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Abstract

Dribble Deficit enables measurement of dribbling speed independent of sprinting speed in collegiate, male, basketball players. J Strength Cond Res XX(X): 000-000, 2019-The aim of this study was to determine the relationships between sprinting and dribbling speed in basketball during linear and change-of-direction (COD) sprints using total dribbling time and Dribble Deficit. Collegiate, male, basketball players (n = 10; 21.0 ± 1.6 years) performed linear and COD sprints with and without dribbling a ball. Linear dribbling sprints were measured for the dominant and nondominant hands, whereas COD dribbling sprints involved bilateral use of hands. Dribble Deficit was determined as the difference between total time (second) during each dribbling trial and the equivalent nondribbling trial for linear and COD sprints. Simple linear regression analyses were performed during linear and COD sprints to determine the relationship (R) and shared variance (R) between (a) sprinting times and total dribbling times and (b) sprinting times and Dribble Deficit. Large to very large, significant relationships were evident between linear sprinting and dribbling time for dominant (R = 0.86; R = 0.74, p = 0.001) and nondominant hands (R = 0.80; R = 0.65, p = 0.005). Trivial relationships were apparent between linear sprinting time and Dribble Deficit with dominant (R = 0.10; R = 0.01, p = 0.778) and nondominant hands (R = 0.03; R = 0.00, p = 0.940). A very large relationship was evident between COD sprinting and dribbling time (R = 0.91; R = 0.82, p < 0.001), whereas a trivial relationship was observed between COD sprinting time and COD Dribble Deficit (R = -0.23; R = 0.05, p = 0.530). Dribble Deficit eliminates the strong influence of sprinting speed on outcome measures typically seen when using tests predicated on total dribbling time. Consequently, Dribble Deficit may be of added use in basketball test batteries to measure dribbling speed across linear and multidirectional movement paths

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... Our sample size encompassed all players in the basketball academy in those age categories and exceeded the minimum number of required participants (i.e. 10 players) based on recommendations in previous investigations assessing Dribble Deficit in basketball players (G*Power; version 3.1.9.2; University of Dusseldorf, Dusseldorf, Germany) (alpha = 0.05; beta = 0.80; coefficient of determination = 0.5) [11,12]. Players were usually completing 3 x 90-min training sessions per week and participating in ~25 matches across the season including participation within academy tournaments and two international tournaments. ...
... R 2 = 0.77-0.82) [11,12]. Therefore, testing protocols that can assess high-speed dribbling skill in isolation from sprinting speed are practically important to determine the dribbling skill of a player. ...
... The Dribble Deficit was developed to counter the limitations of using total performance time when assessing dribbling speed and is defined as the difference between the total performance times to complete sprint trials with and without dribbling across the same movement path [11]. Dribble Deficit has been reported to isolate dribbling speed independently of sprinting speed as trivial-to-moderate relationships have been documented between Dribble Deficit and total performance time during linear and COD sprints [11,12]. ...
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The aims of this study were to a) quantify the relationships between sprinting and dribbling speed measured using dribble time and Dribble Deficit and b) assess the difference between age categories in sprinting and dribbling speed in pre-adolescent basketball players. Pre-adolescent, male basketball players (Total, N = 81; Under-10, n = 32, Under-9, n = 49) completed two trials of different tasks including 20-m linear sprints without dribbling, 20-m linear sprints dribbling with dominant and non-dominant hands, and change-of-direction (COD) sprints with and without dribbling. Sprinting time, dribbling time and Dribble Deficit were then calculated for each trial. Spearman rank correlations were used to assess the relationships between outcome measures for Under-9 and Under-10 players separately and combined. The Mann-Whitney U test with effect sizes (ES) was used to assess differences in outcome measures between Under-9 and Under-10 players. Moderate-to-very large significant relationships (p <0.05) between linear and COD sprinting time and dribbling time using dominant and non-dominant hands were found in Under-9, Under-10 and all players combined. Trivial-to-moderate relationships were found between sprinting time and Dribble Deficit in all age categories across linear and COD paths. Quicker performance times (p <0.05) were found for Under-10 compared to Under-9 players in all outcome measures (ES: small-to-moderate), except for COD sprinting time (p >0.05; ES: small). Dribble Deficit measures dribbling speed independently of sprinting speed across linear and COD paths in pre-adolescent basketball players and differentiates between age categories.
... Most of the studies used the completion time (the total time to cover a Symmetry 2020, 12, 787 2 of 10 specific course) to detect the dribbling [5] and COD performance [2,6] for imbalance purposes. It has been previously observed that completion time might be biased by an individual's sprint capacity either via dribbling [7,8] or changing direction assessment [9,10]. To overcome this issue, dribble and COD deficits have been proposed to provide practitioners with a more valid and isolated measure within a field-based context, limiting the impact of acceleration [7][8][9][10]. ...
... It has been previously observed that completion time might be biased by an individual's sprint capacity either via dribbling [7,8] or changing direction assessment [9,10]. To overcome this issue, dribble and COD deficits have been proposed to provide practitioners with a more valid and isolated measure within a field-based context, limiting the impact of acceleration [7][8][9][10]. ...
... Dribbling and COD are pivotal to successfully compete in youth football [22][23][24] with the former considered a field-based predictor of a player's success in one-to-one duels [25]. Unfortunately, some evidence exists on COD deficit in the current literature [3,9,[26][27][28], there is a dearth of information on dribble deficit [7,8] and no data are available on its asymmetry. The unpredictability of game scenarios, together with inherent factors such as playing position, tactical constraints and players' leg or directional preference, may prompt players choosing predominantly their dominant side (at the expense of the non-dominant one) to address any football-specific maneuver [5]. ...
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This study aimed to examine the agreement between asymmetries of dribble and change of direction (COD) deficits and to determine their potential difference to each other. Sixteen young elite football players were recruited and tested for sprint (over 10 m), dribbling (90°CODdribbling) and COD (90°CODrunning) performance in dominant (fastest) and non-dominant (slowest) directions. Dribble and COD deficits were computed to express dribbling and COD ability without the influence of acceleration. The asymmetric index (AI%) of both dribble and COD deficits were obtained for both directions. The level of agreement between dribble and COD deficits was assessed by Cohen’s kappa statistic (κ). Results showed that AI% measured by dribble and COD deficits presented a poor level of agreement (κ = −0.159), indicating their imbalance did not favor the same direction. Moreover, AI% of the dribble deficit was significantly higher than those of the COD deficit. This study demonstrated that asymmetries in dribbling and change of direction performance (measured by dribble and COD deficit) were not in agreement to favor the same direction, also displaying a significant difference to each other. Practitioners should consider the task-specificity of asymmetry to reduce the imbalance in dribbling and COD performance.
... Similarly, tests that involved dribbling, likely reflecting the skill, were not included. On the other hand, we acknowledge that the endurance capacity as well as the dribbling skill are essential physical demands for basketball players to achieve high performance (Garcia-Gil et al., 2018;Ramirez-Campillo et al., 2019). It is worth noting that some studies have used CODS tests involving intermittent/endurance running (Scanlan et al., 2012;Staunton et al., 2017) or with dribbling during the CODS test Scanlan et al., 2018;Ramirez-Campillo et al., 2019) in basketball players. ...
... On the other hand, we acknowledge that the endurance capacity as well as the dribbling skill are essential physical demands for basketball players to achieve high performance (Garcia-Gil et al., 2018;Ramirez-Campillo et al., 2019). It is worth noting that some studies have used CODS tests involving intermittent/endurance running (Scanlan et al., 2012;Staunton et al., 2017) or with dribbling during the CODS test Scanlan et al., 2018;Ramirez-Campillo et al., 2019) in basketball players. Thus, further research considering these aspects is warranted to develop the optimum CODS test for basketball players, based on various categorizations. ...
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Change of direction speed (CODS) is essential for basketball performance, extensively assessed by various tests. This review aimed to summarize the CODS test varieties for basketball players on publications until 2019 and identify recent trends regarding what types of tests have gained attention in the 2010s. Electronic literature searches were conducted using three databases with relevant keywords. 104 studies were found eligible, conducting CODS tests 159 times in total with 48 test varieties. To facilitate distinctions between the tests, each test was categorized into one of three types based on the distinctive movement characteristics and changing angles as follows: Defensive (involving lateral shuffling), 180°-turn (exerting only 180°-turns), and Cutting (performing diagonal- or side-cut). We then counted the number of publications and adopted times reported per year for each test, and calculated the adoption rate for each categorized test type. The first CODS test performed in basketball players was the T -Test, reported in 1991, and this was the most commonly adopted test (44/159 times). The 2010s saw abrupt increases in the number of publications (1990s-2000s-2010s: 5-9-90) and test varieties (4-7-44). The adoption rates in the 2010s were similar among the three types (i.e., Defensive/180°-turn/Cutting: 37%/30%/33%), with the Cutting type gradually increasing over the last three decades (1990s-2000s-2010s: 0%-9%-33%). These results suggest that while CODS performances in basketball players are increasingly studied with various tests, recent studies give equal weight to all of the three categorized test types, with increasing adoption of the Cutting type, to assess specific CODS performances.
... To assess the physical characteristics of basketball players, it is essential that tests are valid and reliable to ensure basketball practitioners can use the data to make informed decisions regarding training prescription, guiding return to play processes following injury, quantifying individual player progression, profiling and ranking players, and monitoring player performance and fatigue [22][23][24][25][26]. Researchers and practitioners often implement a diverse combination of tests that assess general physical characteristics (e.g., linear sprint speed) [4,27,28], as well as specialised tests that integrate sport-specific skills aimed to replicate certain basketball-specific demands (e.g., dribbling speed tests) [29][30][31]. However, the wide variety of tests and methods implemented can make it difficult to compare the physical characteristics of adult male basketball players within and between different competition levels. ...
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Background As basketball match-play requires players to possess a wide range of physical characteristics, many tests have been introduced in the literature to identify talent and quantify fitness in various samples of players. However, a synthesis of the literature to identify the most frequently used tests, outcome variables, and normative values for basketball-related physical characteristics in adult male basketball players is yet to be conducted. Objective The primary objectives of this systematic review are to (1) identify tests and outcome variables used to assess physical characteristics in adult male basketball players across all competition levels, (2) report a summary of anthropometric, muscular power, linear speed, change-of-direction speed, agility, strength, anaerobic capacity, and aerobic capacity in adult male basketball players based on playing position and competition level, and (3) introduce a framework outlining recommended testing approaches to quantify physical characteristics in adult male basketball players. Methods A systematic review of MEDLINE, PubMed, SPORTDiscus, Scopus, and Web of Science was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify relevant studies. To be eligible for inclusion, studies were required to: (1) be original research articles; (2) be published in a peer-reviewed journal; (3) have full-text versions available in the English language; and (4) include the primary aim of reporting tests used and/or the physical characteristics of adult (i.e., ≥ 18 years of age) male basketball players. Additionally, data from the top 10 draft picks who participated in the National Basketball Association combined from 2011–12 to 2020–21 were extracted from the official league website to highlight the physical characteristics of elite 19- to 24-year-old basketball players. Results A total of 1684 studies were identified, with 375 being duplicates. Consequently, the titles and abstracts of 1309 studies were screened and 231 studies were eligible for full-text review. The reference list of each study was searched, with a further 59 studies identified as eligible for review. After full-text screening, 137 studies identified tests, while 114 studies reported physical characteristics in adult male basketball players. Conclusions Physical characteristics reported indicate a wide range of abilities are present across playing competitions. The tests and outcome variables reported in the literature highlight the multitude of tests currently being used. Because there are no accepted international standards for physical assessment of basketball players, establishing normative data is challenging. Therefore, future testing should involve repeatable protocols that are standardised and provide outcomes that can be monitored across time. Recommendations for testing batteries in adult male basketball players are provided so improved interpretation of data can occur.
... Moreover, PJT can decrease ground reaction times by increasing muscular force output and movement efficiency, thereby positively affecting change-of-direction speed 126 . 127,128 , this trend for change-of-direction speed may be explained by the same underlying mechanisms that account for greater linear sprint improvements among older players, as discussed above. ...
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Background There is a growing body of experimental evidence examining the effects of plyometric jump training (PJT) on physical fitness attributes in basketball players; however, this evidence has not yet been comprehensively and systematically aggregated. Therefore, our objective was to meta-analyse the effects of PJT on physical fitness attributes in basketball players, in comparison to a control condition. Methods A systematic literature search was conducted in the databases PubMed, Web of Science, and SCOPUS, up to July 2020. Peer-reviewed controlled trials with baseline and follow-up measurements investigating the effects of PJT on physical fitness attributes (muscle power, i.e., jumping performance, linear sprint speed, change-of-direction speed, balance, and muscle strength) in basketball players, with no restrictions on their playing level, sex, or age. Hedge's g effect sizes (ES) were calculated for physical fitness variables. Using a random-effects model, potential sources of heterogeneity were selected, including subgroup analyses (age, sex, body mass, and height) and single training factor analysis (programme duration, training frequency, and total number of training sessions). Computation of meta-regression was also performed. Results Thirty-two studies were included, involving 818 total basketball players. Significant (p<0.05) small-to-large effects of PJT were evident on vertical jump power (ES = 0.45), countermovement jump height with (ES = 1.24) and without arm swing (ES = 0.88), squat jump height (ES = 0.80), drop jump height (ES = 0.53), horizontal jump distance (ES = 0.65), linear sprint time across distances ≤10 m (ES = 1.67) and >10 m (ES = 0.92), change-of-direction performance time across distances ≤40 m (ES = 1.15) and >40 m (ES = 1.02), dynamic (ES = 1.16) and static balance (ES = 1.48), and maximal strength (ES = 0.57). The meta-regression revealed that training duration, training frequency and total number of sessions completed did not predict the effects of PJT on physical fitness attributes. Subgroup analysis indicated greater improvements in older compared to younger players in horizontal jump distance (>17.15 years, ES = 2.11; ≤17.15 years, ES = 0.10; p<0.001), linear sprint time >10 m (>16.3 years, ES = 1.83; ≤16.3 years, ES = 0.36; p = 0.010), and change-of-direction performance time ≤40 m (>16.3 years, ES = 1.65; ≤16.3 years, ES = 0.75; p = 0.005). Greater increases in horizontal jump distance were apparent with >2 compared with ≤2 weekly PJT sessions (ES = 2.12 and 0.39, respectively; p<0.001). Conclusion Data from 32 studies (28 of which demonstrate moderate-to-high methodological quality) indicate PJT improves muscle power, linear sprint speed, change-of-direction speed, balance, and muscle strength in basketball players independent of sex, age, or PJT programme variables. However, the beneficial effects of PJT as measured by horizontal jump distance, linear sprint time >10 m, and change-of-direction performance time ≤40 m, appear to be more evident among older basketball players.
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Movement and locomotion have always been key activities for all animals, being related to the most crucial life functions: retrieving food, facing environmental issues and mating. Thus, humans are able to execute fully developed complex upper arms movements and bipedal gaits in order to move and locomote. To further enhance their performance, they started inventing smart passive mechanical tools. This need arose from both intrinsic limitations of their muscle–joint–bone systems and metabolic power availability. Newly invented devices were mainly introduced in order to cope with such constraints. Some of the potential topics and questions regarding symmetry and biomechanics and energetics of passively assisted human movement and locomotion include: how symmetrical/asymmetrical are most performing/economical human-powered assisted locomotion modes on land, water, and air; how did passively assisted locomotion and/or movement (for catching, manipulating, carrying, etc.) evolve over history in terms of symmetry degree; and how symmetrically do man-passive tool complexes best adapt to extreme environmental conditions (viz. different gradients, surfaces, media, etc.). The aim of this Special Issue is to advance knowledge regarding symmetry and biomechanics and energetics of passively assisted human movement and locomotion.
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At every level of play, knee injuries are some of the most common, and often most severe, injuries in basketball. As a result complete and comprehensive rehabilitation is necessary to help players return to their preinjury level of performance and hopefully avoid future injury. This chapter focuses on relevant information for rehabilitation of all knee injuries in basketball players, with notes related to specific injuries.
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Abstract This study investigated the role of maturity timing in selection procedures and in the specialisation of playing positions in youth male basketball. Forty-three talented Dutch players (14.66 ± 1.09 years) participated in this study. Maturity timing (age at peak height velocity), anthropometric, physiological, and technical characteristics were measured. Maturity timing and height of the basketball players were compared with a matched Dutch population. One-sample t-tests showed that basketball players were taller and experienced their peak height velocity at an earlier age compared to their peers, which indicates the relation between maturity timing and selection procedures. Multivariate analysis of variance (MANOVA) showed that guards experienced their peak height velocity at a later age compared to forwards and centres (P < .01). In addition, positional differences were found for height, sitting height, leg length, body mass, lean body mass, sprint, lower body explosive strength, and dribble (P < .05). Multivariate analysis of covariance (MANCOVA) (age and age at peak height velocity as covariate) showed only a significant difference regarding the technical characteristic dribbling (P < .05). Coaches and trainers should be aware of the inter-individual differences between boys related to their maturity timing. Since technical characteristics appeared to be least influenced by maturity timing, it is recommended to focus more on technical characteristics rather than anthropometric and physiological characteristics.
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Purpose: To investigate the reliability and determinants of performance in a new test of planned agility in elite junior basketball players. Methods: Seventeen female (15.1±0.4 y, 176.9±11.2 cm, 65.7±10.9 kg) and 42 male (14.9±0.4 y, 193.7±8.1 cm, 79.0±12.0 kg) elite junior basketball players performed 5 fitness tests presented in a random order, including a 20-m sprint, a planned-agility test, a triple bilateral horizontal countermovement jump, and 2 triple unilateral horizontal countermovement jumps (with each leg separately). The novelty of the planned-agility test is that it included both offensive and defensive movements. The determinants of planned agility were assessed by a stepwise-regression analysis, and the reliability of the new test was evaluated by the intraclass correlation coefficient and the typical error of measurement. Results: The main results show good reliability of the new test of planned agility. In addition, the determinants of planned-agility performance were different between genders, with sprint performance explaining 74.8% of the variance for girls, while unilateral jump performance and body mass were the most important for boys, accounting for 24.0% and 8.9% of the variance, respectively, in planned agility. Conclusions: These results highlight a gender effect on the determinants of planned-agility performance in young elite basketball players and suggest that straight-line sprint and unilateral horizontal tests must be implemented to test elite junior players.
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The purpose of this study was to identify the effect of 4 months of different training modalities on power, speed, skill and anaerobic capacity in 15-16 year old male basketball players. Thirty five Lithuanian basketball players were randomly assigned into three groups: power endurance group (intermittent exercise, PE, n = 12), general endurance group (continuous exercise, GE, n = 11) and control group (regular basketball training, CG, n = 12). The power endurance model was based in basketball game external structure whereas the general endurance model was based in continuous actions that frequently occur during the basketball game. The training models were used for 16 weeks in sessions conducted 3 times a week during 90 minutes each in the competition period. The following tests were performed: 20 m speed run, Squat jump, Countermovement jump, Running-based Anaerobic Sprint Test (RAST), 2 min. shooting test and the Shuttle ball-dribbling test. A 3x2 repeated measures ANOVA revealed no statistically significant differences in the 20 m speed run, Squat jump and Countermovement jump (p > 0.05). On the other hand, RAST showed significant increases in PE, with greater increases during the 5th and 6th runs. The PE training model also produced a significant improvement in the shuttle ball-dribbling test (48.7±1.5 in the pretest, 45.5±1.3 in the posttest, p ≤ 0.05). Globally, our results suggest that both training modalities were able to maintain initial values of speed and power, however, the anaerobic capacity and skill increased only in the players from the power endurance group. Therefore, the power endurance training (intermittent high intensity exercise) may be more beneficial to prepare junior players according to the game cardiovascular and metabolic specific determinants.
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This study aimed to verify the short-term after-effects of a soccer match on senior players' all-out and inter-limb coordination performances. Right before (pre-match) and after (post-match) a match, 10 senior (52.3±10.2years) male soccer players were administered jump (countermovement jump [CMJ]; repeated jump [RJ]), sprint (10m and 10m while dribbling the ball [10mDB]), in-phase (IP) and anti-phase (AP) inter-limb coordination (synchronized hand and foot flexions and extensions at 80, 120, 180bpm). Heart rate (HR) responses, and subjective ratings of perceived exertion (RPE) and muscle pain (RMP) were used to evaluate the intensity of the friendly match. During the match HR>85% of individual HRmax occurred for 50% of playing time. Subjective ratings at the end of the match were 12.9±2.2pt and 2.7±2.2pt for RPE and RMP, respectively. Post-match CMJ, 10m, 10mDB, AP, IP 80bpm, and IP 120bpm performances did not show any difference with respect to pre-match values, whereas improvements (P<0.05) in RJ (pre-match: 17.4±3.9cm; post-match 19.3±4.8cm) and IP 180bpm (pre-match: 30.4±15.1s; post-match: 50.3±18.9s) emerged. These findings indicate that senior soccer players are able to cope with the high demands of match-play and suggest that an acute bout of intense exercise has an arousing effect that counteracts fatigue effects and facilitates the performance of old trained individuals on complex motor behaviors relying on central executive control. In considering that players consider soccer as highly motivating, with advancing years this sport could help players in preserving high mental and physical functions, as well as maintaining active engagement in life through social interactions.
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Abstract We investigated the anthropometric, physiological and maturation characteristics of young players (13-14 years old) associated with being successful in basketball. Body parameters were measured (stature, total body mass, skinfolds and lengths) and physiological capacities were assessed by endurance, sprint (20 m), jump and dribbling tests. Chronological age (CA) was recorded and maturity estimated using predicted age at peak height velocity (APHV). Anthropometric analysis indicated that elite players were taller, heavier and had a higher percentage of muscle. Further, physiological testing showed that these elite players perform better in jump, endurance, speed and agility tests (especially in the agility and ball tests). In addition, these skills are correlated with point average during the regular season. More basketball players born in the first semester of the year are selected and there is a predominance of early-maturing boys among those selected for the elite team. Those who are more mature have advantages in anthropometric characteristics and physiological test results. In conclusion, around puberty, physical and physiological parameters associated with maturity and CA are important in determining the success of basketball players. These findings should be taken into account by trainers and coaches, to avoid artificial bias in their selection choices.
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Abstract Differences in physiological, physical, and technical demands of small-sided basketball games related to the number of players, court size, and work-to-rest ratios are not well characterised. A controlled trial was conducted to compare the influence of number of players (2v2/4v4), court size (half/full court) and work-to-rest ratios (4x2.5 min/2x5 min) on the demands of small-sided games. Sixteen elite male and female junior players (aged 15-19 years) completed eight variations of a small-sided game in randomised order over a six-week period. Heart rate responses and rating of perceived exertion (RPE) were measured to assess the physiological load. Movement patterns and technical elements were assessed by video analysis. There were ∼60% more technical elements in 2v2 and ∼20% more in half court games. Heart rate (86 ± 4% & 83 ± 5% of maximum; mean ± SD) and RPE (8 ± 2 & 6 ± 2; scale 1-10) were moderately higher in 2v2 than 4v4 small-sided games, respectively. The 2v2 format elicited substantially more sprints (36 ±12%; mean ±90% confidence limits) and high intensity shuffling (75 ±17%) than 4v4. Full court games required substantially more jogging (9 ±6%) compared to half court games. Fewer players in small-sided basketball games substantially increases the technical, physiological and physical demands.
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The aim of this study was to investigate the effect of a typical in-season week including four practice sessions and one competitive game on strength, jump and sprint performances in national-level female basketball players. METHODS: Nine female basketball players (24.3±4.1 years old, 173.0±7.9 cm, 65.1±10.9 kg, 21.1±3.8% body fat) participated in ten testing sessions, before and immediately after practices and game (five pre- and five post-tests). Each session involved isokinetic peak torque measurements of the quadriceps and hamstrings of the dominant leg at 60º.s-1, countermovement jump (CMJ) and 20-m sprint. Fluid loss and subjective training load were measured during each practice session, while the frequencies of the main movements performed during the game were recorded. A two-way ANOVA was used to asses the effect of each practice/game and the effect of the day of the week on performances, and the relationship between performance variations and variables recorded during practices/game were analyzed by a Pearson correlation coefficient. RESULTS: Individual sessions induced significant decreases in lower limb strength (from 4.6 to 10.9%, P<0.05), CMJ (12.6% to 19.6%, P<0.05) and 20-m sprint (1.3% to 7.3%, P<0.05). Performances returned to baseline before the subsequent pre-test session, except on day 3. CONCLUSION: These impairments in performance highlight that coaches should plan conditioning programmes based on repeated sprint and repeated jump ability, and monitor the recovery of their players' strength, sprint and jump capacities following specific sessions
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To describe the physiological and activity demands experienced by Australian female basketball players during competition. A between-subjects (positional comparison) repeated measures (playing periods) observational experimental design was followed. State-level basketball players (n=12; age: 22.0±3.7 yr; body mass: 72.9±14.2 kg; stature: 174.2±6.9 cm; body fat: 17.2±5.6%; estimated V˙O(2max):43.3±5.7 ml  kg⁻¹ min⁻¹) volunteered to participate. Heart rate (HR) and blood lactate concentration ([BLa]) were collected across eight competitive matches. Overall and positional player activity demands were calculated across three matches using time-motion analysis methodology. Activity frequencies, total durations and total distances were determined for various activity categories. Mean (±SD) HR responses of 162±3b min⁻¹ (82.4±1.3% HR(max)) and 136±6b min⁻¹ (68.6±3.1% HR(max)) were evident across live and total time during matches. A mean [BLa] of 3.7±1.4 mmol L⁻¹ was observed across competition. Player activity demands were unchanged across match periods, with 1752±186 movements performed and 5214±315 m travelled across total live match time. Furthermore, 39±3%, 52±2%, 5±1% and 4±1% of total live time was spent performing low-intensity, moderate-intensity, high-intensity and dribbling activity. Positional comparisons revealed backcourt players performed more ball dribbling (p<0.001) and less standing/walking (p<0.01) and running (p<0.05) than frontcourt players. Together, these findings highlight the high intermittent demands and important contributions of both anaerobic and aerobic metabolic pathways during state-level female basketball competition.
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The purpose of the study was to describe the differences in the activity demands of sub-elite and elite Australian men's basketball competition. Ten elite (age 28.3 ± 4.9 years, mass 97.0 ± 13.9 kg, height 197.4 ± 8.3 cm) and 12 sub-elite (age 26.1 ± 5.3 years, mass 85.9 ± 13.2 kg, height 191.4 ± 7.6 cm) Australian basketball players participated in the study. Player activity was analysed using video-based time-motion analysis across multiple in-season matches. Customized analytical software was used to calculate player activity into frequencies, mean and total durations (s), and mean and total distances (m) for standing/walking, jogging, running, sprinting, low shuffling, high shuffling, and dribbling movements. Only movement frequency was calculated for jumping and upper body activity. Multivariate analysis of variance revealed that elite players performed significantly more total movement changes (P <0.001), and experienced greater activity workloads while jogging (P <0.01) and running (P <0.002). In contrast, sub-elite players performed significantly more standing/walking (P <0.023) and sprinting (P <0.003) activities. These data suggest that elite basketball competition requires a greater intermittent workload and more sustained activity demands, whereas sub-elite competition may involve greater bursts of activity and longer recovery periods. These differences are likely to reflect variations in player skill and fitness, as well as playing structure between playing standards.
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The relationship between running velocity and trunk rotation during normal running and running while dribbling was investigated in 7 male competitive basketball players and 7 male nonplayers. Participants performed a normal 20-m sprint and a 20-m sprint while dribbling a basketball. For the motion analysis, all individuals also performed normal running and running while dribbling at target of their maximal speed of sprinting and dribbling, respectively. Basketball players showed significantly smaller decreases in their running velocity from 85% maximal (target) sprint to 85% maximal (target) dribbling speeds than nonplayers. Furthermore, basketball players rotated their shoulders significantly more during target dribbling than during target running. For all participants, significant positive correlations were found between the decreases in running velocity and shoulder rotation. The results suggested that the basketball players' greater shoulder rotation during dribbling permits their running velocity to decrease less during target dribbling compared to a maximal sprint.
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The aim of the present study was to investigate the effect of playing position on strength, power, speed, and agility performances of women basketball players. Thirty subjects playing at national level participated in this study. They were divided into 3 groups according to playing position: guards (positions 1 and 2), forwards (positions 3 and 4), and centers (position 5). Each subject performed 8 tests presented in a random order: The 30-second Wingate Anaerobic test (WAnT), isokinetic testing of the knee extensors, 2 types of jump tests, a 20-m sprint, the agility T-test, a suicide run, and a basketball chest pass. Statistical differences between playing positions were assessed using a 1-way analysis of variance (ANOVA) and Scheffe post hoc analyses. Results showed that guards performed significantly better than centers for the relative peak and mean power achieved during the WAnT (+13% and +16.9%, respectively), relative peak torque of knee extensors (+19.5%), single-leg jump (+21.8), suicide run (+7.5%), and agility T-test (+6.4%, p < 0.05). In addition, guards achieved significantly better performances than forwards in the suicide run test (+7.1%) and forwards were characterized by a greater peak torque of the knee extensors compared to centers (+22.1%). These results indicate that specific fitness training must be undertaken according to playing position. The ability to perform the suicide run, the single-leg jump, and the different movements involved in the agility T-test must be developed in guards. In contrast, speed over short distances and strength development of lower body and upper body should be performed by all playing positions.
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The aim of this study was 2-fold: a) to describe the physiological and technical characteristics of elite young basketball players, and b) to examine the relationship between certain field and laboratory tests among these players. Thirteen male players of the junior's Basketball National team (age: 18.5 +/- 0.5 years, mass: 95.5 +/- 8.8 kg, height: 199.5 +/- 6.2 cm, body fat: 11.4 +/- 1.9%, means+/-SD) performed a run to exhaustion on the treadmill, the Wingate test and 2 types of vertical jump. On a separate day, the field tests (control dribble, defensive movement, speed dribble, speed running, shuttle run and dribble shuttle run) were conducted. Maximal oxygen uptake (VO2max) and ventilatory threshold were 51.7 +/- 4.8 ml/kg/min and 77.6 +/- 7.0% VO2max, respectively. Maximum power output was 10.7 +/- 1.3 Watts/kg and mean power (Pmean) 8.0 +/- 0.7 Watts/kg. Counter-movement and squat jump height were 40.1 +/- 3.7 and 39.8 +/- 4.0 cm, respectively. Performance in control dribble (13.70 +/- 0.96 s), speed dribble (4.24 +/- 0.75 s), high intensity shuttle run (27.90 +/- 1.04 s) and dribble shuttle run (29.50 +/- 1.22 s) was correlated with Pmean (r=-0.58, r=-0.62, r=-0.56 and r=-0.73, respectively, p<0.05). Percent body fat was negatively correlated with all the above field tests (r=0.63, r=0.57, r=0.66, r=0.65, respectively, p<0.05). These players presented a moderate VO2max and anaerobic power. The significant correlation between Pmean and certain field tests indicates that these tests could be used for the assessment of anaerobic capacity of young basketball players.
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This study evaluated and compared the effectiveness of two different off-season, short-term basketball training programs on physical and technical abilities of young basketball players. Twenty-seven adolescent basketball players (14.7+/-0.5 years; Tanner stage: 3.5+/-0.5) were randomly divided into a specialized basketball training group (SP, n=10), a mixed basketball plus conditioning training group (MX, n=10) and a control group (n=7). Training included five sessions per week (100-120 min each) and was performed for 4 weeks. Maximal oxygen uptake was similarly improved after SP (4.9+/-1.8%) and MX (4.9+/-1.4%), but there was no effect on ventilatory threshold. Peak and mean power output measured during the Wingate test were also improved by a similar magnitude after SP (21+/-5%) and MX (15+/-6%). Trunk muscle endurance was equally increased (SP: 23+/-4%, MX: 25+/-5%), but arms endurance was improved significantly more after MX (50+/-11%) compared to SP (11+/-14%, p<0.05). Performance in four basketball technical skills was similarly increased (by 17-27%) in both groups, with a tendency for greater improvement of the SP groups in the technical skills of shooting and passing. These results indicate that a SP basketball training program, performed exclusively on-court was as effective as a MX training program in terms of aerobic and anaerobic fitness improvement. Furthermore, the decrease of the total on-court training time in the MX group resulted in a tendency for a smaller improvement of basketball technical skills. In conclusion, both SP and MX training are equally effective in order to limit and/or reverse the detraining effects that occur during the off-season in basketball.
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The purpose of this study was to evaluate the reliability and validity of a new test of agility, the reactive agility test (RAT), which included anticipation and decision-making components in response to the movements of a tester. Thirty-eight Australian football players took part in the study, categorized into either a higher performance group (HPG) (n=24) or lower performance group (LPG) (n=14) based on playing level from the previous season. All participants undertook testing of a 10m straight sprint (10mSS), a 8-9m change of direction speed test (CODST), and the RAT. Test-retest and inter-tester reliability testing measures were conducted with the LPG. The intra-class correlation (ICC) of the RAT was 0.870, with no significant (p<0.05) difference between the test results obtained on the first and second test sessions using a t-test. A dependent samples t-test revealed no significant (p<0.05) difference between the test results of two different testers with the same population. The HPG were significantly (p=0.001) superior to those of the LPG on the RAT, with no differences observed on any other variable. The RAT is an acceptably reliable test when considering both test-retest reliability, as well as inter-rater reliability. In addition, the test was valid in distinguishing between players of differing performance level in Australian football, while the 10mSS and CODST were not. This result suggests that traditional closed skill sprint and sprint with direction change tests may not adequately distinguish between players of different levels of competition in Australian football.
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The physical demands of modern basketball were assessed by investigating 38 elite under-19-year-old basketball players during competition. Computerised time-motion analyses were performed on 18 players of various positions. Heart rate was recorded continuously for all subjects. Blood was sampled before the start of each match, at half time and at full time to determine lactate concentration. Players spent 8.8% (1%), 5.3% (0.8%) and 2.1% (0.3%) of live time in high "specific movements", sprinting and jumping, respectively. Centres spent significantly lower live time competing in high-intensity activities than guards (14.7% (1%) v 17.1% (1.2%); p<0.01) and forwards (16.6% (0.8%); p<0.05). The mean (SD) heart rate during total time was 171 (4) beats/min, with a significant difference (p<0.01) between guards and centres. Mean (SD) plasma lactate concentration was 5.49 (1.24) mmol/l, with concentrations at half time (6.05 (1.27) mmol/l) being significantly (p<0.001) higher than those at full time (4.94 (1.46) mmol/l). The changes to the rules of basketball have slightly increased the cardiac efforts involved during competition. The game intensity may differ according to the playing position, being greatest in guards.
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Basketball tests assessing dribbling speed predicated on total performance times are influenced by sprinting speed. This study examines an approach termed Dribble Deficit to counter this limitation by examining the relationships between sprinting and dribbling speed during linear and change-of-direction (COD) tasks measured using total performance time and Dribble Deficit. Ten semi-professional basketball players completed linear sprints and COD sprints with and without dribbling. Dribble Deficit was calculated as the difference between the best time for each dribbling trial and corresponding non-dribbling trial for linear and COD sprints. Large to very large significant relationships (P < 0.05) were evident between linear sprint and dribble times (R = 0.64–0.77, R² = 0.41–0.59), and between COD sprint and dribble times (R = 0.88, R² = 0.77). Conversely, trivial-small relationships were evident between linear sprint time and linear Dribble Deficit (R = 0.01–0.15, R² = 0.00–0.02). A non-significant, moderate, negative relationship was observed between COD sprint time and COD Dribble Deficit (R = −0.45, R² = 0.20). These findings indicate Dribble Deficit provides a more isolated measure of dribbling speed than tests using total performance times. Basketball practitioners may use Dribble Deficit to measure dribbling speed independent of sprint speed in test batteries.
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Purpose: The influence of various factors on training load responses in basketball has received limited attention. This study aimed to examine the temporal changes and influence of cumulative training dose on training load responses and interrelationships during basketball activity. Methods: Ten state-level, Australian, male, junior basketball players completed 4 x 10-min standardized bouts of simulated basketball activity using a circuit-based protocol. Internal training load was quantified using the session rating of perceived exertion (sRPE), summated heart rate zones (SHRZ), Banister's training impulse (TRIMP), and Lucia's TRIMP models. External training load was assessed via measurement of mean sprint and circuit speeds. Temporal training load comparisons were performed between each 10-min bout, while Pearson correlation analyses were conducted across cumulative training doses (0-10, 0-20, 0-30, and 0-40 min). Results: sRPE training load increased (P < 0.05) following the first 10-min bout of basketball activity. sRPE training load was only significantly related to Lucia's TRIMP (r = 0.66-0.69; P < 0.05) across 0-10 and 0-20 min. Similarly, mean sprint and circuit speed were significantly correlated across 0-20 min (r = 0.67; P < 0.05). In contrast, SHRZ and Banister's TRIMP were significantly related across all training doses (r = 0.84-0.89; P < 0.05). Conclusions: Limited convergence exists between common training load approaches across basketball training doses lasting beyond 20 min. Thus, the interchangeability of commonly-used internal and external training load approaches appears dose-dependent during basketball activity, with various psychophysiological mediators likely underpinning temporal changes.
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The aim of this study was to assess elite women's basketball game performance. Five elite women's games (3 Italian first division and 2 Euroleague) were analyzed for individual and team time-motion analyses. The individual analysis evaluated the players' movement patterns with particular focus on high-intensity activity (HIA), sprint activity, and repeated sprint events (RSEs). Team analysis included live time (LT), stoppage time (ST), and their ratio, transfer (TR) phases, and half court and full court actions. The frequency of occurrence of changes of activities was n = 576 ± 110, one every 2.56 seconds of LT. Total HIA was 8.5 ± 1.8% of LT and no significant differences between quarter periods were observed. In general, players performed linear sprints (48.3 ± 2.9%) over 1-5 m distance (56.8 ± 5.6%). The occurrence of RSE was 4.4 ± 1.7, with 58.6 ± 18.5% passive recovery between sprints. Team analysis showed no significant difference between games for LT and ST phases (ratio = 1.18 ± 0.25). For game analysis, LT and ST were 43.4 ± 7.8% and 51.1 ±8.4%, respectively. A difference between games was found for half court actions (p < 0.01) and TR phases (p ≤ 0.05). Moreover, 1 TR and 2 TR were the most performed (45.3 and 23.9%) actions. These results encourage coaches to include repeated sprint ability with mainly linear and short sprints into a comprehensive training program.
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The aim of this investigation was to establish median performance profiles for the six playing positions in elite women's indoor hockey and then identify whether these position-specific profiles could discriminate between qualifying (top four), mid-table and relegated teams in the 2011-2012 England Hockey premier league. Successful passing in relegated teams was significantly lower (P < 0.008) than in mid-table and qualifying teams in four of the five outfield positions. Furthermore, the right backs of qualifying teams demonstrated significantly fewer (P < 0.008) unsuccessful passes (x̃ = 15.5 ± CLs 15.0 and 10.0, respectively) and interceptions (x̃ = 4.0 ± CLs 4.0 and 3.0, respectively) than relegated teams (x̃ = 19.5 ± CLs 21.0 and 17.0; x̃ = 7.5 ± CLs 8.0 and 6.0, respectively). Finally, the right forwards of relegated teams demonstrated significantly fewer (P < 0.008) successful interceptions (x̃ = 4.0 ± CLs 5.0 and 4.0, respectively) than qualifying teams (x̃ = 5.0 ± CLs 6.0 and 3.0, respectively) and significantly more (P < 0.008) unsuccessful interceptions (x̃ = 5.5 ± CLs 6.0 and 4.0, respectively) than mid-table teams (x̃ = 3.0 ± CLs 3.0 and 2.0, respectively). Based on these findings, coaches should adapt tactical strategies and personnel deployment accordingly to enhance the likelihood of preparing a qualifying team. Research should build from these data to examine dribbling, pressing and patterns of play when outletting.
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Examination of activity demands and stoppage durations across game periods provides useful insight concerning fatigue, tactical strategies, and playing pace in team sports such as basketball. Therefore, the aims of this study were to quantify and compare game activity fluctuations across quarters in professional and semi-professional basketball players. Video-based time-motion analyses were conducted across multiple games. Frequencies, total durations (s), total distances (m), and mean velocities (m[BULLET OPERATOR]s) were calculated for low-intensity movement (≤3 m·s), high-intensity movement (>3 m·s), shuffling, and dribbling activity. Frequencies were determined for jumping and upper-body activity; stoppage durations were also calculated. Separate repeated measures analysis of variance and Cohen's d were used to identify significant differences and quantify the effect sizes between game quarters for all outcome measures, respectively. Pearson correlation analyses were performed to determine the relationship between stoppage duration and all activity measures. The results showed significantly (P < 0.05) reduced dribbling (3.09 ± 0.03 vs. 2.81 ± 0.01 m[BULLET OPERATOR]s) and total (2.22 ± 0.04 vs. 2.09 ± 0.03 m[BULLET OPERATOR]s) activity velocities during the third compared to the first quarter in professional players. Furthermore, effect size analyses showed greater decreases in high-intensity (professional: d = 1.7-5.4; semi-professional: d = 0.3-1.7), shuffling (professional: d = 2.3-3.2; semi-professional: d = 1.4-2.1), and total (professional: d = 1.0-4.9; semi-professional: d = 0.3-0.8) activity, and increases in dribbling (professional: d = 1.4-4.7; semi-professional: d = 2.5-2.8) with game progression in professional players. In semi-professional players, stoppage duration was significantly (P < 0.05) related to various low-intensity (R = 0.64-0.72), high-intensity (R = 0.65-0.72), and total (R = 0.63-0.73) activity measures. Although not directly measured, the observed game activity fluctuations were likely due to a combination of physiological (e.g. muscle glycogen depletion, dehydration), tactical (e.g. ball control, game pace), and game-related (e.g. time-outs, player fouls) factors. Basketball coaches can use the provided data to: (i) develop more precise training plans and management strategies; (ii) elevate semi-professional player performance closer to the professional level; and (iii) incorporate tactical strategies to maximize the benefits of stoppages.
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Change of direction (COD) and agility require the integration of multiple components to produce a faster performance. However, the mechanisms contributing to a faster performance without the confounding factor of athlete expertise or gender is currently unknown. Therefore, the purpose of this study was to assess body composition, strength and kinetic profile required for a faster COD and agility performance across multiple directional changes. Six faster and six slower (n=12) elite female basketball athletes completed a maximal dynamic back squat; eccentric and concentric only back squat; isometric mid-thigh pull; whole body scan to determine lean, fat and total mass; 505 COD test; T-Test; and a multidirectional agility test over in-ground force plates to obtain relevant kinetic measures. Group (faster and slower) by test (2x3) MANOVA's with follow up ANOVA's were conducted to examine differences between faster and slower groups and each COD and agility test (p ≤ 0.05). Faster athletes during the 505 COD test produced significantly greater vertical force (p = 0.002) and eccentric and isometric strength capacity (p = 0.001). Faster agility and T-Test athletes demonstrated significantly shorter contact times (p = 0.001), greater propulsive impulse (p = 0.02), isometric strength, and relative lean mass compared to slower athletes. Differences between faster athletes across each test appear to be attributed to the mechanical demands of the directional change, increasing force and impulse application as the degree of directional change increased. These findings indicate that different mechanical properties are required to produce a faster COD and agility performances, and the importance of a greater strength capacity to enable greater mechanical adjustment via force production and body control, during different directional changes.
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To compare game activity demands between female and male semi-professional basketball players. Female (n = 12) and male (n = 12) semi-professional basketball players were monitored across three competitive games. Time-motion analysis procedures quantified player activity into pre-defined movement categories across backcourt (BC) and frontcourt (FC) positions. Activity frequencies, durations, and distances were calculated relative to live playing time (·min-1). Work:rest ratios were also calculated using the video data. Game activity was compared between genders for each playing position and all players. Female players performed at greater running work-rates than males (45.7 ± 1.4 vs. 42.1 ± 1.7 m·min-1, P = 0.05), while male players performed more dribbling than females (2.5 ± 0.3 vs. 3.0 ± 0.2 s·min-1; 8.4 ± 0.3 vs. 9.7 ± 0.7 m·min-1, P = 0.05). Positional analyses revealed female BC players performed more low-intensity shuffling (P = 0.04) and jumping (P = 0.05), as well as longer (P = 0.04) jogging durations than male BC players. Female FC players executed more upper-body activity (P = 0.03) and larger work:rest ratios (P < 0.001) than male FC players. No significant gender differences were observed in the overall intermittent demands, distance traveled, high-intensity shuffling activity, and sprinting requirements during game-play. These findings highlight that gender-specific running and dribbling differences might exist in semi-professional basketball. Further, position-specific variations between female and male basketball players should be considered. These data may prove useful in the development of gender-specific conditioning plans relative to playing position in basketball.
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The aim of this study was to assess elite women's basketball game performance. Five elite women's games (3 Italian 1st division and 2 Euroleague) were analyzed for individual and team time-motion analyses. The individual analysis evaluated the players' movement patterns with particular focus on high intensity activity (HIA), sprint activity, and repeated sprint events (RSEs). Team analysis included live time (LT), stoppage time (ST), and their ratio, transfer (TR) phases, half court and full court actions. The frequency of occurrence of changes of activities was n=576 ± 110, one every 2.56 s of LT. Total HIA was 8.5 ± 1.8% of LT and no significant differences between quarter-periods were observed. In general, players performed linear sprints (48.3 ± 2.9%) over 1-5 m distance (56.8 ± 5.6%). The occurrence of RSE was 4.4 ± 1.7, with 58.6 ± 18.5% passive recovery between sprints. Team analysis showed no significant difference between games for LT and ST phases (ratio = 1.18 ± 0.25). For game analysis, LT and ST were 43.4 ± 7.8% and 51.1 ± 8.4%, respectively. A difference between games was found for half court actions (p<0.01) and TR phases (p<0.05). Moreover, 1TR and 2TR were the most performed (45.3% and 23.9%) actions. These results encourage coaches to include repeated sprint ability with mainly linear and short sprints into a comprehensive training program.
Article
The measurement of fitness qualities relevant to playing position is necessary to inform basketball coaching and conditioning staff of role-related differences in playing groups. To date, sprinting and agility performance have not been compared between playing positions in adult male basketball players. Therefore, the purpose of this study was to describe and compare linear speed, closed-skill agility, and open-skill agility qualities between backcourt (point guard and shooting guard positions) and frontcourt (small forward, power forward, and center positions) semi-professional basketball players. Six backcourt (mean ± SD: age: 24.3 ± 7.9 yr; stature: 183.4 ± 4.0 cm; body mass: 85.5 ± 12.3 kg; VO2max: 51.9 ± 4.8 mL·kg·min) and six frontcourt (27.5 ± 5.5 yr; 194.4 ± 7.1 cm; 109.4 ± 8.8 kg; 47.1 ± 5.0 mL·kg·min) adult male basketball players completed 20-m sprint, closed-skill agility, and open-skill agility performance tests. Magnitude-based inferences revealed backcourt players (5-m, 1.048 ± 0.027 s; 10-m, 1.778 ± 0.048 s; 20-m, 3.075 ± 0.121 s) possessed likely quicker linear sprint times than frontcourt players (5-m, 1.095 ± 0.085 s; 10-m, 1.872 ± 0.127 s; 20-m, 3.242 ± 0.221 s). Conversely, frontcourt players (1.665 ± 0.096 s) held possible superior closed-skill agility performance than backcourt players (1.613 ± 0.111 s). In addition, unclear positional differences were apparent for open-skill agility qualities. These findings indicate linear and change of direction speed might be differently developed across playing positions. Furthermore, position-related functions might similarly depend on aspects of open-skill agility performance across backcourt and frontcourt players. Basketball coaching and conditioning staff should consider the development of position-targeted training drills to improve speed, agility, and cognitive qualities in players.
Article
This study aimed to verify whether basketball players are able to maintain strength (handgrip), jump (countermovement jump [CMJ]), sprint (10 m and 10 m bouncing the ball [10 mBB]), and interlimb coordination (i.e., synchronized hand and foot flexions and extensions at 80, 120, and 180 bpm) performances at the end of their game. Ten young (age 15.7 ± 0.2 years) male basketball players volunteered for this study. During the friendly game, heart rate (HR), rate of perceived exertion (RPE), and rate of muscle pain (RMP) were assessed to evaluate the exercise intensity. Overall, players spent 80% of the time playing at intensities higher than 85% HRmax. Main effects (p < 0.05) for game periods emerged for HR and the number of players involved in a single action, with lower occurrence of maximal efforts and higher involvement of teammates after the first 2 periods. At the end of the game, players reported high (p < 0.05) RPE (15.7 ± 2.4) and RMP (5.2 ± 2.3) values; decreased (p < 0.05) sprint capabilities (10 m: pre = 1.79 ± 0.09 seconds, post = 1.84 ± 0.08 seconds; 10 mBB: pre = 1.81 ± 0.11 seconds, post = 1.96 ± 0.08 seconds); increased (p < 0.05) interlimb coordination at 180 bpm (pre = 33.3 ± 20.2 seconds, post = 43.9 ± 19.8 seconds); and maintained jump (pre = 35.2 ± 5.2 cm, post = 35.7 ± 5.2 cm), handgrip (pre = 437 ± 73 N, post = 427 ± 55 N), and coordinative performances at lower frequencies of executions (80 bpm: pre = 59.7 ± 1.3 seconds, post = 60.0 ± 0.0 seconds; 120 bpm: pre = 54.7 ± 12.3 seconds, post = 57.3 ± 6.7 seconds). These findings indicate that the heavy load of the game exerts beneficial effects on the efficiency of executive and attentive control functions involved in complex motor behaviors. Coaches should structure training sessions that couple intense physical exercises with complex coordination tasks to improve the attentional capabilities of the players.
Article
The purpose of this study was to compare 2 sport-specific field tests common in the training programs of basketball players to a laboratory measure of anaerobic power. Nine 17-year-old members of the Israel National Youth Basketball Team participated in this investigation. Field tests included a countermovement jump (CMJ), a 15-second anaerobic jump test (APJT), and a sprint test to assess anaerobic power (line drill). The line drill was performed 3 times (T1, T2, and T3) with a 2-minute passive rest between each sprint. In addition, all subjects performed a 30-second Wingate anaerobic power test (WAnT) to determine peak power (PP), mean power (MP), and fatigue index (FIWAnT). Kendall tau ([middle dot]) rank correlation analysis revealed moderate positive rank correlations between MP and both T1 and T2 ([middle dot] = 0.61 and 0.54, respectively). No significant rank correlations were observed between PP and the line drill. Significant (p <0.05) positive rank correlations were noted between CMJ and both PP and MP ([tau] = 0.59 and 0.76, respectively). However, only a poor relationship (p > 0.05) was observed between APJT and both PP and MP ([tau] = 0.20 and 0.28, respectively). These results suggest that the line drill and jump tests may be acceptable field measures of anaerobic power specific for basketball players. (C) 2000 National Strength and Conditioning Association
Article
Chaouachi, A, Manzi, V, Chaalali, A, Wong, DP, Chamari, K, and Castagna, C. Determinants analysis of change-of-direction ability in elite soccer players. J Strength Cond Res 26(10): 2667-2676, 2012-In this study, we examined the components of 2 change-of-direction (COD) ability (CODA) tests in elite-level male soccer players (n = 23, age 19 ± 1 years, height 181 ± 5.7 cm, body mass 73.2 ± 4.1 kg, % body fat 11 ± 2.4). As CODA paradigms, the T-test and 5-m shuttle run-sprint (5mSS) test assumed as describing the opposing ends of the COD complexity in soccer (i.e., general and specific tests, respectively) were considered. Results showed that the anthropometric and muscular performance variables were able to account for ∼45% (p < 0.04) of the common variance of CODA. The T-test performance was explained by 8 variables (adjusted R = 0.45, p = 0.026), with 5mSS, height, knee extensors isokinetic concentric strength at 60°·per second, and right-to-left knee extensors eccentric strength deficit reaching a level of significance in the provided model (p ≤ 0.02). The best-fitting equation for 5mSS performance included 10 variables (adjusted R = 0.48, p = 0.036) of which T-test performance, height, percentage of body fat, and peak power during the countermovement jump resulted significantly affecting the common shared variance (p ≤ 0.03). This study finding showed that the affecting variables of CODA differ according to the test characteristics. Furthermore, the magnitude of the reported associations suggests that currently CODA should be regarded mainly as a task-specific fitness attribute. Further studies are warranted to detect more relevant performance variables to describe CODA. Meanwhile, soccer coaches and fitness trainers are advised to improve players' CODA using training drills that mimic crucial match actions.
Article
The purpose of the present study was to compare the physical attributes of elite men's basketball players according to age and specific individual positional roles. Forty-five players from 3 national basketball teams (Under-18 years, Under-20 years, and Senior) were measured for anthropometry (height, body mass, percentage body fat), explosive power (5 jumps and vertical jump), speed (5-m, 10-m, and 30-m sprint), agility (T-test), strength (bench press and squat 1 repetition maximum [1RM]), and intermittent high-intensity endurance performance (Yo-Yo intermittent recovery test [Yo-Yo IR1]). Data on match frequency, training routines, and playing experience were also collected. Under-18 players were significantly (p < 0.05) shorter and lighter than both Senior and Under-20 players but showed higher (p < 0.05) percentage body fat. Under-20 and Senior players were faster and had better explosive-power and agility (p < 0.05) performances than Under-18 players. Bench press and squat 1RMs were higher in Senior players (p < 0.05) compared with the other groups. There were significant difference in the Yo-Yo IR1 performance among groups (Senior > Under-20 > Under-18, p < 0.05). Centers and power forwards were the tallest and the heaviest (p < 0.05). The Yo-Yo IR1 performance was higher (p < 0.01) in point guards than in centers. Point guards showed also better agility and 5- and 10-m performances. Power forwards and centers were stronger than the rest of players' positions in the bench press 1RM (p < 0.01). These results showed the existence of age and positional role differences in fitness performance in men's basketball. Differences were particularly evident in intermittent high-intensity endurance and agility performance. Sprint training possibly should be individualized when dealing with positional roles in elite men's basketball. Strength and conditioning coaches should use Yo-Yo IR1 to assess specific endurance in players of different age and positional role.
Article
Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.
Article
The purpose of this study was the investigation of the effects of an intensive combined training program based on the pretest scores of a university women's basketball team on their physical, physiological, biomotoric, and technical features. Twenty-four university volunteers were equally divided into two groups: an experiment group (intensive combined training group) and a control (technical training) group. The 10-week intensive combined training program was performed on the experiment group according to their pretest outcomes. Before and at the end of each period of training, which was scheduled four times a week, the physical, physiological, biomotoric, and technical performance of each subject were determined. With respect to the pre- and posttest measurements, the basketball group showed significant differences (p < 0.05) in girth measurements (shoulder, waist, hip, arm, thigh, and calf), in skinfold measurements (percent body fat), in physiological measurements (vital capacity and forced vital capacity), in biomotoric tests (right-left hand grip, dynamic and countermovement jump, sit-up, push-up, 1500-m endurance), and in technique tests (free and inside shooting). It can be concluded that a 10-week intensive combined training program performed on university women basketball players had a significant effect on improving their physical, physiological, biomotoric, and technical features. It proved to be highly recommendable for female basketball players who are preparing for short-term tournaments; the basketball group in this study won a championship.
Article
Based upon the expertise performed by ten basketball professional relative importance coefficients with regard to positions in the game were determined for nineteen performance evaluation criteria. High degree of interobservers agreement was obtained concerning all positions (from 0.91 to 0.98). In concordance with the obtained results the particular play positions were explicitly described, as well as similarities and differences between them were determined from the aspect of the single criteria importance. The following criteria had an above average importance for the: Position 1--levels of defensive pressure, transition defense efficiency, the ball control, passing skills, dribble penetration, outside shots, and transition offence efficiency; Position 2--level of defensive pressure, transition defense efficiency, outside shots, dribble penetration, offence without the ball, and transition offence efficiency; Position 3--transition defense efficiency, outside shots, dribble penetration, offense without the ball, free throws, and transition offence efficiency; Position 4--defensive and offensive rebounding efficiency, inside shots, dribble penetration, efficiency of screening, and free throws; Position 5--defensive and offensive rebounding efficiency, inside shots, dribble penetration, efficiency of screening, drawing fouls and three-point plays, and free throws. The research results could be usefully applied by the basketball practitioners to selecting and following-up players, the teching-learning process directing and improving, the training process programming and the transformational effects controlling.
Article
The purpose of this study was to determine if straight sprint training transferred to agility performance tests that involved various change-of-direction complexities and if agility training transferred to straight sprinting speed. Thirty-six males were tested on a 30-m straight sprint and 6 agility tests with 2-5 changes of direction at various angles. The subjects participated in 2 training sessions per week for 6 weeks using 20-40-m straight sprints (speed) or 20-40-m change-of-direction sprints (3-5 changes of 100 degrees) (agility). After the training period, the subjects were retested, and the speed training resulted in significant improvements (p < 0.05) in straight sprinting speed but limited gains in the agility tests. Generally, the more complex the agility task, the less the transfer from the speed training to the agility task. Conversely, the agility training resulted in significant improvements in the change-of-direction tests (p < 0.05) but no significant improvement (p > 0.05) in straight sprint performance. We concluded that straight speed and agility training methods are specific and produce limited transfer to the other. These findings have implications for the design of speed and agility training and testing protocols.
Article
The aim of this study was to examine the effect of recovery mode on repeated sprint ability in young basketball players. Sixteen basketball players (age, 16.8 +/- 1.2 years; height, 181.3 +/- 5.7 cm; body mass, 73 +/- 10 kg; VO2max, 59.5 +/- 7.9 mL x kg(-1) x min(-1)) performed in random order over 2 separate occasions 2 repeated sprint ability protocols consisting of 10 x 30-m shuttle run sprints with 30 seconds of passive or active (running at 50% of maximal aerobic speed) recovery. Results showed that fatigue index (FI) during the active protocol was significantly greater than in the passive condition (5.05 +/- 2.4, and 3.39 +/- 2.3, respectively, p < 0.001). No significant association was found between VO2peak and FI and sprint total time (TT) in either repeated sprint protocols. Blood lactate concentration at 3 minutes post exercise was not significantly different between the 2 recovery conditions. The results of this study show that during repeated sprinting, passive recovery enabled better performance, reducing fatigue. Consequently, the use of passive recovery is advisable during competition in order to limit fatigue as a consequence of repeated high intensity exercise.
A scale of magnitudes for effect statistics
  • W Hopkins
Hopkins, W. (2002). A scale of magnitudes for effect statistics. Retrieved from http://sportsci.org/resource/stats/effectmag.html.
The influence of basketball dribbling on repeated sprints
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Meckel, Y., Casorla, T., & Eliakim, A. (2009). The influence of basketball dribbling on repeated sprints. International Journal of Coaching Science, 3(2), 43-56.
Effect of recovery mode on repeated sprint ability in young basketball players
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  • E Padua
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Castagna, C, Abt, G, Manzi, V, Annino, G, Padua, E, and D'Ottavio, S. Effect of recovery mode on repeated sprint ability in young basketball players. J Strength Cond Res 22: 923-929, 2008.