Effects of dribbling restrictions in small-sided games on aerobic and anaerobic fitness in youth basketball players

Introduction

Imposing constraints such as limiting dribbling in smallsided games (SSGs) is known to increase physiological and locomotor demands. However, the long-term effects on physical adaptations remain unexplored. This experimental study aimed to compare the impact of free-play SSGs (freeD) and limited-dribbling SSGs (limitedD) in SSGs on the aerobic and anaerobic adaptations of youth basketball players.

Methods

Forty-five youth basketball players (aged 15.7 ± 0.6 years, with 4.2 ± 0.7 years of experience) were randomly assigned to two experimental groups (freeD and limitedD) and a control group (not exposed to SSG interventions). During the eight-week intervention, the experimental groups participated in additional SSG sessions twice a week, with session work time durations ranging from 12 to 16 min. Both experimental groups followed identical SSG formats, court dimensions, and training regimens, with the only difference being that one group participated in free play while the other group was prohibited from dribbling during progression. Aerobic capacity was assessed using the Yo-Yo Intermittent Recovery Test Level 1 (YYIRT), while the 30-second Wingate Test measured peak power output (PPO) and average power output (APO) at baseline and post-intervention. Statistical analysis was conducted using a mixed ANOVA to examine the interactions between time and group.

Results

Comparisons of YYIRT between groups at post-intervention revealed that limitedD performed significantly better than both freeD (p = 0.035; d = 1.038) and the control group (p < 0.001; d = 2.050), while freeD also showed significantly better performance (p = 0.021; d = 0.082) than the control group. Regarding PPO, limitedD was significantly better than the control group (p = 0.043; d = 0.943). Finally, for APO, limitedD was significantly better than both freeD (p = 0.043; d = 0.928) and the control group (p < 0.001; d = 1.793), while freeD also exhibited significantly better performance than the control group (p = 0.046; d = 0.036).

Conclusions

Limiting dribbling in basketball SSGs is more effective than free play. This makes it a potentially valuable strategy for designing SSGs in basketball training. Coaches may consider incorporating limited-dribbling conditions into SSGs to boost the intensity of training sessions, improve cardiovascular endurance, and enhance anaerobic power.

Energetics (and Mechanical Determinants) of Sprint and Shuttle Running

Unsteady locomotion (e. g., sprints and shuttle runs) requires additional metabolic (and mechanical) energy compared to running at constant speed. In addition, sprints or shuttle runs with relevant speed changes (e. g., with large accelerations and/or decelerations) are typically short in duration and, thus, anaerobic energy sources must be taken into account when computing energy expenditure. In sprint running there is an additional problem due to the objective difficulty in separating the acceleration phase from a (necessary and subsequent) deceleration phase.In this review the studies that report data of energy expenditure during sprints and shuttles (estimated or actually calculated) will be summarized and compared. Furthermore, the (mechanical) determinants of metabolic energy expenditure will be discussed, with a focus on the analogies with and differences from the energetics/mechanics of constant-speed linear running.

Comparative Analysis of Cardiorespiratory Parameters of Basketball and Soccer Players Using Principal Component Analysis

Principal component analysis (PCA) is a statistical technique used to identify variations in multivariate data obtained during the performance of the maximum ergospirometry test (MET). To use the PCA to compare the coefficients of change of the principal component (PC1) using the eigenvalue and the maximum values ​​of the cardiorespiratory variables obtained in the athletes' in MET. 10 soccer players and 10 basketball players, all male, were evaluated. The PCA analyzed the values ​​of the variables during the performance of the MET. The PC1 for each variable was calculated, and the eigenvalue was generated, representing the coefficients of variation of the PC1 of all variables. In the quantitative assessment (maximum values), a higher VO2max (3.93±0.62 vs. 3.41±0.37 l·min-1) was observed in basketball players compared to soccer players (p<0.05). The qualitative evaluation using PC1 of cardiorespiratory parameters (heart rate, minute volume, O2 consumption, CO2 production, expired fraction of O2 and expired fraction CO2) was observed as an eigenvalue (6.50±0.27 vs. 6.22±0.19) high for basketball players compared to soccer players (p<0.05). It is concluded that the basketball players showed more significant variability in their cardiorespiratory variables during the performance of the MET and higher VO2max at the end of the MET. These findings indicate that basketball players were less efficient in buffering the ventilatory acidosis observed during the MET. The results of this study highlight the importance of making complex assessments of the cardiorespiratory system, providing qualitative information to complement the quantitative data.

Comparison of Physiological and Perceptional Responses to 5-m Forward, Forward-Backward, and Lateral Shuttle Running

Purpose

The aim of this study was to investigate the physiological and perceptional responses to forward, forward-backward, and lateral shuttle running.

Methods

Twenty-four eligible male subjects performed a maximal oxygen uptake (VO_2max) test and three directional modes (i.e., forward, forward-backward, and lateral) of 5-m shuttle running at the speed of 6 km⋅h^–1 for 5 min on separate days. Heart rate (HR) and oxygen uptake (VO₂) were continuously measured during the whole tests. Rating of perceived exertion (RPE) was inquired and recorded immediately after the test. Capillary blood samples were collected from the earlobe during the recovery to determine the peak value of blood lactate concentration ([La^–]_peak).

Results

Running directional mode had significant effects on HR (F = 72.761, P < 0.001, η²_p = 0.760), %HR_max (F = 75.896, P < 0.001, η²_p = 0.767), VO₂ (F = 110.320, P < 0.001, η²_p = 0.827), %VO_2max (F = 108.883, P < 0.001, η²_p = 0.826), [La^–]_peak (F = 55.529, P < 0.001, η²_p = 0.707), and RPE (F = 26.268, P < 0.001, η²_p = 0.533). All variables were significantly different between conditions (P ≤ 0.026), with the variables highest in lateral shuttle running and lowest in forward shuttle running. The effect sizes indicated large magnitude in the differences of all variables between conditions (ES = 0.86–2.83, large) except the difference of RPE between forward and forward-backward shuttle running (ES = 0.62, moderate).

Conclusion

These findings suggest that the physiological and perceptional responses in shuttle running at the same speed depend on the directional mode, with the responses highest in lateral shuttle running, and lowest in forward shuttle running.

The Effect of Simulation-based Training on Athletic Performances among Female Basketball Players

Background:

The effectiveness of simulation-based training has been examined in various sports. However, considering the effect of gender and sport on training, it would be interesting to evaluate simulation-based training in female basketball.

Objective:

The purpose of the study was to examine the effect of simulation-based training on physical fitness and performance indices in female basketball players.

Methods:

Sixteen female semi-professional basketball players were randomly assigned to experimental (n=8; age, 25±2 years; weight, 62±9 kg; height, 167±8 cm) or control (n=8; age, 24±1 years; weight, 57±9 kg; height, 170±8 cm) groups. The experimental group participated in a six week basketball simulation training program including running with different speeds (jogging to sprinting), agility, jumping, and shuffling. Both groups performed the Cooper 12 min run, line drill, an adjusted T-test, 20 ms print, the Sargent vertical jump and basketball exercise simulation test before and after six weeks of the study period. Control and experimental groups performed typical basketball training, three times weekly. The overall training volume was similar for both groups.

Results:

The perceived exertion was higher in the simulation-based training than control (p<0.05) group. The findings of this study indicated a significant increase in VO2 max (p=0.001), anaerobic power (p=0.009), explosive leg strength (p=0.036), and total distance covered in basketball exercise simulation test (p=0.001) and decrease of the meantime of one round of basketball exercise simulation test (p=0.001) in the simulation training compared to the control group.

Conclusion:

Generally incorporation of the simulation-based training in conditioning programs is recommended for improving aerobic, anaerobic and leg explosive strength of basketball players.

Metabolic Profiles of the 30-15 Intermittent Fitness Test and the Corresponding Continuous Version in Team-Sport Athletes-Elucidating the Role of Inter-Effort Recovery

PURPOSE

To elucidate the role of inter-effort recovery in shuttle running by comparing the metabolic profiles of the 30-15 Intermittent Fitness Test (30-15IFT) and the corresponding continuous version (30-15IFT-CONT).

METHODS

Sixteen state-level handball players (age = 23 [3] y, height = 185 [7] cm, weight = 85 [14] kg) completed the 30-15IFT and 30-15IFT-CONT, and speed at the last completed stage (in kilometers per hour) and time to exhaustion (in seconds) were assessed. Furthermore, oxygen uptake (in milliliters per kilogram per minute) and blood lactate were obtained preexercise, during exercise, and until 15 minutes postexercise. Metabolic energy (in kilojoules), metabolic power (in Watts per kilogram), and relative (in percentage) energy contribution of the aerobic (WAER, WAERint), anaerobic lactic (WBLC, WBLCint), and anaerobic alactic (WPCr, WPCrint) systems were calculated by PCr-La-O2 method for 30-15IFT-CONT and 30-15IFT.

RESULTS

No difference in peak oxygen uptake was found between 30-15IFT and 30-15IFT-CONT (60.6 [6.6] vs 60.5 [5.1] mL·kg-1·min-1, P = .165, d = 0.20), whereas speed at the last completed stage was higher in 30-15IFT (18.3 [1.4] vs 16.1 [1.0] km·h-1, P < .001, d = 1.17). Metabolic energy was also higher in 30-15IFT (1224.2 [269.6] vs 772.8 [63.1] kJ, P < .001, d = 5.60), and metabolic profiles differed substantially for aerobic (30-15IFT = 67.2 [5.2] vs 30-15IFT-CONT = 85.2% [2.5%], P < .001, d = -4.01), anaerobic lactic (30-15IFT = 4.4 [1.4] vs 30-15IFT-CONT = 6.2% [1.8%], P < .001, d = -1.04), and anaerobic alactic (30-15IFT = 28.4 [4.7] vs 30-15IFT-CONT = 8.6% [2.1%], P < .001, d = 5.43) components.

CONCLUSIONS

Both 30-15IFT and 30-15IFT-CONT are mainly fueled by aerobic energy, but their metabolic profiles differ substantially in both aerobic and anaerobic alactic energy contribution. Due to the presence of inter-effort recovery, intermittent shuttle runs rely to a higher extent on anaerobic alactic energy and a fast, aerobic replenishment of PCr during the short breaks between shuttles.

Mechanical work in shuttle running as a function of speed and distance: Implications for power and efficiency

Biomechanics (and energetics) of human locomotion are generally studied at constant, linear, speed whereas less is known about running mechanics when velocity changes (because of accelerations, decelerations or changes of direction). The aim of this study was to calculate mechanical work and power and to estimate mechanical efficiency in shuttle runs (as an example of non-steady locomotion) executed at different speeds and over different distances. A motion capture system was utilised to record the movements of the body segments while 20 athletes performed shuttle runs (with a 180° change of direction) at three paces (slow, moderate and maximal) and over four distances (5, 10, 15 and 20 m). Based on these data the internal, external and total work of shuttle running were calculated as well as mechanical power; mechanical efficiency was then estimated based on values of energy cost reported in the literature. Total mechanical work was larger the faster the velocity and the shorter the distance covered (range: 2.3-3.7 J m^-1 kg^-1) whereas mechanical efficiency showed an opposite trend (range: 0.20-0.50). At maximal speed, over all distances, braking/negative power (about 21 W kg^-1) was twice the positive power. Present results highlight that running humans can exert a larger negative than positive power, in agreement with the fundamental proprieties of skeletal muscles in vivo. A greater relative importance of the constant speed phase, associated to a better exploitation of the elastic energy saving mechanism, is likely responsible of the higher efficiency at the longer shuttle distances.

Eight-Week Battle Rope Training Improves Multiple Physical Fitness Dimensions and Shooting Accuracy in Collegiate Basketball Players

Chen, WH, Wu, HJ, Lo, SL, Chen, H, Yang, WW, Huang, CF, and Liu, C. Eight-week battle rope training improves multiple physical fitness dimensions and shooting accuracy in collegiate basketball players. J Strength Cond Res 32(10): 2715-2724, 2018-Basketball players must possess optimally developed physical fitness in multiple dimensions and shooting accuracy. This study investigated whether battle rope (BR) training enhances multiple physical fitness dimensions, including aerobic capacity (AC), upper-body anaerobic power (AnP), upper-body and lower-body power, agility, and core muscle endurance, and shooting accuracy in basketball players and compared its effects with those of regular training (shuttle run [SR]). Thirty male collegiate basketball players were randomly assigned to the BR or SR groups (n = 15 per group). Both groups received 8-week interval training for 3 sessions per week; the protocol consisted of the same number of sets, exercise time, and rest interval time. The BR group exhibited significant improvements in AC (Progressive Aerobic Cardiovascular Endurance Run laps: 17.6%), upper-body AnP (mean power: 7.3%), upper-body power (basketball chest pass speed: 4.8%), lower-body power (jump height: 2.6%), core muscle endurance (flexion: 37.0%, extension: 22.8%, and right side bridge: 23.0%), and shooting accuracy (free throw: 14.0% and dynamic shooting: 36.2%). However, the SR group exhibited improvements in only AC (12.0%) and upper-body power (3.8%) (p < 0.05). The BR group demonstrated larger pre-post improvements in upper-body AnP (fatigue index) and dynamic shooting accuracy than the SR group did (p < 0.05). The BR group showed higher post-training performance in upper-body AnP (mean power and fatigue index) than the SR group did (p < 0.05). Thus, BR training effectively improves multiple physical fitness dimensions and shooting accuracy in collegiate basketball players.

Energy expenditure associated with walking speed and angle of turn in children

Purpose

Recent studies have suggested that turning is power intensive. Given the sporadic and irregular movement patterns of children, such findings have important implications for the assessment of true energy expenditure associated with habitual physical activity. The purpose of this study was to investigate the influence of walking speed and angle, and their interaction, on the energy expenditure of healthy children.

Methods

20 children (10.1 ± 0.5 years; 10 boys) participated in the study. On two separate days, participants completed a turning protocol involving 3-min bouts of walking at one of the 16 speed (2.5, 3.5, 4.5, and 5.5 km h^− 1) and angle (0°, 45°, 90°, and 180°) combinations, interspersed by 3 min seated rest. The movement involved 5 m straight walking interspaced with prescribed turns with speed dictated by a digital, auditory metronome. Breath-by-breath gas exchange was measured, in addition to tri-axial acceleration and magnetic field intensity recorded at 100 Hz.

Results

Mixed models revealed a significant main effect for speed (p < 0.006) and angle (p < 0.006), with no significant interaction between speed and angle (p > 0.006). Significant differences to straight-line walking energy expenditure within speed were established for 3.5 and 5.5 km h^− 1 for 180° turns (~ 13% and ~ 30% increase, respectively).

Conclusion

These findings highlight the importance of accounting for the magnitude and frequency of turns completed when estimating children’s habitual physical activity and have significant implications for the assessment of daily energy expenditure.

Investigating the relationship between energy expenditure, walking speed and angle of turning in humans

Recent studies have suggested that changing direction is associated with significant additional energy expenditure. A failure to account for this additional energy expenditure of turning has significant implications in the design and interpretation of health interventions. The purpose of this study was therefore to investigate the influence of walking speed and angle, and their interaction, on energy expenditure in 20 healthy adults (7 female; 28±7 yrs). On two separate days, participants completed a turning protocol at one of 16 speed- (2.5, 3.5, 4.5, 5.5 km∙h^-1) and angle (0, 45, 90, 180°) combinations, involving three minute bouts of walking, interspersed by three minutes seated rest. Each condition involved 5 m of straight walking before turning through the pre-determined angle with the speed dictated by a digital, auditory metronome. Tri-axial accelerometry and magnetometry were measured at 60 Hz, in addition to gas exchange on a breath-by-breath basis. Mixed models revealed a significant main effect for speed (F = 121.609, P < 0.001) and angle (F = 19.186, P < 0.001) on oxygen uptake (V˙O2) and a significant interaction between these parameters (F = 4.433, P < 0.001). Specifically, as speed increased, V˙O2 increased but significant increases in V˙O2 relative to straight line walking were only observed for 90° and 180° turns at the two highest speeds (4.5 and 5.5 km∙hr^-1). These findings therefore highlight the importance of accounting for the quantity and magnitude of turns completed when estimating energy expenditure and have significant implications within both sport and health contexts.

Accuracy of a 10 Hz GPS Unit in Measuring Shuttle Velocity Performed at Different Speeds and Distances (5 - 20 M)

The aim of this study was to validate the accuracy of a 10 Hz GPS device (STATSports, Ireland) by comparing the instantaneous values of velocity determined with this device with those determined by kinematic (video) analysis (25 Hz). Ten male soccer players were required to perform shuttle runs (with 180° change of direction) at three velocities (slow: 2.2 m·s^-1; moderate: 3.2 m·s^-1; high: maximal) over four distances: 5, 10, 15 and 20 m. The experiments were video-recorded; the "point by point" values of speed recorded by the GPS device were manually downloaded and analysed in the same way as the "frame by frame" values of horizontal speed as obtained by video analysis. The obtained results indicated that shuttle distance was smaller in GPS than video analysis (p < 0.01). Shuttle velocity (shuttle distance/shuttle time) was thus smaller in GPS than in video analysis (p < 0.001); the percentage difference (bias, %) in shuttle velocity between methods was found to decrease with the distance covered (5 m: 9 ± 6%; 20 m: 3 ± 3%). The instantaneous values of speed were averaged; from these data and from data of shuttle time, the distance covered was recalculated; the error (criterion distance-recalculated distance) was negligible for video data (0.04 ± 0.28 m) whereas GPS data underestimated criterion distance (0.31 ± 0.55 m). In conclusion, the inaccuracy of this GPS unit in determining shuttle speed can be attributed to inaccuracy in determining the shuttle distance.

Energetics (and kinematics) of short shuttle runs

PURPOSES

The energy cost of shuttle running (C netSR), over distances of 10-20 m, was reported to increase with the shuttle speed and to decrease with the shuttle distance. The aims of this study were to assess C netSR over a shorter distance (5 m), at different speeds, and to estimate the energy cost based on a simple kinematic analysis (C netK).

METHODS

Ten subjects (six basketball players, BP; four non-basketball players, NBP) performed ten shuttle runs (SR) with 30 s of passive recovery in-between, over a distance of 5 + 5 m (with a 180° change of direction); these experiments were repeated at different speeds (range 2-3.5 m s(-1)). The values of average (v mean) and maximal (v max) speed during each run were determined by means of kinematic analysis and C netK was calculated as: 0.96[Formula: see text]. C netSR was calculated based on data of oxygen uptake, blood lactate concentration and distance covered.

RESULTS

The relationships between C (J m(-1) kg(-1)) and v (m(.)s(-1)) are well described by C netK (all subjects) = 11.76v - 13.09, R (2) = 0.853; C netSR (BP) = 11.94v - 12.82, R (2) = 0.636; and C netSR (NBP) = 14.09v - 14.53, R (2) = 0.738. Hence C netSR ≈ C netK in BP, whereas C netSR > C netK in NBP (un-familiar with this specific motor task).

DISCUSSION

The calculations proposed in this study allow to estimate C of short SR based on simple measures of v max and can be utilized to develop training protocols in basketball as well as in other team sports (characterized by repeated sprints over short distances).

Repeated sprint ability in young basketball players: one vs. two changes of direction (Part 1)

The present study aimed to compare the changes of direction on repeated sprint ability (RSA) vs. intensive repeated sprint ability (IRSA) protocols in basketball. Eighteen young male basketball players performed on RSA [10 × 30-m (15 + 15-m, one change of direction)] and IRSA [10 × 30-m (10 + 10 + 10-m, two changes of direction)]. A correlation matrix between RSA, IRSA, "squat jump (SJ)-countermovement jump (CMJ)", footstep analysis and total distance in Yo-Yo intermittent recovery level 1 was performed. The best time, worst time, total time and the number of footsteps were significantly smaller in the RSA test compared to IRSA test (P < 0.001), even though they were significantly correlated with each other (r > 0.80, P < 0.05). Blood lactate level and fatigue index did not show any difference between tests. The sensibility of the two tests assessed by the Bland-Altman analysis revealed a small bias (<1.5%) for almost all variables. Moreover, almost all time variables of the two tests were significantly correlated with the SJ (r > 0.478, P < 0.05), CMJ (r > 0.515, P < 0.05) and Yo-Yo (r > 0.489, P < 0.05) performances. The IRSA provided a reliable method for assessing specific sprint ability (with 10-m legs for IRSA ~2.3 s vs. 15 m for RSA ~3 s) with a closer link to basketball game's actions (~2 s). Besides, IRSA could be an appropriate choice for assessing both RSA and changes of direction capacities in basketball players.

Energetics of Shuttle Runs: The Effects of Distance and Change of Direction

Shuttle runs can be used to study the physiological responses in sports (such as basketball) characterized by sprints (accelerations/decelerations) and changes of direction.

Purpose:

To determine the energy cost (C) of shuttle runs with different turning angles and over different distances (with different acceleration/deceleration patterns).

Methods:

Nine basketball players were asked to complete 6 intermittent tests over different distances (5, 10, 25 m) and with different changes of direction (180° at 5 and 25 m; 0°, 45°, 90°, and 180° at 10 m) at maximal speed (v ≍ 4.5 m/s), each composed by 10 shuttle runs of 10-s duration and 30-s recovery; during these runs oxygen uptake (VO2), blood lactate (Lab), and C were determined.

Results:

For a given shuttle distance (10 m) no major differences where observed in VO2 (~33 mL · min−1 · kg−1), Lab (~3.75 mM), and C (~21.2 J · m−1 · kg−1) when the shuttle runs were performed with different turning angles. For a given turning angle (180°), VO2 and Lab were found to increase with the distance covered (VO2 from 26 to 35 mL · min−1 · kg−1; Lab from 0.7 to 7.6 mM) while C was found to decrease with it (from 29.9 to 10.6 J · m−1 · kg−1); the relationship between C and d (m) is well described by C = 92.99 × d0.656, R2 = .971.

Conclusions:

The metabolic demands of shuttle tests run at maximal speeds can be estimated based on the running distance, while the turning angle plays a minor role in determining C.

The relationship between running velocity and the energy cost of turning during running

Ball game players frequently perform changes of direction (CODs) while running; however, there has been little research on the physiological impact of CODs. In particular, the effect of running velocity on the physiological and energy demands of CODs while running has not been clearly determined. The purpose of this study was to examine the relationship between running velocity and the energy cost of a 180°COD and to quantify the energy cost of a 180°COD. Nine male university students (aged 18–22 years) participated in the study. Five shuttle trials were performed in which the subjects were required to run at different velocities (3, 4, 5, 6, 7, and 8 km/h). Each trial consisted of four stages with different turn frequencies (13, 18, 24 and 30 per minute), and each stage lasted 3 minutes. Oxygen consumption was measured during the trial. The energy cost of a COD significantly increased with running velocity (except between 7 and 8 km/h, p = 0.110). The relationship between running velocity and the energy cost of a 180°COD is best represented by a quadratic function (y = −0.012+0.066x +0.008x², [r = 0.994, p = 0.001]), but is also well represented by a linear (y = −0.228+0.152x, [r = 0.991, p<0.001]). These data suggest that even low running velocities have relatively high physiological demands if the COD frequency increases, and that running velocities affect the physiological demands of CODs. These results also showed that the energy expenditure of COD can be evaluated using only two data points. These results may be useful for estimating the energy expenditure of players during a match and designing shuttle exercise training programs.