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Purpose: To quantify and compare loads encountered in individual training sessions and games during noncongested and congested weeks in semiprofessional women basketball players., Methods: Using an observational, longitudinal design, 12 players from the same team had their external (PlayerLoad, relative PlayerLoad, and total and high-intensity inertial movement analysis variables) and internal load (session rating of perceived exertion [sRPE], sRPE-load, percentage of heart rate peak, and modified summated-heart-rate-zones load) monitored across a regular season. Training and game data were categorized into noncongested (0-1 game) and congested weeks (2-3 games). Linear mixed models and Cohen d effect sizes were used for analyses., Results: Comparisons between training sessions revealed higher (P < .05, d = 1.35-5.33) PlayerLoad, total inertial movement analysis, sRPE, and sRPE-load during training session 1 than training session 2 in congested weeks. Comparisons between training sessions and games revealed higher (P ≤ .001, d = 1.10-1.66) sRPE and sRPE-load during games than training sessions 1 and 2 in noncongested weeks, alongside higher (P ≤ .001, d = 1.87-3.55) sRPE during game 1 than training sessions 1 and 2 in congested weeks. Comparisons between games revealed higher (P < .05, d = 0.57-2.82) loads in game 3 during congested weeks compared with all other games., Conclusions: Training appeared to be tapered in congested weeks, likely to account for upcoming increases in game loading, but remained relatively consistent across sessions during noncongested weeks. Individual game loads remained relatively consistent but were noticeably increased when a third game was played in the week.

Background: Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear., Objectives: The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS)., Methods: PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS., Results: Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s -2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s -1 ) and acceleration/deceleration zones (> 2.0 m·s -2 ); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research., Conclusions: Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice., (© 2024. The Author(s).)

Understanding sleep patterns and behaviors of athletes is essential for developing targeted sleep-based interventions for implementation in practice. However, more than double the number of sleep studies have examined male athletes compared with female athletes, making the current understanding of sleep patterns, behaviors, and interventions among athletes disproportionately indicative of men. Consequently, this review demonstrates the need for more female-specific sleep data among athlete populations due to research inattention and sex-related differences. Specifically, this review identifies variations in sleep patterns and behaviors between male and female athletes, as well as physiological and lifestyle factors that potentially affect sleep patterns and behaviors across the lifespan, specifically in female athletes. In this regard, evidence suggests some female athletes experience longer sleep durations and better objective sleep quality, but similar or worse subjective sleep quality compared with male athletes. Additionally, scheduling training in the morning or throughout the day may benefit sleep in some female athletes. Considering sleep disorders, women may be at greater risk for insomnia and restless legs syndrome compared with men, which may be attributed to pregnancy, as well as a higher prevalence of anxiety and depressive symptoms, iron deficiency without anemia, and use of psychotropic medication among women. Finally, the menstrual cycle, menstrual disorders, oral contraceptive use, and the postpartum period have been shown to exert detrimental effects on sleep patterns and behaviors and should theoretically be considered when monitoring and managing sleep in female athletes., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Although transcriptome profiling has been used in several resistance training studies, the associated analytical approaches seldom provide in-depth information on individual genes linked to skeletal muscle hypertrophy. Therefore, a secondary analysis was performed herein on a muscle transcriptomic dataset we previously published involving trained college-aged men (n = 11) performing two resistance exercise bouts in a randomized and crossover fashion. The lower-load bout (30 Fail) consisted of 8 sets of lower body exercises to volitional fatigue using 30% one-repetition maximum (1 RM) loads, whereas the higher-load bout (80 Fail) consisted of the same exercises using 80% 1 RM loads. Vastus lateralis muscle biopsies were collected prior to (PRE), 3 h, and 6 h after each exercise bout, and 58 genes associated with skeletal muscle hypertrophy were manually interrogated from our prior microarray data. Select targets were further interrogated for associated protein expression and phosphorylation induced-signaling events. Although none of the 58 gene targets demonstrated significant bout x time interactions, ~57% (32 genes) showed a significant main effect of time from PRE to 3 h (15↑ and 17↓, p < 0.01), and ~26% (17 genes) showed a significant main effect of time from PRE to 6 h (8↑ and 9↓, p < 0.01). Notably, genes associated with the myostatin (9 genes) and mammalian target of rapamycin complex 1 (mTORC1) (9 genes) signaling pathways were most represented. Compared to mTORC1 signaling mRNAs, more MSTN signaling-related mRNAs (7 of 9) were altered post-exercise, regardless of the bout, and RHEB was the only mTORC1-associated mRNA that was upregulated following exercise. Phosphorylated (phospho-) p70S6K (Thr389) ( p = 0.001; PRE to 3 h) and follistatin protein levels ( p = 0.021; PRE to 6 h) increased post-exercise, regardless of the bout, whereas phospho-AKT (Thr389), phospho-mTOR (Ser2448), and myostatin protein levels remained unaltered. These data continue to suggest that performing resistance exercise to volitional fatigue, regardless of load selection, elicits similar transient mRNA and signaling responses in skeletal muscle. Moreover, these data provide further evidence that the transcriptional regulation of myostatin signaling is an involved mechanism in response to resistance exercise.

This study aimed to investigate the effect of vitamin D 3 supplementation at a dose of 4,000 IU/day for 6 weeks on serum levels of: 25-hydroxyvitamin D [25(OH)D], bone turnover [osteocalcin and carboxy-terminal telopeptides of crosslinks of type I collagen (CTx-I)], and muscle damage [lactate dehydrogenase (LDH) and creatine kinase (CK)] in middle adolescent (15-18 years) and late-adolescent to early adulthood (19-30 years) female basketball players with inadequate vitamin D status. Participants (N=24) were randomly assigned in a double-blind manner into a vitamin D or placebo group. Data were analyzed using separate 2×2x2 mixed ANOVAs with one within-subjects factor (time) and two between-subjects factors (condition and age). When a significant interaction was observed, the intra-group changes were assessed using paired t tests and Hedge's g . Paired t-tests comparing intra-group changes in the vitamin D condition revealed a non-significant large improvement in 25(OH)D ( p  = 0.06; g = 0.86), non-significant small decreases in CTx-I ( p  = 0.13; g  = -0.22) and CK ( p  = 0.07; g  = -0.26), as well as a significant moderate decrease in LDH ( p  = 0.004; g  = -0.74). Paired t-tests comparing intra-group changes in the placebo condition revealed a significant moderate decline in 25(OH)D ( p <0.001; g  = -0.77), as well as significant small increases in CTx-I ( p  = 0.04; g  = 0.47) and CK ( p  = 0.04; g  = 0.36). Vitamin D 3 supplementation at 4,000 IU/day could be effective in reducing bone resorption and muscle damage in female basketball players with inadequate baseline vitamin D, irrespective of age.

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.

Purpose: To compare weekly training, game, and overall (training and games) demands across phases of the regular season in basketball., Methods: Seven semiprofessional, male basketball players were monitored during all on-court team-based training sessions and games during the regular season. External monitoring variables included PlayerLoad™ and inertial movement analysis events per minute. Internal monitoring variables included a modified summated heart rate zones model calculated per minute and rating of perceived exertion. Linear mixed models were used to compare training, game, and overall demands between 5-week phases (early, middle, and late) of the regular season with significance set at P ≤ .05. Effect sizes were calculated between phases and interpreted as: trivial, <0.20; small, 0.20 to 0.59; moderate, 0.60 to 1.19; large, 1.20 to 1.99; very large, ≥2.00., Results: Greater (P > .05) overall inertial movement analysis events (moderate-very large) and rating of perceived exertion (moderate) were evident in the late phase compared with earlier phases. During training, more accelerations were evident in the middle (P = .01, moderate) and late (P = .05, moderate) phases compared with the early phase, while higher rating of perceived exertion (P = .04, moderate) was evident in the late phase compared with earlier phases. During games, nonsignificant, trivial-small differences in demands were apparent between phases., Conclusions: Training and game demands should be interpreted in isolation and combined given overall player demands increased as the season progressed, predominantly due to modifications in training demands given the stability of game demands. Periodization strategies administered by coaching staff may have enabled players to train at greater intensities late in the season without compromising game intensity.

This study compared the effects of acute caffeine supplementation (3 mg/kg) administered in the morning and evening on performance-related variables in basketball players. Eleven, national-level, adolescent male basketball players underwent field-based fitness testing on four occasions: morning (10:00) with caffeine ingestion (AM CAFF ), morning (10:00) with placebo ingestion (AM PLAC ), evening (21:00) with caffeine ingestion (PM CAFF ), and evening (21:00) with placebo ingestion (PM PLAC ). Fitness testing included of a countermovement jump without arm swing (CMJ), CMJ with arm swing (CMJAS), squat jump (SJ), Lane Agility Drill (LAD), 20-m linear sprint, and Suicide Run with (SRD) and without dribbling (SR). Data were analysed using two-way repeated measures analyses of variance and paired t-tests, with effect sizes (ES) also determined for all pairwise comparisons. Follow-up t-test comparisons revealed that AM CAFF produced small-moderate , significant ( p <0.001), improvements in CMJ (ES = 0.51), CMJAS (ES = 0.40), SJ (ES = 0.51), and SR (ES = -0.45) compared to AM PLAC. AM CAFF also produced a moderate , significantly ( p <0.001) faster LAD (ES = -0.61) compared to PM CAFF . PM PLAC demonstrated small-moderate , significant ( p <0.05) improvements in CMJ (ES = 0.43), CMJAS (ES = 0.48), and 20-m sprint (ES = -0.63) compared to AM PLAC . In contrast, AM PLAC resulted in large, significantly ( p <0.001), faster SRD (ES = -1.46) and SR (ES = -1.59) compared to PM PLAC . Given the ergogenic effects of caffeine during basketball-specific fitness tests appear to be influenced by time of ingestion, basketball practitioners should consider administering caffeine only to players in the morning to improve vertical jump, sprinting, and change-of-direction performance, with no beneficial effects observed with caffeine ingestion in the evening. Highlights The effect of caffeine supplementation on basketball-specific performance related variables were mediated by ingestion time in elite, adolescent basketball players.AMCAFF produced small-moderate improvements in vertical jump, change-of-direction, 20-m linear sprint, and repeated-sprint performance compared to AMPLAC while PMCAFF produced trivial differences in each performance-related variable compared to PMPLAC.Comparisons between ingestion times in the placebo condition revealed vertical jump height and 20-m sprint speed were impaired in the morning compared to the evening, but these time-dependent differences were eliminated when caffeine was consumed in the morning.Basketball practitioners should consider administering caffeine only to players in the morning to improve vertical jump, sprinting, and change-of-direction performance, with no beneficial effects observed with caffeine ingestion in the evening.

Abstract: Stojanović, E, Stojiljković, N, Stanković, R, Scanlan, AT, Dalbo, VJ, and Milanović, Z. Recreational basketball small-sided games elicit high-intensity exercise with low perceptual demand. J Strength Cond Res 35(11): 3151-3157, 2021-The purpose of this study was to describe and compare the internal and external load imposed on players during 1-a-side, 2-a-side, and 3-a-side recreational basketball small-sided games (SSGs). Twelve recreationally active, male college students were monitored across 10 minutes of 1-a-side, 2-a-side, and 3-a-side basketball SSG. Internal load variables included continuous measurement of heart rate (HR) responses, as well as rating of perceived exertion (RPE) and blood lactate concentration (BLa), after each game. External load variables included measurement of the total distance covered as well as the frequency of accelerations and decelerations. Blood lactate concentration and RPE were moderately (p < 0.05) greater in 1-a-side SSG than 3-a-side SSG. Total accelerations and decelerations were higher in 1-a-side and 2-a-side SSG compared with 3-a-side SSG (p < 0.05, moderate-large). All SSG formats resulted in players spending more time (p < 0.05, moderate-large) at higher HR intensities (81-100% HRmax) than lower intensities (≤80% HRmax). Furthermore, players covered greater distances (p < 0.05, large-very large) at lower intensities (0-12 km·h-1) and completed more accelerations and decelerations (p < 0.05, large-very large) at lower intensities (<2 m·s-2) than at higher intensities across SSG formats. Basketball SSG consisting of 1-3 players elicits an intermittent activity profile, promoting the extensive utilization of anaerobic and aerobic metabolism pathways, which potentially can lead to marked improvements in cardiovascular and musculoskeletal fitness in the general population when administered in recreational settings. Moreover, recreational basketball SSG with only 1 player per team elicits higher BLa, RPE, distances covered at low speeds as well as acceleration and deceleration volumes than SSG with 3 players per team., (Copyright © 2019 National Strength and Conditioning Association.)

Abstract: Scanlan, AT, Wen, N, Pyne, DB, Stojanović, E, Milanović, 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., (Copyright © 2019 National Strength and Conditioning Association.)

Abstract: Scanlan, AT, Fox, JL, Milanović, Z, Stojanović, E, Stanton, R, and Dalbo, VJ. Individualized and fixed thresholds to demarcate PlayerLoad intensity zones produce different outcomes. J Strength Cond Res 35(7): 2046-2052, 2021-Individualized approaches to derive intensity zones are yet to be examined using microsensor metrics in basketball. The purpose of this study was to quantify and compare the time spent in different PlayerLoad intensity zones using individualized and fixed approaches during basketball training. Thirteen semiprofessional, male basketball players were monitored across the preparatory training phase. Microsensors recorded the time spent in 6 PlayerLoad intensity zones using individualized and fixed approaches. Individualized zones were calculated relative to the peak instantaneous PlayerLoad response observed in each player across training. Fixed zones were determined following predefined cut-points set in proprietary software. The majority of training time was spent in zones 1-2 (98-99%), with a low proportion of time detected in zones 3-6 (1-2%) across approaches. The fixed approach produced greater training time in zones 2 (11.9 ± 1.2 vs. 9.3 ± 2.4 minutes; very likely large) and 3 (1.7 ± 0.8 vs. 0.8 ± 0.9 minutes; very likely moderate), was an unclear small increase in time spent in zone 1 were apparent using individualized thresholds (76.5 ± 11.2 vs. 72.9 ± 9.6 minutes). Almost certain similar time was spent in zones 4-6 across approaches. Individual analyses showed deviations across players; however, fixed PlayerLoad thresholds produced higher training time in zones 2 (moderate to very large), 3 (moderate to very large), 4 (moderate to large), and 5 (moderate) than the individualized approach in most players. Variations in outcomes between individualized and fixed approaches must be considered when quantifying the time spent working in PlayerLoad intensity zones., (Copyright © 2019 National Strength and Conditioning Association.)

Abstract: Ramirez-Campillo, R, Gentil, P, Moran, J, Dalbo, VJ, and Scanlan, AT. Dribble Deficit enables measurement of dribbling speed independent of sprinting speed in collegiate, male, basketball players. J Strength Cond Res 35(7): 2040-2045, 2021-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 (R2) 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; R2 = 0.74, p = 0.001) and nondominant hands (R = 0.80; R2 = 0.65, p = 0.005). Trivial relationships were apparent between linear sprinting time and Dribble Deficit with dominant (R = 0.10; R2 = 0.01, p = 0.778) and nondominant hands (R = 0.03; R2 = 0.00, p = 0.940). A very large relationship was evident between COD sprinting and dribbling time (R = 0.91; R2 = 0.82, p < 0.001), whereas a trivial relationship was observed between COD sprinting time and COD Dribble Deficit (R = -0.23; R2 = 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., (Copyright © 2019 National Strength and Conditioning Association.)

Purpose: To compare weekly training and game demands according to playing position in basketball players., Methods: A longitudinal, observational study was adopted. Semiprofessional, male basketball players categorized as backcourt (guards; n = 4) and frontcourt players (forwards/centers; n = 4) had their weekly workloads monitored across an entire season. External workload was determined using microsensors and included PlayerLoad™ (PL) and inertial movement analysis variables. Internal workload was determined using heart rate to calculate absolute and relative summated-heart-rate-zones workload and rating of perceived exertion (RPE) to calculate session-RPE workload. Comparisons between weekly training and game demands were made using linear mixed models and effect sizes in each positional group., Results: In backcourt players, higher relative PL (P = .04, very large) and relative summated-heart-rate-zones workload (P = .007, very large) were evident during training, while greater session-RPE workload (P = .001, very large) was apparent during games. In frontcourt players, greater PL (P < .001, very large), relative PL (P = .019, very large), peak PL intensities (P < .001, moderate), high-intensity inertial movement analysis events (P = .002, very large), total inertial movement analysis events (P < .001, very large), summated-heart-rate-zones workload (P < .001, very large), RPE (P < .001, very large), and session-RPE workload (P < .001, very large) were evident during games., Conclusions: Backcourt players experienced similar demands between training and games across several variables, with higher average workload intensities during training. Frontcourt players experienced greater demands across all variables during games than training. These findings emphasize the need for position-specific preparation strategies leading into games in basketball teams.

Purpose: To compare the aerobic capacity of elite female basketball players between playing roles and positions determined using maximal laboratory and field tests., Methods: Elite female basketball players from the National Croatian League were grouped according to playing role (starter: n = 8; bench: n = 12) and position (backcourt: n = 11; frontcourt: n = 9). All 20 players completed 2 maximal exercise tests in a crossover fashion 7 days apart. First, the players underwent a laboratory-based continuous running treadmill test with metabolic measurement to determine their peak oxygen uptake (VO2peak). The players then completed a maximal field-based 30-15 Intermittent Fitness Test (30-15 IFT) to estimate VO2peak. The VO2peak was compared using multiple linear regression analysis with bootstrap standard errors and playing role and position as predictors., Results: During both tests, starters attained a significantly higher VO2peak than bench players (continuous running treadmill: 47.4 [5.2] vs 44.7 [3.5] mL·kg-1·min-1, P = .05, moderate; 30-15 IFT: 44.9 [2.1] vs 41.9 [1.7] mL·kg-1·min-1, P < .001, large), and backcourt players attained a significantly higher VO2peak than frontcourt players (continuous running treadmill: 48.1 [3.8] vs 43.0 [3.3] mL·kg-1·min-1, P < .001, large; 30-15 IFT: 44.2 [2.2] vs 41.8 [2.0] mL·kg-1·min-1, P < .001, moderate)., Conclusions: Starters (vs bench players) and guards (vs forwards and centers) possess a higher VO2peak irrespective of using laboratory or field tests. These data highlight the role- and position-specific importance of aerobic fitness to inform testing, training, and recovery practices in elite female basketball.

Abstract: Scanlan, AT, Madueno, MC, Guy, JH, Giamarelos, K, Spiteri, T, and Dalbo, VJ. Measuring decrement in change-of-direction speed across repeated sprints in basketball: Novel vs. traditional approaches. J Strength Cond Res 35(3): 841-845, 2021-Approaches to quantify decrement in change-of-direction speed during repeated sprints in basketball players have traditionally used total performance time, which is strongly influenced by linear speed. The purpose of this study was to compare performance decrement across change-of-direction sprints using total performance time and a novel approach that better isolates change-of-direction speed, termed change-of-direction deficit (CODD). Semiprofessional basketball players (N = 8; 19.9 ± 1.5 years; 183.0 ± 9.6 cm; 77.7 ± 16.9 kg) completed 12 × 20-m change-of-direction sprints (Agility 5-0-5 trials) with 20-second recoveries between each sprint. Agility 5-0-5 performance time was taken as the duration to cover 5 m immediately before and after (10 m in total) a 180° directional change. Change-of-direction deficit was calculated as the difference between mean 10- and 20-m split time determined during reference 20-m linear sprints in a separate session and Agility 5-0-5 time in each sprint. Performance decrement was calculated for each approach as: ([total time/ideal time] × 100) - 100. Comparisons between approaches were made using a paired-sample t-test, effect size analyses, and magnitude-based inferences. A significantly greater (P < 0.001; effect size = 2.16, very large; almost certainly higher) performance decrement was apparent using CODD (5.99 ± 1.88%) than Agility 5-0-5 performance time (2.84 ± 0.84%). The present findings indicate that change-of-direction speed measured with CODD shows promise in providing different insight and deteriorates more than total performance time during repeated sprints in basketball players. Change-of-direction deficit has potential to better isolate decrements in change-of-direction speed across repeated sprints compared with total performance time., (Copyright © 2018 National Strength and Conditioning Association.)

Purpose: Games-based drills are the predominant form of training adopted during basketball practice. As such, researchers have begun to quantify the physical, physiological, and perceptual demands of different games-based drill formats. However, study methodology has not been systematically reported across studies, limiting the ability to form conclusions from existing research. The authors developed this call to action to draw attention to the current standard of methodological reporting in basketball games-based drill research and establish a systematic reporting standard the authors hope will be utilized in future research. The Basketball Games-Based Drill Methodical Reporting Checklist (BGBDMRC) was developed to encourage the systematic reporting of games-based drill methodology. The authors used the BGBDMRC to evaluate the current methodological reporting standard of studies included in their review published in the International Journal of Sports Physiology and Performance, "A Systematic Review of the External and Internal Workloads Experienced During Games-Based Drills in Basketball Players" (2020), which highlighted this issue. Of the 17 studies included in their review, only 38% (±18%) of applicable checklist items were addressed across included studies, which is problematic as checklist items are essential for study replication., Conclusions: The current standard of methodological reporting in basketball games-based drill research is insufficient to allow for replication of examined drills in future research or the application of research outcomes to practice. The authors implore researchers to adopt the BGBDMRC to improve the quality and reproducibility of games-based drill research and increase the translation of research findings to practice.

Background: Conditioning in the form of football small-sided games (SSG) is being increasingly utilized as a health-promoting and performance-enhancing activity., Objective: The aim of this study was to quantify and compare the physiological responses and activity demands encountered during 3-a-side, 4-a-side, and 5-a-side football SSG in recreational players., Method: Heart rate, blood lactate (BLa), rating of perceived exertion (RPE) and activity demands were measured across 2 × 20-min football sessions played on a 40 × 20-m pitch in 12 recreationally active college students. Data were collected over a period of two weeks using a repeated-measures crossover design., Results: Mean heart rate was higher (moderate) during 5-a-side than 4-a-side (p = 0.02) and 3-a-side SSG (p < 0.001). BLa tended to be higher (small) in 3-a-side compared to 4-a-side (p = 0.12) and 5-a-side SSG (p = 0.46). The total distance covered was lower (large) during 5-a-side than 4-a-side SSG (p = 0.02), while the total number of accelerations (p = 0.01) and decelerations (p = 0.02) were higher (large) during 5-a-side than 4-a-side SSG., Conclusion: These data suggest: 1) 5-a-side SSG require a greater intermittent workload and exacerbated HR responses; 2) 4-a-side SSG require more sustained activity (distance); and 3) 3-a-side SSG result in higher BLa compared to other SSG formats. The observed intermittent workload and exacerbated HR response in 5-a-side SSG were likely due to greater turnover rates with more frequent interceptions. Sustained activity in 4-a-side SSG might be underpinned by format-specific structures permitting optimal team work, while isolated guarding of players in 3-a-side SSG may have exacerbated BLa responses., Competing Interests: The author(s) have no conflicts of interest relevant to this article., (© 2020 The Society of Chinese Scholars on Exercise Physiology and Fitness. Published by Elsevier (Singapore) Pte Ltd.)

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., Competing Interests: The authors declare that they have no conflict of interest., (Copyright © Biology of Sport 2020.)

Basketball athletes possess a higher bone mineral density (BMD) than matched non-athletes and swimming, soccer, and volleyball athletes. Differences appear to be exacerbated with continued training and competition beyond adolescence. The greater BMD in basketball athletes compared to non-athletes, swimming, and soccer athletes is more pronounced in males than females., Purpose: The aim of this study was to examine differences in total and regional bone mineral density (BMD) between basketball athletes, non-athletes, and athletes competing in swimming, soccer, and volleyball, considering age and sex., Methods: PubMed, MEDLINE, ERIC, Google Scholar, and Science Direct were searched. Included studies consisted of basketball players and at least one group of non-athletes, swimming, soccer, or volleyball athletes. BMD data were meta-analyzed. Cohen's d effect sizes [95% confidence intervals (CI)] were interpreted as: trivial ≤ 0.20, small = 0.20-0.59, moderate = 0.60-1.19, large = 1.20-1.99, and very large ≥ 2.00., Results: Basketball athletes exhibited significantly (p < 0.05) higher BMD compared to non-athletes (small-moderate effect in total-body: d = 1.06, CI 0.55, 1.56; spine: d = 0.67, CI 0.40, 0.93; lumbar spine: d = 0.96, CI 0.57, 1.35; upper limbs: d = 0.70, CI 0.29, 1.10; lower limbs: d = 1.14, CI 0.60, 1.68; pelvis: d = 1.16, CI 0.05, 2.26; trunk: d = 1.00, CI 0.65, 1.35; and femoral neck: d = 0.57, CI 0.16, 0.99), swimming athletes (moderate-very large effect in total-body: d = 1.33, CI 0.59, 2.08; spine: d = 1.04, CI 0.60, 1.48; upper limbs: d = 1.19, CI 0.16, 2.22; lower limbs: d = 2.76, CI 1.45, 4.06; pelvis d = 1.72, CI 0.63, 2.81; and trunk: d = 1.61, CI 1.19, 2.04), soccer athletes (small effect in total-body: d = 0.58, CI 0.18, 0.97), and volleyball athletes (small effect in total-body: d = 0.32, CI 0.00, 0.65; and pelvis: d = 0.48, CI 0.07, 0.88). Differences in total and regional BMD between groups increased with age and appeared greater in males than in females., Conclusion: Basketball athletes exhibit a greater BMD compared to non-athletes, as well as athletes involved in swimming, soccer, and volleyball.

Purpose: To systematically quantify the external and internal workloads reported during games-based drills in basketball and identify the effects of different modifiable factors on the workloads encountered., Methods: PubMed, Scopus, MEDLINE, and SPORTDiscus databases were searched for original research published up until January 2, 2019. The search included terms relevant to workload, games-based drills, and basketball. Studies were screened using predefined selection criteria, and methodological quality was assessed prior to data extraction., Results: The electronic search yielded 8,284 studies with 3,411 duplicates. A total of 17 studies met the inclusion criteria for this review, with quality scores ranging from 9 to 10 out of 11. Factors regularly modified during games-based drills among the included studies were team size, playing area, playing and rest time, and game alterations. Games-based drills containing smaller team sizes elicited greater external and internal workloads compared to larger team sizes. Furthermore, full-court games-based drills elicited greater external and internal workloads compared to half-court drills, while continuous games-based drills elicited greater internal workloads compared to intermittent drills., Conclusions: This review provides a comprehensive collation of data indicating the external and internal workloads reported during different games-based drills in various samples of basketball players. Furthermore, evidence is provided for basketball coaches to consider when prescribing games-based drills and modifying factors during drills across the season. Current literature suggests that smaller team sizes and full-court playing areas elicit greater external and internal workloads than larger team sizes and half-court drills, respectively. Furthermore, continuous games-based drills elicit greater internal workloads than intermittent drills.

This study determined whether external workload could be anticipated during 5 vs. 5 games-based drills in basketball. Thirteen semi-professional, male basketball players were monitored during 5 vs. 5 training drills across the season. External workload was determined using PlayerLoad™ (AU∙min -1 ). The reference workload for each drill was calculated across all sessions, using bootstrapping. The bootstrap mean workload and 95% confidence intervals (CI) were then calculated for session 1, sessions 1-2, and continued for remaining sessions (1-3, 1-4, etc.), and were compared with those of the reference workload. The minimum sessions to anticipate workload for each drill was identified when the first normative value fell within ±5% or ±10% of the reference workload 95% CI. The minimum sessions were then tested to determine the accuracy to which workload could be anticipated. Three to four sessions were needed to anticipate workload within ±5%, while 2-3 sessions were needed to anticipate workload within ±10%. External workload was anticipated in 0-55% of future sessions using an error range of ±5%, and in 58-89% of sessions using an error range of ±10%. External workload during 5 vs. 5 games-based drills can be anticipated in most sessions using normative values established during a short-term monitoring period with an error range of ±10%.

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.

Introduction: Repeated-sprinting involves performing frequent short sprints (≤10 s) interspersed with brief recovery periods (≤60 s). Studies involving repeated-sprint protocols have typically employed active or passive recovery modes applied between running and cycling sprints. This review synthesized the literature to determine the acute physiological, perceptual, and performance effects of recovery mode applied between repeated-sprints during running and cycling protocols., Evidence Acquisition: A systematic search was conducted according to PRISMA guidelines. Articles were retrieved from PubMed, Scopus, SPORTDiscus, and MEDLINE databases. Studies were eligible if they: 1) compared active and passive recovery applied between repeated-sprints; 2) examined sprints lasting ≤10 s, and; 3) included ≤60 s recovery between sprints. Nine studies were included in this review. Five of the included studies examined running and four studies examined cycling., Evidence Synthesis: Passive recovery induced less physiological stress (heart rate, oxygen consumption, and changes in oxyhemoglobin), lower perceptual stress (rating of perceived exertion), and reduced performance decrement (sprint time, speed, and sprint decrement) compared to active recovery in all running studies. Findings were equivocal in cycling., Conclusions: Application of passive recovery between running repeated-sprints is recommended to reduce performance decrement than passive recovery. Alternatively, active recovery applied between running repeated-sprints provides greater physiological stress than passive recovery and may be a useful training overload strategy to promote physiological adaptation. The mixed findings for physiological and performance measures in cycling studies suggest further research is required to reach definitive conclusions regarding application of recovery modes between cycling repeated-sprints.

The aim of this study was to determine the effect of acute caffeine supplementation on anaerobic performance in professional female basketball players. A double-blind, placebo-controlled, experimental design was used in a randomized counterbalanced manner. In separate sessions, 10 professional basketball players ingested caffeine (3 mg/kg body mass) or a placebo (dextrose: 3 mg/kg body mass) 60 min before completing countermovement jumps (CMJ) with and without arm swing, a squat jump (SJ), the Lane Agility Drill, 20-m sprints (with 5-m and 10-m split times recorded) with and without dribbling a ball, and a suicide run. Participants provided ratings of perceived exertion (RPE) and ratings of perceived performance 30 min following testing. Data analyses included the use of effect size (ES) and significance. Caffeine supplementation produced small nonsignificant ( p > 0.05) increases in CMJ without arm swing (ES = 0.30), CMJ with arm swing (ES = 0.29), SJ (ES = 0.33), and the lane agility drill (ES = -0.27). Caffeine supplementation produced small to moderate significant improvements in 10-m (ES = -0.63; p = 0.05) and 20-m (ES = -0.41; p = 0.04) sprint times without dribbling. Caffeine supplementation promoted a moderate significant reduction in RPE during the test battery (ES = -1.18; p = 0.04) and a small nonsignificant improvement in perceived performance (ES = 0.23; p = 0.53). Acute caffeine supplementation may produce small to moderate improvements in key performance attributes required for basketball while reducing RPE.

Purpose: To examine the effect of caffeine supplementation on dribbling speed in elite female and male basketball players., Methods: A double-blind, counterbalanced, randomized, crossover design was utilized. Elite basketball players (n = 21; female, n = 10; male, n = 11; age = 18.3 ± 3.3 yr) completed placebo (3 mg·kg-1 of body mass of dextrose) and caffeine (3 mg·kg-1 of body mass) trials 1 week apart during the in-season phase. During each trial, players completed 20-m linear sprints with and without dribbling a basketball. Performance times were recorded at 5-m, 10-m, and 20-m splits. Dribbling speed was measured using traditional (total performance time) and novel (Dribble Deficit) methods. Dribble Deficit isolates the added time taken to complete a task when dribbling compared to a non-dribbling version of the same task. Comparisons between placebo and caffeine conditions were conducted at group and individual levels., Results: Non-significant (P > 0.05), trivial-small (effect size = 0.04-0.42) differences in dribbling speed were observed between conditions. The majority (20 out of 21) of players were classified as non-responders to caffeine, with 1 player identified as a negative responder using Dribble Deficit measures., Conclusions: Results indicate caffeine offers no ergogenic benefit to dribbling speed in elite basketball players. The negative response to caffeine in one player indicates caffeine supplementation may be detrimental to dribbling speed in specific cases and emphasizes the need for individualized analyses in nutrition-based sport science research.

Spiteri, T, Binetti, M, Scanlan, AT, Dalbo, VJ, Dolci, F, and Specos, C. Physical determinants of Division 1 Collegiate basketball, Women's National Basketball League, and Women's National Basketball Association athletes: with reference to lower-body sidedness. J Strength Cond Res 33(1): 159-166, 2019-In female basketball, the assumed components of success include power, agility, and the proficiency at executing movements using each limb. However, the importance of these attributes in discriminating between playing levels in female basketball has yet to be determined. The purpose of this study was to compare lower-body power, change of direction (COD) speed, agility, and lower-body sidedness between basketball athletes participating in Division 1 Collegiate basketball (United States), Women's National Basketball League (WNBL) (Australia), and Women's National Basketball Association (WNBA) (United States). Fifteen female athletes from each league (N = 45) completed a double- and single-leg countermovement jump (CMJ), static jump, drop jump, 5-0-5 COD test, and an offensive and a defensive agility test. One-way analysis of variance with post hoc comparisons were conducted to compare differences in physical characteristics (height, body mass, age) and performance outcomes (jump, COD, agility assessments) between playing levels. Separate dependent t-tests were performed to compare lower-body sidedness (left vs. right lower limbs) during the single-leg CMJ jumps (vertical jump height) and 5-0-5 COD test for each limb within each playing level. WNBA athletes displayed significantly greater lower-body power (p = 0.01-0.03) compared with WNBL athletes, significantly faster COD speed (p = 0.02-0.03), and offensive and defensive agility performances (p = 0.02-0.03) compared with WNBL and Collegiate athletes. The WNBL athletes also produced a faster defensive agility performance compared with Collegiate athletes (p = 0.02). Furthermore, WNBA and WNBL athletes exhibited reduced lower-body sidedness compared with Collegiate athletes. These findings indicate the importance of lower-body power, agility, and reduced lower-body imbalances to execute more proficient on-court movements required to compete at higher playing levels.

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, R 2  = 0.41-0.59), and between COD sprint and dribble times (R = 0.88, R 2  = 0.77). Conversely, trivial-small relationships were evident between linear sprint time and linear Dribble Deficit (R = 0.01-0.15, R 2  = 0.00-0.02). A non-significant, moderate, negative relationship was observed between COD sprint time and COD Dribble Deficit (R = -0.45, R 2  = 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.

Berkelmans, DM, Dalbo, VJ, Fox, JL, Stanton, R, Kean, CO, Giamarelos, KE, Teramoto, M, and Scanlan, AT. Influence of different methods to determine maximum heart rate on training load outcomes in basketball players. J Strength Cond Res 32(11): 3177-3185, 2018-The summated-heart-rate-zones (SHRZ) approach uses heart rate (HR) responses relative to maximum HR (HRmax) to calculate the internal training load (TL). Age-predicted, test-derived, and session-based approaches have all been used to determine HRmax in team sports. The purpose of this study was to determine the effects of using age-predicted, test-derived, and session-based HRmax responses on SHRZ TL in basketball players. Semiprofessional, male basketball players (N = 6) were analyzed during the preparatory training phase. Six age-based approaches were used to predict HRmax including Fox (220 - age); Hossack (206 - [0.567 × age]); Tanaka (208 - [0.7 × age]); Nikolaidis (223 - [1.44 × age]); Nes (211 - [0.64 × age]); and Faff (209.9 - [0.73 × age]). Test-derived HRmax was taken as the highest HR during the Yo-Yo intermittent recovery test (Yo-Yo IRT), whereas session-based HRmax was taken as the higher HR seen during the Yo-Yo IRT or training sessions. Comparisons in SHRZ TL were made at group and individual levels. No significant group differences were evident between SHRZ approaches. Effect size analyses revealed moderate (d = 0.60-0.79) differences between age-predicted, test-derived, and session-based methods across the group and individually in 2 players. The moderate differences between approaches suggest age-predicted, test-derived, and session-based methods to determine HRmax are not interchangeable when calculating SHRZ. Basketball practitioners are encouraged to use individualized HRmax directly measured during field-based tests supplemented with higher HR responses evident during training sessions and games when calculating the SHRZ TL to ensure greatest accuracy.

Purpose: To investigate the physiological and performance effects of active and passive recovery between repeated-change-of-direction sprints., Methods: Eight semiprofessional basketball players (age: 19.9 [1.5] y; stature: 183.0 [9.6] cm; body mass: 77.7 [16.9] kg; body fat: 11.8% [6.3%]; and peak oxygen consumption: 46.1 [7.6] mL·kg -1 ·min -1 ) completed 12 × 20-m repeated-change-of-direction sprints (Agility 5-0-5 tests) interspersed with 20 seconds of active (50% maximal aerobic speed) or passive recovery in a randomized crossover design. Physiological and perceptual measures included heart rate, oxygen consumption, blood lactate concentration, and rating of perceived exertion. Change-of-direction speed was measured during each sprint using the change-of-direction deficit (CODD), with summed CODD time and CODD decrement calculated as performance measures., Results: Average heart rate (7.3 [6.4] beats·min -1 ; P = .010; effect size (ES) = 1.09; very likely) and oxygen consumption (4.4 [5.0] mL·kg -1 ·min -1 ; P = .12; ES = 0.77; unclear) were moderately greater with active recovery compared with passive recovery across sprints. Summed CODD time (0.87 [1.01] s; P = .07; ES = 0.76, moderate; likely) and CODD decrement (8.1% [3.7%]; P < .01; ES = 1.94, large; almost certainly) were higher with active compared with passive recovery. Trivial-small differences were evident for rating of perceived exertion (P = .516; ES = 0.19; unclear) and posttest blood lactate concentration (P = .29; ES = 0.40; unclear) between recovery modes., Conclusions: Passive recovery between repeated-change-of-direction sprints may reduce the physiological stress and fatigue encountered compared with active recovery in basketball players.

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.

Air travel requirements are a concern for National Basketball Association (NBA) coaches, players, and owners, as sport-based research has demonstrated short-haul flights (≤6 h) increase injury risk and impede performance. However, examination of the impact of air travel on player health and performance specifically in the NBA is scarce. Therefore, we conducted a narrative review of literature examining the influence of air travel on health and performance in team sport athletes with suggestions for future research directions in the NBA. Prominent empirical findings and practical recommendations are highlighted pertaining to sleep, nutrition, recovery, and scheduling strategies to alleviate the negative effects of air travel on health and performance in NBA players.

Berkelmans, DM, Dalbo, VJ, Kean, CO, Milanović, Z, Stojanović, E, Stojiljković, N, and Scanlan, AT. Heart rate monitoring in basketball: applications, player responses, and practical recommendations. J Strength Cond Res 32(8): 2383-2399, 2018-The aims of this review were to collate the existing literature encompassing heart rate (HR) monitoring in basketball to (a) identify the applications of HR measurement; (b) report HR responses in male and female players during training and game-play; (c) evaluate use of current HR-based training load models; and (d) provide recommendations for future research and best practice approaches for basketball practitioners. Heart rate monitoring in basketball carries 3 primary applications: (a) monitoring exercise intensity; (b) assessing player fatigue status; and (c) quantifying internal training load. When interpreting the available training and game-play HR data in basketball players, key differences have been observed between playing positions and playing levels. Sex- and age-based differences in HR responses during basketball training and game-play are apparent across separate studies; however, further research exploring HR responses in wider player groups is needed, especially in female and junior players. There is also a lack of research directly comparing player HR responses during training and game-play to ascertain the effectiveness of different drills in preparing players for competition. Heart rate-based models have been frequently used to quantify the internal training load in basketball players, including Banister's Training Impulse (TRIMP), Lucia's TRIMP, and Edwards' Summated-Heart-Rate-Zones (SHRZ). The SHRZ model seems to hold practical advantages and better detect changes in player responses across training cycles compared with other approaches. Practical outcomes of this review center on recommendations for position-specific training plans, drills to promote desired cardiovascular stress, analysis of HR outcome measures, and ideal training load monitoring approaches.

Purpose: The aims of this study were to: (1) provide a comprehensive physiological profile of simulated basketball activity and (2) identify temporal changes in player responses in controlled settings., Methods: State-level male basketball players ( n  = 10) completed 4 × 10 min simulated quarters of basketball activity using a reliable and valid court-based test. A range of physiological (ratings of perceived exertion, blood lactate concentration ([BLa - ]), blood glucose concentration ([BGlu]), heart rate (HR), and hydration) and physical (performance and fatigue indicators for sprint, circuit, and jump activity) measures were collected across testing., Results: Significantly reduced [BLa - ] (6.19 ± 2.30 vs. 4.57 ± 2.33 mmol/L; p  = 0.016) and [BGlu] (6.91 ± 1.57 vs. 5.25 ± 0.81 mmol/L; p  = 0.009) were evident in the second half. A mean HR of 180.1 ± 5.7 beats/min (90.8% ± 4.0% HR max ) was observed, with a significant increase in vigorous activity (77%-95% HR max ) (11.31 ± 6.91 vs. 13.50 ± 6.75 min; p  = 0.024) and moderate decrease in near-maximal activity (>95% HR max ) (7.24 ± 7.45 vs. 5.01 ± 7.20 min) in the second half. Small increases in performance times accompanied by a significantly lower circuit decrement (11.67% ± 5.55% vs. 7.30% ± 2.16%; p  = 0.032) were apparent in the second half., Conclusion: These data indicate basketball activity imposes higher physiological demands than previously thought and temporal changes in responses might be due to adapted pacing strategies as well as fatigue-mediated mechanisms.

This study quantified lower-limb strength decrements and assessed the relationships between strength decrements and performance fatigue during simulated basketball. Ten adolescent, male basketball players completed a circuit-based, basketball simulation. Sprint and jump performance were assessed during each circuit, with knee flexion and extension peak concentric torques measured at baseline, half-time, and full-time. Decrement scores were calculated for all measures. Mean knee flexor strength decrement was significantly (P < 0.05) related to sprint fatigue in the first half (R = 0.65), with dominant knee flexor strength (R = 0.67) and dominant flexor:extensor strength ratio (R = 0.77) decrement significantly (P < 0.05) associated with sprint decrement across the entire game. Mean knee extensor strength (R = 0.71), dominant knee flexor strength (R = 0.80), non-dominant knee flexor strength (R = 0.75), mean knee flexor strength (R = 0.81), non-dominant flexor:extensor strength ratio (R = 0.71), and mean flexor:extensor strength ratio (R = 0.70) decrement measures significantly (P < 0.05) influenced jump fatigue during the entire game. Lower-limb strength decrements may exert an important influence on performance fatigue during basketball activity in adolescent, male players. Consequently, training plans should aim to mitigate lower-limb fatigue to optimise sprint and jump performance during game-play.

Background: Physical activity (PA) and diet are 2 lifestyle factors that affect cardiometabolic risk. However, data on how a high-fat high-carbohydrate (HFHC) diet influences the effect of different intensities of PA on cardiometabolic health and cardiovascular function in a controlled setting are yet to be fully established. This study investigated the effect of sedentary behavior, light-intensity training (LIT), and high-intensity interval training (HIIT) on cardiometabolic markers and vascular and cardiac function in HFHC-fed adult rats., Methods: Twelve-week-old Wistar rats were randomly allocated to 4 groups (12 rats/group): control (CTL), sedentary (SED), LIT, and HIIT. Biometric indices, glucose and lipid control, inflammatory and oxidative stress markers, vascular reactivity, and cardiac electrophysiology of the experimental groups were examined after 12 weeks of HFHC-diet feeding and PA interventions., Results: The SED group had slower cardiac conduction ( p  = 0.0426) and greater thoracic aortic contractile responses ( p  < 0.05) compared with the CTL group. The LIT group showed improved cardiac conduction compared with the SED group ( p  = 0.0003), and the HIIT group showed decreased mesenteric artery contractile responses compared with all other groups and improved endothelium-dependent mesenteric artery relaxation compared with the LIT group (both p  < 0.05). The LIT and HIIT groups had lower visceral ( p  = 0.0057 for LIT, p  = 0.0120 for HIIT) and epididymal fat ( p  < 0.0001 for LIT, p  = 0.0002 for HIIT) compared with the CTL group., Conclusion: LIT induced positive adaptations on fat accumulation and cardiac conduction, and HIIT induced a positive effect on fat accumulation, mesenteric artery contraction, and endothelium-dependent relaxation. No other differences were observed between groups. These findings suggest that few positive health effects can be achieved through LIT and HIIT when consuming a chronic and sustained HFHC diet.

Background: Basketball is a popular, court-based team sport that has been extensively studied over the last decade., Objective: The purpose of this article was to provide a systematic review regarding the activity demands and physiological responses experienced during basketball match-play according to playing period, playing position, playing level, geographical location, and sex., Methods: An electronic database search of relevant articles published prior to 30 September 2016 was performed with PubMed, MEDLINE, ERIC, Google Scholar, SCIndex, and ScienceDirect. Studies that measured activity demands and/or physiological responses during basketball match-play were included., Results: Following screening, 25 articles remained for review. During live playing time across 40-min matches, male and female basketball players travel 5-6 km at average physiological intensities above lactate threshold and 85% of maximal heart rate (HR). Temporal comparisons show a reduction in vigorous activities in the fourth quarter, likely contributing to lower blood lactate concentrations and HR responses evident towards the end of matches. Guards tend to perform a higher percentage of live playing time sprinting and performing high-intensity shuffling compared with forwards and centers. Guards also perform less standing and walking during match-play compared with forwards and centers. Variations in activity demands likely account for the higher blood lactate concentrations and HR responses observed for guards compared with forwards and centers. Furthermore, higher-level players perform a greater intermittent workload than lower-level players. Moreover, geographical differences may exist in the activity demands (distance and frequency) and physiological responses between Australian, African, and European basketball players, whereby Australian players sustain greater workloads. While activity demands and physiological data vary across playing positions, playing levels, and geographical locations, male and female players competing at the same level experience similar demands., Conclusion: The current results provide a detailed description of the specific requirements placed on basketball players during match-play according to playing period, playing level, playing position, geographical location, and sex, which may be useful in the development of individualized basketball training drills.

We aimed to determine nutritional knowledge and behaviors of normal weight, overweight, and obese residents of Central Queensland, Australia. Data were collected as part of the 2010 Central Queensland Social Survey ( N = 1289). Residents were asked questions assessing nutritional knowledge and behaviors. Statistical analyses were performed to examine differences in nutritional knowledge and behaviors by body mass index (BMI) classification: normal weight, overweight, and obese. Independent of BMI, residents ate fewer than the recommended daily servings of vegetables ( p < 0.05) and fruits ( p < 0.05) with no differences found between BMI classifications. Overweight (OR: 1.52; 95% CI: 1.13⁻2.04) and obese (OR: 1.43; 95% CI: 1.04⁻1.98) residents were more likely to have eaten fast food the week of the survey than normal weight residents. Residents correctly identified the amount of kilocalories required to maintain current body weight with no differences between BMI classifications. Each BMI classification underestimated the amount of kilojoules required to maintain current body weight ( p < 0.05). Nutritional knowledge may not be the limiting factor preventing residents from making proper nutritional choices.

Aims: Intestinal microbiota modulates the development of clinical conditions, including metabolic syndrome and obesity. Many of these conditions are influenced by nutritional and exercise behaviours. This study aimed to investigate the ability of exercise to re-shape the intestinal microbiota and the influence of the diet on the process., Methods and Results: A rat model was used to examine the intestinal microbiota responses to four activity conditions, including: high-intensity interval training (HIIT), light-intensity training (LIT), sedentary and normal control, each containing two nutritional conditions: high-fat high-fructose diet (HF) and standard chow (SC) diet. No significant differences in microbiota were apparent between activity conditions in rats fed a HF diet but changes in the presence/absence of phylotypes were observed in the LIT and HIIT groups. In rats fed SC, significant differences in intestinal microbiota were evident between exercised and nonexercised rats. Both LIT and HIIT induced significant differences in intestinal microbiota in SC-fed rats compared to their respective SC-fed controls. Characterization of the exercise-induced bacterial phylotypes indicated an increase in bacteria likely capable of degrading resistant polysaccharides and an increase in short chain fatty acid producers., Conclusions: While a significant effect of exercise on microbiota composition occurred in SC-fed rats, the HF-fed rats microbiota showed little response. These data suggest that a HF diet prevented microbiota differentiation in response to exercise., Significance and Impact of the Study: The importance of diet-exercise interaction is extended to the level of intestinal bacteria and gut health., (© 2017 The Society for Applied Microbiology.)

The aim of this study was to determine if adults in Central Queensland have accurate self-perceptions of health. Data were collected as part of the 2010 Central Queensland Social Survey (N = 1289). Overweight/obesity is considered a health disorder and was determined using body mass index. Disease states were determined by asking respondents if they have: heart disease, high/low blood pressure, high cholesterol, high triglycerides, thyroid disorder, diabetes, and osteopenia/osteoporosis. Self-perceptions of health were assessed by asking, "Would you say that in general your health is" poor, fair, good, very good, excellent, don't know, and no response. An accurate health perception occurred if: (1) A respondent with a disease/health disorder reported that their health was poor/fair or (2) A respondent without a disease/health disorder reported that their health was good/very good/excellent. The proportions of people with an accurate health perception by disease/health disorder were compared using a χ² test. A proportion ratio (PR) with a 95% confidence interval (CI) was calculated for each disease/health disorder. A logistic regression analysis was performed to examine the association between each disease/health disorder and health perception using gender, age, education, physical activity level, and smoking status as covariates. More than 50% of residents with each disease/health disorder reported their health to be good/very good/excellent. Residents with each disease/health disorder were less likely to have an accurate health perception than those without the corresponding disease/health disorder prior to ( p < 0.001) and following adjustment of the covariates ( p < 0.001). Our results suggest that overweight/obesity and prevalence of disease are not being recognized as unhealthy, which contradicts established definitions of health.

The androgen-induced alterations in adult rodent skeletal muscle fibre cross-sectional area (fCSA), satellite cell content and myostatin (Mstn) were examined in 10-month-old Fisher 344 rats (n = 41) assigned to Sham surgery, orchiectomy (ORX), ORX + testosterone (TEST; 7.0 mg week -1 ) or ORX + trenbolone (TREN; 1.0 mg week -1 ). After 29 days, animals were euthanised and the levator ani/bulbocavernosus (LABC) muscle complex was harvested for analyses. LABC muscle fCSA was 102% and 94% higher in ORX + TEST and ORX + TREN compared to ORX (p < .001). ORX + TEST and ORX + TREN increased satellite cell numbers by 181% and 178% compared to ORX, respectively (p < .01), with no differences between conditions for myonuclear number per muscle fibre (p = .948). Mstn protein was increased 159% and 169% in the ORX + TEST and ORX + TREN compared to ORX (p < .01). pan-SMAD2/3 protein was ~30-50% greater in ORX compared to SHAM (p = .006), ORX + TEST (p = .037) and ORX + TREN (p = .043), although there were no between-treatment effects regarding phosphorylated SMAD2/3. Mstn, ActrIIb and Mighty mRNAs were lower in ORX, ORX + TEST and ORX + TREN compared to SHAM (p < .05). Testosterone and trenbolone administration increased muscle fCSA and satellite cell number without increasing myonuclei number, and increased Mstn protein levels. Several genes and signalling proteins related to myostatin signalling were differentially regulated by ORX or androgen therapy., (© 2016 Blackwell Verlag GmbH.)

The current review clarifies the cardiometabolic health effects of high-intensity interval training (HIIT) in adults. A systematic search (PubMed) examining HIIT and cardiometabolic health markers was completed on 15 October 2015. Sixty-five intervention studies were included for review and the methodological quality of included studies was assessed using the Downs and Black score. Studies were classified by intervention duration and body mass index classification. Outcomes with at least 5 effect sizes were synthesised using a random-effects meta-analysis of the standardised mean difference (SMD) in cardiometabolic health markers (baseline to postintervention) using Review Manager 5.3. Short-term (ST) HIIT (<12 weeks) significantly improved maximal oxygen uptake (VO 2 max; SMD 0.74, 95% CI 0.36 to 1.12; p<0.001), diastolic blood pressure (DBP; SMD -0.52, 95% CI -0.89 to -0.16; p<0.01) and fasting glucose (SMD -0.35, 95% CI -0.62 to -0.09; p<0.01) in overweight/obese populations. Long-term (LT) HIIT (≥12 weeks) significantly improved waist circumference (SMD -0.20, 95% CI -0.38 to -0.01; p<0.05), % body fat (SMD -0.40, 95% CI -0.74 to -0.06; p<0.05), VO 2 max (SMD 1.20, 95% CI 0.57 to 1.83; p<0.001), resting heart rate (SMD -0.33, 95% CI -0.56 to -0.09; p<0.01), systolic blood pressure (SMD -0.35, 95% CI -0.60 to -0.09; p<0.01) and DBP (SMD -0.38, 95% CI -0.65 to -0.10; p<0.01) in overweight/obese populations. HIIT demonstrated no effect on insulin, lipid profile, C reactive protein or interleukin 6 in overweight/obese populations. In normal weight populations, ST-HIIT and LT-HIIT significantly improved VO 2 max, but no other significant effects were observed. Current evidence suggests that ST-HIIT and LT-HIIT can increase VO 2 max and improve some cardiometabolic risk factors in overweight/obese populations., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Purpose: Declines in high-intensity activity during game play (in-game approach) and performance tests measured pre- and postgame (across-game approach) have been used to assess player fatigue in basketball. However, a direct comparison of these approaches is not available. Consequently, this study examined the commonality between in- and across-game jump fatigue during simulated basketball game play., Methods: Australian, state-level, junior male basketball players (n = 10; 16.6 ± 1.1 y, 182.4 ± 4.3 cm, 68.3 ± 10.2 kg) completed 4 × 10-min standardized quarters of simulated basketball game play. In-game jump height during game play was measured using video analysis, while across-game jump height was determined pre-, mid-, and postgame play using an in-ground force platform. Jump height was determined using the flight-time method, with jump decrement calculated for each approach across the first half, second half, and entire game., Results: A greater jump decrement was apparent for the in-game approach than for the across-game approach in the first half (37.1% ± 11.6% vs 1.7% ± 6.2%; P = .005; d = 3.81, large), while nonsignificant, large differences were evident between approaches in the second half (d = 1.14) and entire game (d = 1.83). Nonsignificant associations were evident between in-game and across-game jump decrement, with shared variances of 3-26%., Conclusions: Large differences and a low commonality were observed between in- and across-game jump fatigue during basketball game play, suggesting that these approaches measure different constructs. Based on our findings, it is not recommended that basketball coaches use these approaches interchangeably to monitor player fatigue across the season.

Purpose: The influence of various factors on training-load (TL) responses in basketball has received limited attention. This study aimed to examine the temporal changes and influence of cumulative training dose on TL responses and interrelationships during basketball activity., Methods: Ten state-level Australian male junior basketball players completed 4 × 10-min standardized bouts of simulated basketball activity using a circuit-based protocol. Internal TL was quantified using the session rating of perceived exertion (sRPE), summated heart-rate zones (SHRZ), Banister training impulse (TRIMP), and Lucia TRIMP models. External TL was assessed via measurement of mean sprint and circuit speeds. Temporal TL comparisons were performed between 10-min bouts, while Pearson correlation analyses were conducted across cumulative training doses (0-10, 0-20, 0-30, and 0-40 min)., Results: sRPE TL increased (P < .05) after the first 10-min bout of basketball activity. sRPE TL was only significantly related to Lucia TRIMP (r = .66-.69; P < .05) across 0-10 and 0-20 min. Similarly, mean sprint and circuit speed were significantly correlated across 0-20 min (r = .67; P < .05). In contrast, SHRZ and Banister TRIMP were significantly related across all training doses (r = .84-.89; P < .05)., Conclusions: Limited convergence exists between common TL approaches across basketball training doses lasting beyond 20 min. Thus, the interchangeability of commonly used internal and external TL approaches appears dose-dependent during basketball activity, with various psychophysiological mediators likely underpinning temporal changes.

Objective: The objective of this study was to compare the chronic effects of different whey protein forms on body composition and performance when supplemented with resistance training., Methods: Resistance-trained men (N = 56, 21.4 ± 0.4 years, 79.5 ± 1.0 kg) participated in an 8-week resistance training regimen (2 upper-body sessions and 2 lower-body sessions per week) and received one of 4 double-blinded treatments: 30 g/serving carbohydrate placebo (PLA) or 30 g/serving protein from either (a) 80% whey protein concentrate (WPC), (b) high-lactoferrin-containing WPC (WPC-L), or (c) extensively hydrolyzed WPC (WPH). All subjects consumed 2 servings of treatment per day; specifically, once immediately before and after training and between meals on nontraining days. Blood collection, one repetition maximum (1RM) testing for bench press and hack squat, and body composition assessment using dual-energy x-ray absorptiometry (DXA) occurred prior to training and 48 hours following the last training session., Results: Total body skeletal muscle mass increased in all groups (p < 0.0125). There were similar between-group increases in upper-body (4%-7%, analysis of covariance [ANCOVA] interaction p = 0.73) and lower-body (24%-35%, ANCOVA interaction p = 0.85) 1RM strength following the intervention. Remarkably, WPH reduced fat mass (-6%), which was significantly different from PLA (+4.4%, p < 0.0125). No time or between-group differences were present for serum markers of health, metabolism, or muscle damage, with the exception of blood urea nitrogen being significantly lower for WPH than WPC (p < 0.05) following the intervention., Conclusions: WPH may augment fat loss but did not provide any other advantages when used in combination with resistance training. More mechanistic research is needed to examine how WPH affects adipose tissue physiology.

Physical activity has the potential to reduce cardiometabolic risk factors but evaluation of different intensities of physical activity and the mechanisms behind their health effects still need to be fully established. This study examined the effects of sedentary behaviour, light-intensity training, and high-intensity interval training on biometric indices, glucose and lipid metabolism, inflammatory and oxidative stress markers, and vascular and cardiac function in adult rats. Rats (12 weeks old) were randomly assigned to 1 of 4 groups: control (CTL; no exercise), sedentary (SED; no exercise and housed in small cages to reduce activity), light-intensity trained (LIT; four 30-min exercise bouts/day at 8 m/min separated by 2-h rest period, 5 days/week), and high-intensity interval trained (HIIT, four 2.5-min work bouts/day at 50 m/min separated by 3-min rest periods, 5 days/week). After 12 weeks of intervention, SED had greater visceral fat accumulation (p < 0.01) and slower cardiac conduction (p = 0.04) compared with the CTL group. LIT and HIIT demonstrated beneficial changes in body weight, visceral and epididymal fat weight, glucose regulation, low-density lipoprotein cholesterol, total cholesterol, and mesenteric vessel contractile response compared with the CTL group (p < 0.05). LIT had significant improvements in insulin sensitivity and cardiac conduction compared with the CTL and SED groups whilst HIIT had significant improvements in systolic blood pressure and endothelium-independent vasodilation to aorta and mesenteric artery compared with the CTL group (p < 0.05). LIT and HIIT induce health benefits by improving traditional cardiometabolic risk factors. LIT improves cardiac health while HIIT promotes improvements in vascular health.

Background: Chronic kidney disease (CKD) is an irreversible disease that diminishes length and quality of life. Emerging evidence suggests CKD progression and genomic integrity are inversely and causally related. To reduce health complications related to CKD progression, chronic aerobic exercise is often recommended. To date, appraisals of differing modes of exercise, along with postulations regarding the mechanisms responsible for observed effects, are lacking. In order to examine the ability of aerobic exercise to encourage improvements in genomic integrity, we evaluated the effects of 8 weeks of high-intensity interval training (HIIT; 85 % VO 2max ), low intensity training (LIT; 45-50 % VO 2max ), and sedentary behaviour (SED), in an animal model of early-stage CKD., Methods: To assess genomic integrity, we examined kidney-specific messenger RNA (mRNA) expression of genes related to genomic repair and stability: Fan1 , Mre11a , and telomere length as measured by T/S ratio., Results: Following HIIT, mRNA expression of Fan1 was significantly up-regulated, compared to SED ( p  = 0.026) and T/S ratio was significantly increased, compared to SED ( p  < 0.001) and LIT ( p  = 0.002)., Conclusions: Our results suggest that HIIT is superior to SED and LIT as HIIT beneficially influenced the expression of genes related to genomic integrity.

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.

Purpose: To examine age-related differences in intramuscular concentrations of adenosine triphosphate (ATP), free creatine (FCr), phosphocreatine (PCr) and total creatine (TCr) and if these differences were related to muscle performance., Methods: Forty-two healthy, non-sedentary, males between 20 and 76 years provided muscle samples to determine [ATP], [FCr], [PCr], and [TCr]. Maximal strength and endurance were assessed and correlated with intramuscular variables., Results: Intramuscular [ATP] decreased by 13.5% (p = 0.013) in the older cohort (18.0 ± 0.6 mmol/kg dry wt) vs. the young cohort (20.8 ± 0.9 mmol/kg dry wt) and was significantly correlated to age (r = -0.38, p = 0.008). No other differences were observed between age groups for intramuscular [PCr], [FCr], [TCr], or [PCr]:[TCr] (p > 0.05). The older cohort consumed significantly less (p < 0.05) dietary protein when compared to the young cohort. Bivariate correlations were found for intramuscular [ATP] and lower body 1RM (r = 0.24, p = 0.066), leg press volume and free creatine (r = 0.325, p = 0.036) and leg press repetitions and free creatine (r = 0.373, p = 0.015). Partial correlations controlling for age eliminated the relationship between [ATP] and 1RM while intramuscular free creatine and leg press repetitions remained significant (p < 0.05) and leg press volume approached significance (p = 0.095)., Conclusion: These results expand upon previous observations indicative of age-related reductions in intramuscular [ATP] and dietary protein intake. The lack of change in other intramuscular PCr system markers are suggestive of dysfunctions at the mitochondrial level while the impact of neuromuscular changes, lean mass cross-sectional area and differences in physical activity are also important.