Anthropometric and Power-Related Attributes Differ Between Competition Levels in Age-Matched Under-19-Year-Old Male Basketball Players.

PURPOSE: To compare anthropometric and power-related attributes between competition levels in under-19-year-old (U19) male basketball players. METHODS: National-level (n = 7; age: 17.7 [0.5] y), first-division state-level (n = 8; 17.4 [0.4] y), and second-division state-level (n = 8; 17.1 [0.4] y) players from Australian basketball programs participated in this pilot study. Players had various anthropometric attributes (height, standing reach height, wingspan, and body mass) and power-related attributes (isometric midthigh pull, linear sprint, countermovement jump, 1-step vertical jump, standing long jump, repeated lateral bound, and Modified Agility T Test) measured in the preseason. Differences between groups were assessed using 1-way analyses of variance with Tukey post hoc tests and effect sizes (ES) interpreted as trivial, <0.20; small, 0.20 to 0.59; moderate, 0.60 to 1.19; large, 1.20 to 1.99; and very large, ≥2.00. RESULTS: Regarding anthropometric attributes, national-level players possessed greater (P < .05, large-very large) height (ES = 2.09), standing reach height (ES = 1.54), wingspan (ES = 1.45), and body mass (ES = 1.77) than second-division state-level players. For power-related attributes, national-level players possessed greater (P < .05, large-very large) isometric midthigh-pull peak force (ES = 1.46-2.57), sprint momentum (ES = 1.17-2.18), and countermovement jump peak force (ES = 1.73-2.01) than state-level players. Moreover, national-level players demonstrated greater (P < .05) 1-step vertical jump height (ES = 1.95, large) than second division state-level players. CONCLUSIONS: Specific anthropometric and power-related attributes clearly differ between competition levels in U19 male basketball players. This information can inform development of testing protocols, reference ranges, and training programs in practice. Further research is encouraged on this topic to confirm our findings across larger samples of basketball players.

Power-Related Determinants of Modified Agility T-test Performance in Male Adolescent Basketball Players.

ABSTRACT: Scanlan, AT, Wen, N, Pyne, DB, Stojanovic, E, Milanovic, Z, Conte, D, Vaquera, A, and Dalbo, VJ. Power-related determinants of Modified Agility T-test performance in male adolescent basketball players. J Strength Cond Res 35(8): 2248-2254, 2021-Although the Modified Agility T-test (MAT) has been advocated for assessing change-of-direction performance in basketball, the power-related attributes emphasized during the test are unknown. Therefore, the aim of this study was to identify the power-related determinants of the MAT in basketball players. A cross-sectional, descriptive research design was used whereby national- and state-level male adolescent basketball players (n = 24; 17.3 ± 0.5 years) completed a battery of power-related performance tests. The tests administered included the MAT, isometric midthigh pull, 10-m sprint, countermovement jump, 1-step vertical jump, standing long jump, and repeated lateral bound. Associations between performance during the MAT and other tests were quantified, and performance in each test was compared between faster (>50th percentile) and slower (<50th percentile) players in the MAT. The MAT exhibited large correlations (p < 0.05) with standing long jump distance (r = -0.67, R2 = 45%), countermovement jump relative peak force (r = -0.63, R2 = 39%), isometric midthigh pull relative peak force (r = -0.55, R2 = 30%), and 10-m sprint time (r = 0.53, R2 = 28%). The faster group performed better (p < 0.05) during the standing long jump (mean difference; ±90% confidence limits: 0.16; ±0.12 m) and produced greater (p < 0.05) relative peak force during the isometric midthigh pull (2.5; ±2.3 N·kg-1) and countermovement jump (2.1; ±1.8 N·kg-1) than the slower group. The MAT complements other power-related tests used in basketball and stresses basketball-specific, power-related attributes in various movement planes. These data can inform training and testing approaches to optimize change-of-direction performance in basketball.

The Isometric Midthigh Pull in Basketball: An Effective Predictor of Sprint and Jump Performance in Male, Adolescent Players.

PURPOSE: To examine correlations between peak force and impulse measures attained during the isometric midthigh pull (IMTP) and basketball-specific sprint and jump tests. METHODS: Male, adolescent basketball players (N = 24) completed a battery of basketball-specific performance tests. Testing consisted of the IMTP (absolute and normalized peak force and impulse at 100 and 250 ms); 20-m sprint (time across 5, 10, and 20 m); countermovement jump (CMJ; absolute and normalized peak force and jump height); standing long jump (distance); and repeated lateral bound (distance). Correlation and regression analyses were conducted between IMTP measures and other attributes. RESULTS: An almost perfect correlation was evident between absolute peak force attained during the IMTP and CMJ (r = .94, R2 = 56%, P < .05). Moderate to very large correlations (P < .05) were observed between IMTP normalized peak force and 5-m sprint time (r = -.44, R2 = 19%), 10-m sprint time (r = -.45, R2 = 20%), absolute (r = .57, R2 = 33%), normalized (r = .86, R2 = 73%) CMJ peak force, and standing long-jump distance (r = .51, R2 = 26%). Moderate to very large correlations were evident between impulse measures during the IMTP and 5-m sprint time (100 ms, r = -.40, R2 = 16%, P > .05) and CMJ absolute peak force (100 ms, r = .73, R2 = 54%; 250 ms, r = .68, R2 = 47%; P < .05). CONCLUSIONS: The IMTP may be used to assess maximal and rapid force expression important across a range of basketball-specific movements.

Dribble Deficit: A novel method to measure dribbling speed independent of sprinting speed in basketball players.

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.

Power Testing in Basketball: Current Practice and Future Recommendations.

Wen, N, Dalbo, VJ, Burgos, B, Pyne, DB, and Scanlan, AT. Power testing in basketball: Current practice and future recommendations. J Strength Cond Res 32(9): 2686-2700, 2018-Numerous foundational movements performed during basketball are predicated on underlying power-related attributes, including speed, change-of-direction (COD), and jumping. Accordingly, fitness testing batteries for basketball have incorporated an assortment of linear speed tests, COD tests, and jump tests. However, because of the wide variety of testing options, it is difficult for basketball practitioners to select appropriate testing protocols for the assessment of power-related attributes. As a result, there is a need to review the relevant literature to identify game-specific, power-related attributes important in basketball and the most appropriate tests available to assess power-related attributes for basketball practitioners. Therefore, the aims of this review were to: (a) identify essential power-related attributes important in basketball; (b) discuss the suitability of common and novel power-related tests; and (c) provide recommendations for future research and best practice approaches for basketball coaching staff. In this review, we propose a series of novel tests that are more targeted and specific to basketball movements including: (a) 5- and 10-m linear sprints, (b) modified agility T-test, (c) change-of-direction deficit (CODD), (d) lateral bound, (e) Sargent jump, (f) one-step jump, and (g) isometric midthigh pull test. Improved testing of power-related attributes should enable basketball practitioners to develop targeted training plans for enhancing player performance.

Generic and sport-specific reactive agility tests assess different qualities in court-based team sport athletes.

BACKGROUND: Comparisons between reactive agility tests incorporating generic and sport-specific stimuli have been performed only in field-based team sports. The aim of this study was to compare generic (light-based) and sport-specific (live opponent) reactive agility tests in court-based team sport athletes. METHODS: Twelve semi-professional male basketball players (age: 25.9±6.7 yr; stature: 188.9±7.9 cm; body mass: 97.4±16.1 kg; predicted maximal oxygen uptake: 49.5±5.3 mL/kg 7 min) completed multiple trials of a Reactive Agility Test containing light-based (RAT-Light) and opponent-based stimuli (RAT-Opponent). Multiple outcome measures were collected during the RAT-Light (agility time and total time) and RAT-Opponent (decision time and total time). RESULTS: Mean performance times during the RAT-Light (2.233±0.224 s) were significantly (P<0.001) slower than during the RAT-Opponent (1.726±0.178 s). Further, a small relationship was observed between RAT-Light agility time and RAT-Opponent decision time (r10=0.20), while a trivial relationship was apparent between total performance times across tests (r10=0.02). Low commonality was observed between comparable measures across tests (R2=0-4%). CONCLUSIONS: Reactive agility tests containing light-based and live opponent stimuli appear to measure different qualities in court-based team sport athletes. Court-based team sport coaches and conditioning professionals should not use generic and sport-specific reactive agility tests interchangeably during athlete assessments.

The relationships between internal and external training load models during basketball training.

The present investigation described and compared the internal and external training loads during basketball training. Eight semiprofessional male basketball players (mean ± SD, age: 26.3 ± 6.7 years; stature: 188.1 ± 6.2 cm; body mass: 92.0 ± 13.8 kg) were monitored across a 7-week period during the preparatory phase of the annual training plan. A total of 44 total sessions were monitored. Player session ratings of perceived exertion (sRPE), heart rate, and accelerometer data were collected across each training session. Internal training load was determined using the sRPE, training impulse (TRIMP), and summated-heart-rate-zones (SHRZ) training load models. External training load was calculated using an established accelerometer algorithm. Pearson product-moment correlations with 95% confidence intervals (CIs) were used to determine the relationships between internal and external training load models. Significant moderate relationships were observed between external training load and the sRPE (r42 = 0.49, 95% CI = 0.23-0.69, p < 0.001) and TRIMP models (r42 = 0.38, 95% CI = 0.09-0.61, p = 0.011). A significant large correlation was evident between external training load and the SHRZ model (r42 = 0.61, 95% CI = 0.38-0.77, p < 0.001). Although significant relationships were found between internal and external training load models, the magnitude of the correlations and low commonality suggest that internal training load models measure different constructs of the training process than the accelerometer training load model in basketball settings. Basketball coaching and conditioning professionals should not assume a linear dose-response between accelerometer and internal training load models during training and are recommended to combine internal and external approaches when monitoring training load in players.

Training mode's influences on the relationships between training-load models during basketball conditioning.

PURPOSE: To compare perceptual and physiological training-load responses during various basketball training modes. METHODS: Eight semiprofessional male basketball players (age 26.3 ± 6.7 y, height 188.1 ± 6.2 cm, body mass 92.0 ± 13.8 kg) were monitored across a 10-wk period in the preparatory phase of their training plan. Player session ratings of perceived exertion (sRPE) and heart-rate (HR) responses were gathered across base, specific, and tactical/game-play training modes. Pearson correlations were used to determine the relationships between the sRPE model and 2 HR-based models: the training impulse (TRIMP) and summated HR zones (SHRZ). One-way ANOVAs were used to compare training loads between training modes for each model. RESULTS: Stronger relationships between perceptual and physiological models were evident during base (sRPE-TRIMP r = .53, P < .05; sRPE-SHRZ r = .75, P < .05) and tactical/game-play conditioning (sRPE-TRIMP r = .60, P < .05; sRPE-SHRZ r = .63; P < .05) than during specific conditioning (sRPE-TRIMP r = .38, P < .05; sRPE-SHRZ r = .52; P < .05). Furthermore, the sRPE model detected greater increases (126-429 AU) in training load than the TRIMP (15-65 AU) and SHRZ models (27-170 AU) transitioning between training modes. CONCLUSIONS: While the training-load models were significantly correlated during each training mode, weaker relationships were observed during specific conditioning. Comparisons suggest that the HR-based models were less effective in detecting periodized increases in training load, particularly during court-based, intermittent, multidirectional drills. The practical benefits and sensitivity of the sRPE model support its use across different basketball training modes.