive rebounds (p = 0.261) showed no significant difference between the two cohorts (P > 0.05), and the offensive rebounds of the bottom eight teams were better than the top eight teams. Additionally, there was a large gap between the top eight teams and the bottom eight teams in lost points (p = 0.001) and defensive rebounds (p = 0.000), with a very significant difference (p < 0.01). However, steals (p = 0.760), blocks (p = 0.166), and fouls (p = 0.686) had no significant difference between the two cohorts (P > 0.05). Additionally, there was a very significant difference between attack RSR (p = 0.000), defense RSR (p = 0.006), and the overall attack-defense RSR (p = 0.000) of the top eight and bottom eight teams (p < 0.01), and most top teams focused on developing both attack and defense and paid attention to improve the overall attacking and defensive ability. Moreover, there was a significant relationship between the overall attack-defense performance and assists (p = 0.832), rebounds (p = 0.762), turnovers (p = 0.702), 2-point shoot percentage (p = 0.704), defensive rebounds (p = 0.809), fast-break points (p = 0.577), blocks (p = 0.600), and free throw percentage (p = 0.575). This study showed that the top basketball teams focused on developing both attack and defense, and have the common characteristics of strong attack and defense. Whether it was the attack, defense, or overall attacking and defensive ability, there was a significant relationship with the final ranking. Additionally, this study showed that there were very significant differences in both attacking and defensive abilities between the top eight and bottom eight teams, as well as highlighted their respective advantages and disadvantages in attacking and defensive indicators. Besides that, this study found that performance indicators such as assists, defensive rebounds, 2P%, turnovers, FT%, fast-breaks, and blocks were the main factors that distinguish the top and bottom teams, and they had a significant relationship with overall attacking and defensive performance. The above information allows coaches and players to learn the latest developments in competitive basketball, as well as their advantages and disadvantages, to help them organize targeted training in the future.

Performance factors that negatively influence shooting efficiency in women's basketball.

The purpose of the present study was to examine the influence of selected factors (possession duration, game quarter, defensive pressure, shooting distance from the basket, and heart rate level) on shooting efficiency on Under-19 (U19) and senior level of women's basketball competition (second division). The analysis procedures included five U19 and six senior-level games, containing 224 and 252 shooting attempts, respectively. Binary logistic regression identified the opponent's defensive pressure and shooting distance from the basket as significant predictors of shooting efficiency in both categories. When defensive pressure was high, the chance for the missed shot was 3.5 (95% CI; 1.43-8.52) and 3.19 (95% CI; 1.4-7.26) times more likely than it was under the minimum defensive pressure for U19 and senior category, respectively. Shooting efficiency significantly decreased when the horizontal distance from the basket increased. In U19, a chance for a missed shot was 4.63 (95% CI; 2-10.712) and 5.15 (95% CI; 1.91-13.86) times higher for medium and long-distance (respectively), compared to short-range shooting. In the senior category, the chance for the missed shot was 3.9 (95% CI; 1.83-8.31) and 3.27 (95% CI; 1.43-7.52) times higher for medium and long-distance (respectively) when compared to a short distance. The possession duration, game quarter, and heart rate level were identified as insignificant predictors. Therefore, the aforementioned findings suggest that basketball players and coaches may benefit from designing training sessions where the defender puts pressure on the shooting player as in a real game situation and balanced the frequency of shooting from different distances from the basket.

Recovery of the physiological status in professional basketball players using NESA neuromodulation treatment during different types of microcycles in season: A preliminary randomized clinical trial.

The purpose of the study was to describe and compare recovery status after official basketball competition in players who underwent NESA neuromodulation treatment (NNT) in weeks with one or two matches. The recovery parameters of 12 professional male basketball players (mean ± SD, age: 20.6 ± 2.7yr; height: 197.8 ± 11.7cm; and body mass: 89.0 ± 21.2kg) that competed in the LEB Plata (Spanish third division) were monitored 2days after match-play over 6weeks, and included: 1) the Hooper Test, which combines four subjective variables (sleep, stress, fatigue and soreness); 2) common biochemical markers (e.g., testosterone, cortisol and ratio T:C); and 3) lowest heart rate [HR], average HR, HR variability, sleep duration, awake time during night and onset latency before asleep). Players that completed NNT presented differences compared to the control group in sleep data. For instance, the lowest HR (p < 0.001), average HR (p < 0.001) and total awake time (p = 0.04) were significantly reduced in the NNT group. On the contrary, the control group presented greater values than the NNT group in the subjective Hooper Test, although only stress presented significant differences (Control 2.5 ± 1.2 vs. NNT cost or 3.2 ± 0.9; p = 0.01). Additionally, there were no significant differences in recovery parameters between weeks with one or two matches. In conclusion, the results suggest that players that underwent NNT tended to improve their sleep quality. Nevertheless, player's values in the biochemical markers and wellness status remained similar in both groups. The fact that no significant differences were found between weeks with one or two matches could help basketball professionals to determine that a congested schedule does not seem to negatively alter recovery status. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT04939181?term=NCT04939181, NCT04939181.

Flywheel eccentric overload exercises versus barbell half squats for basketball players: Which is better for induction of post-activation performance enhancement?

This study compared the post-activation performance enhancement (PAPE) effects of a flywheel eccentric overload (FEOL) exercise and barbell half squats (BHS) on countermovement jump (CMJ) and 30 m sprint performance. Twelve male collegiate competitive basketball players were enrolled in this study and they implemented two training protocols: barbell half squat (BHS) and flywheel eccentric overload (FEOL) training. The BHS protocol included three intensities of load: low (40% 1RM), medium (60% 1RM), and high (80% 1RM), with each intensity consisting of 5 sets of 3 repetitions. The FEOL protocol included three inertia intensities: low (0. 015 kg∙m2), medium (0.035 kg∙m2), and high (0.075 kg∙m2), with each intensity consisting of 3 sets of 6 repetitions. The measurement time points were before training (baseline) and at 3, 6, 9, and 12 minutes after training. A two-stage (stage-I and stage-II) randomized crossover design was used to determine the acute effects of both protocols on CMJ and sprint performance. At each training intensity, the jump height, jump peak power output (PPO), jump impulse and 30m sprint speed at 3, 6, 9, and 12 minutes after BHS and FEOL training did not change significantly compared to the baseline. A 2-way ANOVA analysis indicated significant main effects of rest intervals on jump height, jump PPO, and jump impulse, as well as 30m sprint speed. The interaction of the Time × protocol showed a significant effect on jump height between BHS and FEOL groups at high intensity in stage-I (F = 3.809, p = 0.016, df = 4) and stage-II (F = 3.044, p = 0.037, df = 4). And in high training intensity, the jump height at 3 (7.78 ± 9.90% increase, ES = 0.561), 6 (8.96 ± 12.15% increase, ES = 0.579), and 9 min (8.78 ± 11.23% increase, ES = 0.608) were enhanced in I-FEOL group compared with I-BHS group (F = 3.044, p = 0.037, df = 4). In stage-II, the impulse and sprint speed of the FEOL group were significantly higher than those of the BHS group at 6, 9, and 12 min under low (FEOL = 0.015kg∙m2, BHS = 40%1RM), medium(FEOL = 0.035kg∙m2, BHS = 60%1RM), and high (FEOL = 0.075kg∙m2, BHS = 80%1RM) intensities. Furthermore, the sprint speed of the two training protocols did not change at different time points. The interaction of Time × training intensity showed lower sprint speeds in the II-BHS group at a high intensity (BHS = 80%1RM) compared to low (BHS = 40%1RM) and medium (BHS = 60%1RM) training intensities, especially at 9 min and 12 min rest intervals. Although barbell half squat training and flywheel eccentric overload training did not provide a significant PAPE effect on explosive power (CMJ and sprint) in male basketball players, FEOL training showed a better potential effect on enhanced CMJ jump performance at the high training intensity.

Game-play affects hamstring but not adductor muscle fibre mechanics in elite U20 basketball athletes

ABSTRACT Muscle tendon unit fibre mechanics of hamstring and adductor strain injuries are not well studied, with factors such as fatigue promoted as risk factors in the absence of mechanistic evidence. In this study, musculoskeletal modelling was used to estimate fibre mechanics of four hamstring (biceps femoris long head, biceps femoris short head, semimembranosus and semitendinosus) and four adductor (adductor brevis, adductor longus, adductor magnus and gracilis) muscles during an anticipated cut task. The cut task was performed by 10 healthy elite male U20 basketball players both before and immediately after they played in one (of four) competitive basketball game. Biceps femoris long head produced significantly lower (p = 0.032) submaximal force post-game in the latter part of swing (30.7% to 35.0% of stride), though its peak force occurred later (37%) and remained unchanged. Semimembranosus produced significantly lower (p = 0.006) force post-game (32.9% to 44.9% of stride), which encompassed the instance of peak force (39%). Neither fibre velocity nor fibre length of the investigated muscles were significantly affected by game-play. These finding suggest that if fatigue is a factor in hamstring and adductor muscle strain injuries and is brought about by game-play, it is unlikely through the fibre mechanisms investigated in this study.

A Classification Method for Thoracolumbar Vertebral Fractures due to Basketball Sports Injury Based on Deep Learning.

Objective There are more and more basketball competitions, to propose a classification method of thoracolumbar fractures to assist in the diagnosis of basketball injuries, to analyze the feasibility of its clinical application, and to improve the recovery rate. Methods From February 2015 to May 2022, 1130 CT images of thoracolumbar fractures admitted to our hospital and affiliated hospital units due to basketball injuries were collected, and the image labeling system uniformly labeled them. All CT images were classified according to the AO spine classification of thoracolumbar injuries. In the ABC-type classification, 935 CT images were used for training and validation to optimize the deep learning system, including 815 training sets and 120 validation sets; the remaining 198 CT images were used as test sets for comparing the deep learning system and clinician's diagnosis. In the classification of subtype A, a total of 523 CT scans can be performed for training and validation to optimize the deep learning system, including 500 training sets and 23 validation sets; the remaining 94 CT images are used as test sets for comparing depth learning systems and clinicians' diagnostic results. Results The deep learning system had a correct rate of ABC classification of fractures in 86.4%, with a kappa coefficient of 0.850 (P < 0.001); the correct rate of subtype A was 85.3%, with a kappa coefficient of 0.815 (P < 0.001). Conclusion The classification accuracy of thoracolumbar fractures based on deep learning is high. The method can assist in diagnosing CT images of thoracolumbar fractures and improve the current manual and complex diagnosis process.

Relationship Between Game Load and Player's Performance in Professional Basketball.

The purpose of the study was to examine the relationships between external and internal loads, and their ratio (efficiency index), with game performance between backcourt and frontcourt professional basketball players. Game loads of 14 basketball players were monitored during 6 games. External load variables measured were total distance (TD); distance >18km·h-1, commonly known as high-speed running (HSR); and number of accelerations (ACC) and decelerations (DEC) >3m·s-2, whereas the internal load variable measured was average heart rate (HRmean). The ratio between external and internal load variables was calculated and defined through 4 efficiency indexes (TD:HRmean, HSR:HRmean, ACC:HRmean, and DEC:HRmean). Furthermore, basketball performance was quantified using game-related statistics. TD presented a small association with basketball performance, whereas the other external load variables and the 4 efficiency indexes calculated showed trivial relationships with game-related statistics. Furthermore, HRmean showed the greatest (small) associations with individual performance (P = .01-.02; r = .19 to .22). Regarding specific positions, the only 2 variables that presented significant differences were DEC (P = .01; d = 0.86) and DEC:HRmean (P = .01; d = 0.81), which showed higher values in backcourt players compared with frontcourt players. The results suggest that the best performances of basketball players during official competition are not associated with higher game loads. This illustrates the necessity to assess basketball performance from a holistic approach and consider more than just external and internal variables to better understand the players' performance during basketball competition.

Impact of Distance and Proficiency on Shooting Kinematics in Professional Male Basketball Players.

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 Distribution of Match Physical Activities Relative to the Most Demanding Scenarios in Professional Basketball Players.

The purpose of this study was to examine the distribution of physical activities relative to the most demanding scenarios across playing positions during official basketball match-play. Twelve professional basketball players were monitored during twelve matches using a local positioning system. Peak physical demands were measured via total distance covered, distance covered >18 km·h-1, and the number of accelerations and decelerations >3 m·s-2 captured over 30- and 60-s rolling averages. The results showed that players were exposed to more than one high-demanding scenario in all variables and time epochs examined. Additionally, total distance covered presented the greatest number of moderate-demanding scenarios (40-80% of most demanding scenarios), whereas distance covered >18 km·h-1, and accelerations and decelerations >3 m·s-2 presented the greatest proportion of low-demanding scenarios (<40% of most demanding scenarios). Regarding positional differences, backcourt players generally experienced a higher number of scenarios than frontcourt players in most variables, especially in total distance covered. For this variable, scenarios between 20 and 70% of most demanding scenarios during the 30-s epoch (p < 0.001; ES = 0.420.78), and scenarios between 50 and 90% of most demanding scenarios during the 60-s epoch (p < 0.001; ES = 0.400.64) showed significant differences between backcourt and frontcourt players. Our data suggest that match physical activities are position-dependent and variable-dependent. In addition, peak physical demands appear to be repeated during basketball competition. These results may be considered by practitioners to complement average values and most demanding scenarios when prescribing individualized training programs to optimize team performance.

Effects Of Fatigue On Lower Extremity Kinetics And Kinematics In Jump-stop Tasks

Non-contact anterior cruciate ligament (ACL) injury is common among athletes. Sudden deceleration in basketball competitions is closely related to non-contact ACL injury. Fatigue has also been considered one of potential injury risk factors according to epidemiological statistics. PURPOSE:To simulate the actual fatigue in basketball competitions and investigate the changes of injury-related lower extremity biomechanical characteristics. METHODS:Twelve male basketball players (age: 20.1 ± 0.6 years old; height: 1.8 ± 0.1 m; weight: 71.4 ± 13.5 kg) were recruited to executive a basketball-specific fatigue protocol. The fatigue protocol consists of a sequence including sprinting, cutting and consecutive vertical jumps. Participants repeated this sequence until they were unable to reach 80% of the maximal height. Participants were required to perform 6 trials of jump-stop tasks before and immediately after the fatigue protocol. Eight high-speed cameras (Motion Analysis Raptor- 4, USA) sampling at 200 Hz were used to collect joint angles. Two force plates (Kistler 9281CA, Switzerland) sampling at 1000 Hz were used to collect ground reaction forces. Joint net moment was calculated by inverse dynamics. All data was smoothed by 13.3 Hz Butterworth low-pass filter with Cortex 2.6. Paired t-test was performed (α =0.05) with SPSS 24.0. RESULTS:Knee flexion angle (73.52 ± 12.21, P = 0.034, Cohen’s d = 1.243) significantly increased post-fatigue at peak stance, so was the approach speed at initial contact (2.78 ± 0.51, P = 0.003, Cohen’s d = 1.333). A decreased hip abduction angle (-7.67 ± 8.57, P = 0.010, Cohen’s d = 0.577) was significantly observed post-fatigue at initial contact. Participants landed with increased vertical ground reaction force (0.245 ± 0.063(BW), P = 0.031, Cohen’s d = 0.667) in kinetics, but the posterior ground reaction force significantly decreased (0.005 ± 0.012(BW), P = 0.014, Cohen’s d = -0.6) at peak vertical ground reaction force. No fatigue-induced difference of lower extremity moment was found in this study. CONCLUSIONS:The influence of fatigue on both kinematics and kinetics of lower extremity during jump-stop tasks indicates an increased ACL injury risk. Research supported by the Education Social Science Foundation Project of the 13th Five-Year Plan of Education in China (BLA180218).

A Real-world Examination of Progressive Imagery Delivery in Competitive Basketball

Effective delivery of imagery training has been studied for some time. Recently, researchers have determined that, in some contexts, Progressive Imagery (PI), in which content is added to the imagery script in phases, can be more effective than Routine Imagery (RI), in which all the imagery content is presented in every session of an imagery program. However, most research to date consists of field studies, lacking ecological validity. We examined the efficacy of a PI program presented to highly-skilled basketball players in league competition across a whole season, using a Single-Case Design (SCD). Participants were five male players from Division 1 of the State Basketball League, who were pre-tested on the Sport Imagery Ability Measure (SIAM) to ensure they had at least moderate imagery ability. We monitored their Free-Throw Shooting (FTS) percentage in every league match of the whole season. The first 4 to 6 matches (Phase A) gave a stable baseline. Phase B, again lasting 4 to 6 matches, involved imagery that focused on static aspects of FTS movements. In Phase C (4 to 6 matches), more complex elements of FTS were added to imagery, including teammates and opponents on court. Phase D, lasting at least 4 matches, introduced imagery of a high-pressure context in which the FTS shot would decide the match. At the end of the season, each participant was interviewed about his experiences with imagery. We employed visual analysis and the split-middle technique to measure performance and self-efficacy. On these measures, all participants improved their FTS from baseline to Phase D, although two performed best in Phase C. Participants reported feeling comfortable with the changing phases, although one commented that he would have preferred the high-pressure imagery earlier, before he faced real high-pressure finals. We concluded that PI was an effective intervention among highly-skilled participants over a full competition season, while timing of high-pressure imagery should be tested prior to crucial season-ending matches.

Training and match demands differ between the regular season and finals in semi-professional basketball.

Basketball competitions often include a scheduled regular season followed by knock-out finals. Understanding training and match demands through the season can help optimize performance and reduce injury risk. This study investigated whether training and/or match demands differed between the regular season and finals, and whether these differences were dependent on player role. Average session intensity and volume and durations of relative exercise intensities (inactive, light, moderate-vigorous, maximal, supramaximal) were quantified during training sessions and matches using accelerometry in two semi-professional basketball teams (n = 23; 10 women, 13 men). Training and match demands were compared between the regular season (training: 445 observations; matches: 387 observations) and finals (training: 113 observations, matches: 75 observations) with consideration of player role (starters, in-rotation bench, out-rotation bench). During finals matches, starters received 4.4 min more playing time (p = 0.03), performed 14% more absolute maximal activity (p < 0.01) and had 8% less relative inactive time (p = 0.02) when compared to the regular season. Out-rotation bench players received 2.1 min less playing time (p < 0.01), performed 33% less absolute maximal activity (p = 0.01) and 57% less absolute supramaximal activity (p < 0.01) in finals when compared to the regular season. During finals training sessions, average training intensity was 5% higher (p = 0.02), absolute moderate-vigorous activity was 3% higher (p = 0.04), relative maximal activity was 12% higher (p < 0.01), and relative inactive time was 5% lower (p = 0.03) when compared to the regular season. These findings suggest starters need to be physically prepared for greater match demands during finals, while out-rotation bench players should supplement their training during finals with extra supramaximal activity to maintain their conditioning levels for matches.

Game statistics that discriminate winning and losing at the NBA level of basketball competition.

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.