Purpose: This study aimed to investigate the single and combined effects of sleep restriction (SR) and mental fatigue (MF) on free-throw (FT) performance among adult male basketball players. Methods: A total of 19 amateur male basketball players performed, in a randomized, counterbalanced, and crossover order, 2 identical experimental sessions separated by an interval of 1 week. The difference between the 2 sessions was in the quantity of sleep the night before the sessions, as follows: in one case, the participants followed their habitual sleep–wake routines; in the other session, they were forced to sleep not more than 5 hours. During the experimental sessions, the participants performed 60 basketball FTs on 2 occasions, separated by watching a basketball tactical video for 30 minutes designed to induce MF. As such, the FT test was completed in 4 different conditions: control, MF, SR, and SR and MF combined. Results: The participants registered a significantly lower total sleep time in acute SR (P < .001). The subjective rating of MF was lower in the control than in MF, SR, and SR and MF combined (P < .001). There were no differences between conditions for the subjective ratings of motivation. FT accuracy was higher in the control than in MF, SR, and SR and MF combined (P = .010), while no differences were observed between the 3 experimental conditions (all P > .05). Conclusion: The results indicate that a combined effect of MF and SR induces a small reduction in basketball FT performance, similar to MF or SR alone.
Luca Filipas, Davide Ferioli, Giuseppe Banfi, Antonio La Torre, and Jacopo Antonino Vitale
Cody J. O’Grady, Jordan L. Fox, Daniele Conte, Davide Ferioli, Aaron T. Scanlan, and Vincent J. Dalbo
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.
Jos J de Koning, Teun van Erp, Rob Lamberts, Stephen Cheung, and Dionne Noordhof
Fabio R. Serpiello and Will G. Hopkins
Purpose: To assess the convergent validity of internal load measured with the CR100 scale in youth football players of 3 age groups. Methods: A total of 59 players, age 12–17 years, from the youth academy of a professional football club were involved in this study. Convergent validity was examined by calculating the correlation between session ratings of perceived exertion (sRPE) and Edwards load, a commonly used load index derived from the heart rate, with the data originating from 1 competitive season. The magnitude of the relationship between sRPE and Edwards load was obtained with weighted mean correlations and by assessing the effect of the change of the Edwards load on sRPE. Differences between the individuals’ intercepts and slopes were assessed by interpreting the SD representing the random effects (player identity and the interaction of player identity and scaled Edwards load). Probabilistic decisions about true (infinite sample) magnitudes accounting for sampling uncertainty were based on 1-sided hypothesis tests of substantial magnitudes, followed by reference Bayesian analysis. Results: Very high relationships exist between the sRPE and Edwards load across all age groups, with no meaningful differences in the magnitudes of the relationships between groups. Moderate to large differences between training sessions and games were found in the slopes of the relationships between the sRPE and Edwards load in all age groups. Finally, mostly small to moderate differences were observed between individuals for the intercepts and slopes of the relationships between the sRPE and Edwards load. Conclusion: Practitioners working in youth team sports can safely use the CR100 scale to track internal load.
Daniel Boullosa, Marco Beato, Antonio Dello Iacono, Francisco Cuenca-Fernández, Kenji Doma, Moritz Schumann, Alessandro Moura Zagatto, Irineu Loturco, and David G. Behm
Aaron T. Scanlan, Emilija Stojanović, Zoran Milanović, Masaru Teramoto, Mario Jeličić, and Vincent J. Dalbo
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.
Javier Raya-González, Aaron T. Scanlan, María Soto-Célix, Alejandro Rodríguez-Fernández, and Daniel Castillo
Purpose: To examine the effects of acute caffeine supplementation on physical performance during fitness testing and activity during simulated games in basketball players. Methods: A double-blind, counterbalanced, randomized, crossover study design was followed. A total of 14 professional male basketball players ingested a placebo (sucrose) and caffeine (6 mg·kg−1 of body mass) in liquid form prior to completing 2 separate testing sessions. Each testing session involved completion of a standardized 15-minute warm-up followed by various fitness tests including 20-m sprints, countermovement jumps, Lane Agility Drill trials, and a repeated-sprint-ability test. Following a 20-minute recovery, players completed 3 × 7-minute 5-vs-5 simulated periods of full-court basketball games, each separated by 2 minutes of recovery. Local positioning system technology was used to measure player activity during games. Players completed a side-effects questionnaire 12 to 14 hours after testing. Results: Players experienced significant (P < .05), moderate–very large (effect size = −2.19 to 0.89) improvements in 20-m sprint, countermovement jump, Lane Agility Drill, and repeated-sprint-ability performance with caffeine supplementation. However, external workloads completed during simulated games demonstrated nonsignificant, trivial–small (effect size = −0.23 to 0.12) changes between conditions. In addition, players reported greater (P < .05) insomnia and urine output after caffeine ingestion. Conclusions: Acute caffeine supplementation could be effective to improve physical performance during tests stressing fitness elements important in basketball. However, acute caffeine supplementation appears to exert no meaningful effects on the activity completed during simulated basketball games and may promote sleep disturbances and exert a diuretic effect when taken at 6 mg·kg−1 of body mass in professional players.
Ian C. Smith and Brian R. MacIntosh
Samantha B. Kostelnik, Michelle S. Rockwell, Kevin P. Davy, Valisa E. Hedrick, D. Travis Thomas, and Brenda M. Davy
Fluid intake recommendations have been established for the athletic population in order to promote adequate hydration. The Beverage Intake Questionnaire (BEVQ-15) is a quick and reliable food frequency questionnaire that quantifies habitual beverage intake, which has been validated in children, adolescents, and adults. However, no validated beverage consumption questionnaire is available for collegiate athletes. Urine color (UC), while feasible for determining hydration status, has not been validated within a variety of collegiate athletes. The purpose of this investigation was to evaluate the comparative validity and reliability of pragmatic methods to rapidly assess BEVQ-15 and UC rating in U.S. Division I collegiate athletes. Student-athletes (n = 120; 54% females; age 19 ± 1 years) from two universities were recruited to complete three study sessions. At the first and third sessions, the participants completed the BEVQ-15 and provided a urine sample to determine UC and urinary specific gravity. All sessions included completion of a 24-hr dietary recall. Total fluid intake (fl oz) was 111 ± 107 and 108 ± 42 using the BEVQ-15 and the mean of three 24-hr dietary recalls, respectively, which was not different between methods (p > .05). There were moderate associations between the BEVQ-15 and dietary recall results for total beverage intake fl oz and kcal(r = .413 and r = 4.65; p ≤ .05, respectively). Strong associations were noted between both researcher-rated and participant-rated UC with urinary specific gravity measures (r = .675 and r = .884; p ≤ .05, respectively). Therefore, these rapid assessment methods demonstrated acceptable validity and may be used as practical methods to determine whether athletes are meeting their hydration recommendations.
Corrado Lupo, Alexandru Nicolae Ungureanu, Gennaro Boccia, Andrea Licciardi, Alberto Rainoldi, and Paolo Riccardo Brustio
Purpose: The present study aimed to verify if practicing tackles during rugby union training sessions would affect the players’ internal training load and acute strength loss. Method: A total of 9 male Italian Serie A rugby union players (age: 21  y) were monitored by means of an integrated approach across 17 sessions, 6 with tackles (WT) and 11 with no tackles (NT). Edwards training load was quantified using heart-rate monitoring. Global positioning system devices were used to quantify the total distance and time at >20 W. Work-to-rest ratio was quantified by means of a video analysis. Before (PRE) and after (POST) the session, the players’ well-being and rating of perceived exertion were measured, respectively. The countermovement jump and plyometric push-up jump tests were performed on a force plate to record the players’ PRE–POST concentric peak force. Linear mixed models were applied to quantify the differences between WT and NT in terms of training load and PRE–POST force deltas, even controlling for other training factors. Results: The Edwards training load (estimated mean [EM]; standard error [SE]; WT: EM = 214, SE = 11.8; NT: EM = 194, SE = 11.1; P = .01) and session rating of perceived exertion (WT: EM = 379, SE = 21.9; NT: EM = 277, SE = 16.4; P < .001) were higher in WT than in NT. Conversely, no difference between the sessions emerged in the countermovement jump and plyometric push-up concentric peak force deltas. Conclusions: Although elite rugby union players’ external and internal training load can be influenced by practicing tackles, upper- and lower-limb strength seem to not be affected.