This study compared the effects of recreational football and high‐intensity interval training (HIIT) on body composition, muscular fitness, and cardiorespiratory fitness in overweight and obese children. Forty‐two overweight/obese males aged 11‐13 years [body mass index (BMI) >20.5 kg/m²] were randomly assigned to a recreational football training group (n = 14; 157.9 ± 5.8 cm; 63.7 ± 12.6 kg), HIIT group (n = 14; 163.8 ± 9.4 cm; 71.5 ± 10.5 kg), or nontraining control group (n = 14; 162.7 ± 9.3 cm; 67.4 ± 16.1 kg). Physical fitness components were measured at baseline and after 12 weeks of training at the same time of the day and under similar conditions, including body composition, muscular fitness (lower‐body power, change‐of‐direction speed, and flexibility), and cardiovascular fitness (Yo‐Yo Intermittent Endurance test distance, resting heart rate, and blood pressure). Lean body mass (4.3%, ES = 0.40; 95% CI: −0.48, 1.29; P = .382) and muscle mass 4.4% (ES = 0.40; 95% CI: −0.48, 1.29; P = .378) very likely increased in the recreational football group, while possible improvements were observed in the HIIT group (lean body mass: 2.5%, ES = 0.22; 95% CI: −0.62, 1.06; P = .607, muscle mass: 2.8%, ES = 0.23; 95% CI: −0.61, 1.07; P = .594). Only trivial increases were observed in the control group for lean body mass (0.5%, ES = 0.05; 95% CI: −0.70, 0.79; P = .906) and muscle mass (1.1%, ES = 0.09; 95% CI: −0.65, 0.83; P = .814). Significant differences were found between the recreational football and control groups in post‐training body mass (P = .034) and body mass index (P = .017). Body fat very likely decreased in the recreational football group (−7.7%, ES = −0.41; 95% CI: −1.29, 0.48; P = .376) and possibly decreased in the HIIT group (−5.2%, ES = −0.22; 95% CI: −1.05, 0.62; P = .607), with a trivial reduction in the control group (−1.1%, ES = −0.04; 95% CI: −0.78, 0.70; P = .914). Very likely increases in lower‐body power were evident in the recreational football (17.0%, ES = 0.76; 95% CI: −0.15, 1.66; P = .107) and control groups (16.1%, ES = 0.55; 95% CI: −0.20, 1.31; P = .156), while small improvements were observed in the HIIT group (6.0%, ES = 0.24; 95% CI: −0.60, 1.08; P = .580, possible). Likely to most likely improvements in Yo‐Yo Intermittent Endurance test performance and change‐of‐direction speed were noted in the recreational football group (Yo‐Yo: 79.8%, ES = 1.09; 95% CI: 0.16, 2.03; P = .025, change‐of‐direction speed: −10.6%, ES = −1.05; 95% CI: −1.98, −0.12; P = .031) and the HIIT group (Yo‐Yo: 81.2%, ES = 1.03; 95% CI: 0.15, 1.92; P = .025, change‐of‐direction speed: −5.4%, ES = −0.91; 95% CI: −1.79, −0.04; P = .045). Diastolic blood pressure likely decreased in the recreational football (−8.6%, ES = −0.74; 95% CI: −1.64, 0.17; P = .116) and HIIT groups (−9.8%, ES = −0.57; 95% CI: −1.40, 0.30; P = .195), with a possible increase in the control group (1.2%, ES = 0.21; 95% CI: −0.53, 0.96; P = .068). Recreational football and HIIT elicited improvements in all muscular and cardiorespiratory fitness measures. In contrast, the control group, which performed only physical education classes, increased body mass, BMI, and fat mass. Therefore, additional activities such as recreational football or HIIT might counter the prevalence of overweight and obesity in children.

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.

Stojanović, E, Aksović, N, Stojiljković, N, Stanković, R, Scanlan, AT, and Milanović, Z. Reliability, usefulness, and factorial validity of change-of-direction speed tests in adolescent basketball players. J Strength Cond Res 33(11): 3162–3173, 2019—The purposes of this study were to (1) determine the reliability, usefulness, and factorial validity of change-of-direction speed (CODS) tests in adolescent basketball players and (2) evaluate positional differences in test performances. Elite, adolescent male basketball players (n = 53; 17.3 ± 1.0 years) completed 6 CODS tests: “Lane Arrow Closeout,” “Lane Agility Drill,” “Reactive Shuttle Test,” “Run-Shuffle-Run,” “Compass Drill,” and “Modified 505 Test.” Players completed 3 trials of each test. All tests demonstrated acceptable reliability (intraclass correlation coefficient: 0.50–0.88; coefficient of variation: 5.1–7.9%). The typical error (TE) calculated for each test was above the smallest worthwhile change, rating the usefulness of all tests as marginal. The principal component factor analysis in all tests resulted in the extraction of one significant component that explained 74% of the total variance across tests. Positional comparisons showed that backcourt (guards) players performed better (small to moderate differences) in all CODS tests compared with frontcourt (forwards and centers) players. All tests were deemed reliable and valid in adolescent basketball players. The “Lane Agility Drill” and “Run-Shuffle-Run” tests seem the most appropriate to quantify changes in CODS possessing the lowest TE, whereas the “Lane Arrow Closeout” and “Lane Agility Drill” tests are the most sensitive in detecting positional differences.

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.