Energetic Profile of the Basketball Exercise Simulation Test in Junior Elite Players

Athlete Monitoring Systems in Elite Men's Basketball: Challenges, Recommendations, and Future Perspectives

Athlete monitoring systems (AMSs) provide a centralized platform for integrating, processing, analyzing, and graphing various monitoring data to help coaches manage the rigorous demands of elite men's basketball players, who frequently participate in high-stress games with minimal recovery time. This review synthesizes current challenges in deploying AMSs, underscores their role in injury prevention and performance optimization, and discusses technological advances that could enhance their utility. Key challenges include selecting appropriate monitoring methods based on human and financial resources, accuracy of data collection, real-time data processing, and personalization of training regimens. Due to the weaknesses and limitations of each monitoring method, it is recommended that both objective (e.g., external load data, heart rate measures, and biomarkers) and subjective (athlete-reported outcome measures) monitoring data be integrated into an AMS to provide a holistic insight of the athlete's health and readiness. In addition, decision support systems integrated into an AMS can help coaches quickly gain an overview of their players' current condition and make informed decisions about daily load and recovery management. In this context, future perspectives suggest the potential for AMSs to incorporate predictive analytics and artificial intelligence to further enhance decision-making processes in elite men's basketball. Our findings underscore the need for continued innovation and rigorous validation of AMS technologies to ensure they meet the evolving demands of professional sports environments.

The reliability and discriminant validity of physical, technical, and perceptual-physiological measures during a game-specific basketball activity simulation protocol

Activity simulation protocols offer useful applications in research and practice; however, the specificity of such protocols to basketball game-play is currently lacking. Consequently, this study aimed to develop a game-specific basketball activity simulation protocol representative of typical playing durations and assess its reliability and discriminant validity. The simulation protocol was modified from an original version (i.e., Basketball Exercise Simulation Test) to incorporate regular breaks indicative of time-outs, free-throws, and substitutions. Twelve competitive male and female adult basketball players competing in the fourth or fifth Spanish basketball division underwent repeated trials of the simulation protocol (min. 4 to max. 14 days apart) for reliability analyses. In turn, 13 competitive male (fifth division), 9 competitive female (fourth division), and 13 recreational male adult basketball players completed the simulation protocol to assess discriminant validity via comparisons between sexes (competitive players) and playing levels (males). A range of physical, technical, and perceptual-physiological variables were collected during and following the simulation protocol. Several physical and heart rate variables displayed the strongest reliability (intraclass correlation coefficient [ICC] = 0.72-0.96; coefficient of variation [CV] = 1.78-6.75%), with physical decrement, technical, blood lactate concentration, and rating of perceived exertion (RPE) variables having the weakest (ICC = 0.52-0.75; CV = 10.34-30.85%). Regarding discriminant analyses between sexes, males demonstrated significantly greater physical outputs in several variables and lower RPE compared to females (p < 0.05, moderate-to-large effects). Comparisons between playing levels revealed competitive males had significantly greater physical outputs across many variables, alongside higher mean heart rate and lower RPE than recreational males (p < 0.05, moderate-to-large effects). This study presents a novel game-specific basketball activity simulation protocol replicating actual playing durations and game configurations that might be successfully applied for both training and research purposes. Reliability statistics are provided for several variables to inform end-users on potential measurement error when implementing the simulation protocol. Discriminant validity of the simulation protocol was supported for several variables, suggesting it may hold practical utility in benchmarking or selecting players. Future research on this topic is encouraged examining wider samples of male and female basketball players at different levels as well as additional forms of validity for the protocol.

The contribution of energy systems during 30-second lower body Wingate anaerobic test in combat sports athletes: Intermittent versus single forms and gender comparison

Combat sports, encompassing a range of activities from striking and grappling to mixed and weapon-based disciplines, have witnessed a surge in popularity worldwide. These sports are demanding, requiring athletes to harness energy from different metabolic pathways to perform short, high-intensity activities interspersed with periods of lower intensity. While it is established that the anaerobic alactic (ATP-PC) and anaerobic lactic systems are pivotal for high-intensity training sessions typical in combat sports, the precise contribution of these systems, particularly in varied training modalities such as single (SMT) and intermittent (IST) forms of the 30-second Wingate test, remains inadequately explored. This study aims at comparing performance outputs, physiological responses and gender differences during the SMT and IST forms of the 30-second Wingate test. Thirty-three highly trained combat sports athletes (17 women, 16 men; 10 boxing, 8 wrestling, 8 taekwondo and 7 karate) randomly performed SMT and IST. The IST consisted of three 10-second all-out attempts separated by 30 seconds of passive recovery, whereas the SMT was a single 30-second maximal effort. Resting, exercise and post-exercise oxygen uptake and peak blood lactate value were used to determine the metabolic energy demands via the PCr-LA-O2 method. The findings showed that total metabolic energy expenditure (TEE), ATP-PCr system contribution and the output of mechanical variables were higher in the IST than in the SMT form (all p<0.001). In contrast, the contribution of glycolytic and oxidative systems was higher in the SMT form (all p<0.001). However, exercise form and gender interaction were not significant (p>0.05). In combat sports, performance is not only determined by physiological and technical skills but also by metabolic energy input and efficiency. Therefore, our results can provide a comparison regarding the effects of exercise type and gender on metabolic energy metabolism to design the training of combat sports athletes.

Energy System Contributions in Repeated Sprint Tests: Protocol and Sex Comparison

The aim of this study was to investigate the energy system contributions to different repeated sprint protocols and also to determine sex-related differences in these contributions. Sixteen men and fourteen women team sport athletes randomly performed two cycling repeated sprint protocols with the same total duration (10 x 6 s and 6 x 10 s). Relative peak power (RPP), relative mean power (RMP), performance decrement (PD), oxygen uptake (VO2), blood lactate (LA), heart rate (HR) and ratings of perceived exertion (RPEs) were measured. The contributions of energy systems were calculated from oxygen consumption and lactate values during rest, exercise and recovery phases based on mathematical methods. Findings indicate that men had higher RPP and RMP. RPP did not differ according to protocols, while RMP was higher in the 10 x 6 s protocol. The sex effect in PD was similar; however, it was higher in the 6 x 10 s protocol. The effects of protocols on the maximum HR and LA were similar; however, the 6 x 10 s protocol resulted in higher RPEs. In both protocols women had higher ATP-PCr and men had higher glycolytic system contribution with similar oxidative system contribution. In addition, the 10 x 6 s protocol had higher ATP-PCr system contribution and the 6 x 10 s protocol had higher glycolytic system and oxidative system contributions. In conclusion, the contribution of energy systems, physiological and performance variables showed variations according to sex and different protocols.

Differences in countermovement vertical jump force-time metrics between starting and non-starting professional male basketball players

With force plates being widely implemented for neuromuscular performance assessment in sport-specific settings and various force-time metrics being able to differentiate athletes based on their performance capabilities, the purpose of the present study was to examine the differences in countermovement vertical jump (CVJ) characteristics between starting and non-starting professional male basketball players (e.g., ABA League). Twenty-three athletes (height = 199.2 ± 7.7 kg, body mass = 94.2 ± 8.2 kg, age = 23.8 ± 4.9 years) volunteered to participate in the present investigation. Upon completion of a standardized warm-up protocol, each athlete performed three maximal-effort CVJs without an arm swing while standing on a uni-axial force plate system sampling at 1,000 Hz. Independent t-tests were used to examine statistically significant differences (p < 0.05) in each force-time metric between starters (n = 10) and non-starters (n = 13). No significant differences in any of the CVJ force-time metrics of interest were observed between the two groups, during both the eccentric and concentric phases of the movement (i.e., impulse, duration, peak velocity, and mean and peak force and power). Moreover, starters and non-starters demonstrated similar performance on CVJ outcome (e.g., jump height) and strategy metrics (e.g., countermovement depth). Overall, these findings suggest that at the professional level of play, the ability to secure a spot in the starting lineup is not primarily determined by the players' CVJ performance characteristics.

Training drills in high performance badminton-effects of interval duration on internal and external loads

Purpose: The aim of the present study was to analyze the impact of interval duration on training loads and technical skill performance in high performance badminton drills. Methods: On three experimental days, 19 internationally ranked players (13 male: 22.7 ± 3.8 years, 180 ± 6 cm, 71.5 ± 6.1 kg; 6 females: 20.4 ± 2.5 years, 168 ± 4 cm, 59.8 ± 6.0 kg) completed one of three protocols (T₁₀, T₃₀, and T₅₀) of a typical badminton specific drill, the so-called "Multifeeding" (the coach feeds shuttlecock without break in a random order) in a counterbalanced order. The protocols varied in interval duration (10, 30, and 50 s) but were matched for the rally-to-rest-ratio (1:1) and active playing time (600 s). Cardiorespiratory responses (portable spirometry, chest belt), energy metabolism (levels of blood lactate, La), rate of perceived exertion (RPE), player's kinematics (Local Positioning System), and technical skill performance (video analysis) were measured. Results: Average oxygen consumption (T₁₀ 45 ± 6; T₃₀ 46 ± 7; T₅₀ 44 ± 6 mL min^-1·kg^-1), Energy expenditure (886 ± 209; 919 ± 176; 870 ± 206 kcal h^-1), heart rate (164 ± 13; 165 ± 11; 165 ± 10 bpm) and RPE (16 ± 2; 17 ± 2; 17 ± 2) did not differ between the protocols. Respiratory exchange ratio (RER) and La significantly increased depending on interval duration (RER: 0.90 ± 0.05; 0.93 ± 0.03; 0.96 ± 0.04 and La: 3.6 ± 2.0; 5.6 ± 3.0; 7.3 ± 2.3 mmol l^-1). Stroke frequency (SF; 0.58 ± 0.05; 0.57 ± 0.05; 0.55 ± 0.06 strokes·s^-1) was similar while distance covered, and average running velocity were significantly lower for T₅₀ compared to T₁₀ (76 ± 17; 70 ± 13; 65 ± 11 m min^-1). Moreover, jump frequency in T₃₀ was higher than in T₁₀ (6.7 ± 3.1; 8.8 ± 3.8; 8.5 ± 4.2 jumps·min^-1), whereas differences in internal and external loads were not associated with changes in stroke precision (errors: 16 ± 6; 19 ± 4; 18 ± 4%; accuracy: 22 ± 6; 24 ± 8; 23 ± 8%). Conclusion: Anaerobic metabolic stimulus increases while running distance and velocity decrease, in case of longer interval durations. Even though there was no impact on stroke precision, extending the intervals beyond 30 s might impair external training load and skill performance. Consequently, interval duration should be defined carefully depending on the training goals.

Acute physiological, perceived exertion and enjoyment responses during a 4-week basketball training: a small-sided game vs. high-intensity interval training

Introduction

Although previous research found that small-sided game (SSG) training was more enjoyable than high-intensity interval training (HIT) in various sports, no data were provided during longer training period in basketball. Furthermore, the comparison of internal loads between the two training approaches needs to be further examined. Thus, this study aimed to examine the acute physiological, perceived exertion and enjoyment responses during 4-week progressive basketball SSG or HIT programs.

Methods

Nineteen female collegiate basketball players were randomly assigned to two groups that performed either HIT (n = 10) or SSG (n = 9) 3 times per week for 4 continuous weeks. Average and percentage of maximal heart rate (HR_mean and %HR_max), rating of perceived exertion (RPE), and physical activity enjoyment (PACES) were determined during each training session.

Results

There was a main group effect in PACES (p < 0.001; ηp2 = 0.44, moderate), and SSG had higher PACES than HIT in each week (p < 0.05). There were no significant interactions or main group effects in HR_mean, %HR_max or RPE, but a main time effect was found in HR_mean (p = 0.004; ηp2 = 0.16, minimum), %HR_max (p < 0.001; ηp2 = 0.25, minimum), and RPE (p < 0.001; ηp2 = 0.31, moderate), respectively. In the SSG group, although no significant differences were found in HR responses, %HR_max was below 90% in week 1 and week 2. Accompanied with changes in %HR_max, RPE in week 1 and week 2 was lower than that in week 3 and week 4 (p < 0.05).

Conclusion

Our findings suggest that SSG and HIT elicit similar acute HR response and RPE level, but SSG is perceived as more enjoyable and therefore it is more likely to increase exercise motivation and adherence comparing to HIT. Moreover, it seems that half-court, 2 vs. 2 SS Gtraining format with modified rules and lasting ≥ 7.5 min should be prescribed as an enjoyable training alternative to provide optimal cardiovascular stimuli (> 90% of HR_max) for female basketball players.

The impact of sport-specific physical fitness change patterns on lower limb non-contact injury risk in youth female basketball players: a pilot study based on field testing and machine learning

Background: In recent years, identifying players with injury risk through physical fitness assessment has become a hot topic in sports science research. Although practitioners have conducted many studies on the relationship between physical fitness and the likelihood of injury, the relationship between the two remains indeterminate. Consequently, this study utilized machine learning to preliminary investigate the relationship between individual physical fitness tests and injury risk, aiming to identify whether patterns of physical fitness change have an impact on injury risk. Methods: This study conducted a retrospective analysis by extracting the records of 17 young female basketball players from the sport-specific physical fitness monitoring and injury registration database in Fujian Province. Sports-specific physical fitness tests included physical performance, physiological, biochemical, and subjective perceived responses. The data for each player was standardized individually using Z-scores. Synthetic minority over-sampling techniques and edited nearest neighbor algorithms were used to sample the training set to address the negative impact of class imbalance on model performance. Feature extraction was performed on the dataset using linear discriminant analysis, and the prediction model was constructed using the cost-sensitive neural network. Results: The 10 replicate 5-fold stratified cross-validation showed that the lower limb non-contact injury prediction model based on the cost-sensitive neural network had achieved good discrimination and calibration (average Precision: 0.6360; average Recall: 0.8700; average F2-Score: 0.7980; average AUC: 0.8590; average Brier-score: 0.1020), which could be well applied in training practice. According to the attribution analysis, agility and speed were important physical attributes that affect youth female basketball players' non-contact lower limb injury risk. Specifically, there was enhance in the performance of the 1-min double under, accompanied by an increase in urinary ketone and urinary blood levels following the agility test. The 3/4 basketball court sprint performance improved, while urinary protein and RPE levels decreased after the speed test. Conclusion: The sport-specific physical fitness change pattern can impact the lower limb non-contact injury risk of young female basketball players in Fujian Province, specifically in terms of agility and speed. These findings will provide valuable insights for planning athletes' physical training programs, managing fatigue, and preventing injuries.

The Contribution of Energy Systems in Repeated-Sprint Protocols: The Effect of Distance, Rest, and Repetition

Purpose: This study aims to investigate the effects of rest intervals, sprint distance, and number of repetitions on performance variables, physiological responses, and energy system contributions in repeated-sprint protocols when total distance variable was the controlled (300 m). Method: Sixteen male soccer players participated in this study. The four protocols, each totaling a distance of 300 m, consisted of the combination of 15 and 30 m sprints with 30 s rest intervals (15meters30sec and 30meters30sec, respectively) and 1:5 work-rest ratios (15meters12sec and 30meters22sec, respectively). Aerobic, glycolytic, and phosphagen energy systems' contributions were calculated from the oxygen consumption (VO2) during the exercise, net lactate production, and the recovery VO2 kinetics using mono-exponential models. Repeated measures ANOVA with the Bonferroni correction was applied to examine the hypothesized differences. Results: The findings indicated that total sprint duration (F3:45=281.14; p<0.001), percentage of performance decline (F3:45=16.58; p<0.001), delta lactate (F3:45=39.72, p<0.001), rating of perceived exertion (F3:45=28.64; p<0.001), energy demand (F3:45=101.6; p<0.001), VO2 during the rest intervals (F3:45=42.72; p<0.001), and the absolute contribution of glycolytic (F3:45=119.6; p<0.001) and phosphagen energy systems (F3:45=72.9; p<0.001) were lowest in the 15meters30sec compared to other protocols. However, the relative contribution of aerobic system was greatest in the 15meters30sec compared to other protocols (F3:45=28.1, p<0.001). Both absolute (F3:45=119.6; p<0.001) and relative contribution of glycolytic system (F3:45=88.5, p<0.001) were greatest in the 30meters22sec compared to other protocols. Conclusion: This study showed that increasing sprint distance when rest interval is equal and decreasing rest interval when sprint distance is equal can increase the glycolytic system contribution.

A randomized open-labeled study to examine the effects of creatine monohydrate and combined training on jump and scoring performance in young basketball players

Background

Creatine monohydrate (CrM) supplementation has been shown to be an effective and safe nutritional supplement to improve performance; however, the impact of CrM supplementation in young basketball players is less clear. This study evaluated the effects of CrM supplementation during a strength and conditioning training (SCT) program on lower-limb strength parameters and performance in under-16 (U16) basketball players.

Methods

Twenty-three male U16 basketball players participated in this study (14.3 ± 0.4 years; BMI: 20.7 ± 2.2 kg∙m⁻²). The players were randomly assigned to either a CrM group (n = 12) that ingested 0.1 g·kg⁻¹·day⁻¹ of CrM or to a non-supplemented control group (n = 11, CON). The athletes participated in an 8-week SCT program consisting of two lower-limb resistance-training sessions and two plyometric sessions per week. Squat jump (SJ), drop jump (DP), countermovement jump (CMJ), and Abalakov (ABK) jump power tests as well as basketball performance (points and minutes per game) were measured before, during and/or after the intervention. Data were analyzed using a general linear model with repeated measures with independent Student’s t-test pairwise comparisons.

Results

The results (95% confidence interval for mean change from baseline) show that there were significant differences for all variables for CrM and CON, respectively: SJ (cm): 2.6 – 6.4, P < 0.01 and 2.2–5.1 P < 0.01; DJ (cm): 2.5–5.6, P < 0.01, and 1.8–4.4, P < 0.01; CMJ (cm): 0.3–0.8, P < 0.01, and 0.2–0.5, P < 0.01; ABK (cm): 2.8–5.5, P < 0.01 and 0.7–2.6, P = 0.003. A significant group x time interaction (p = 0.003, η_p² = 0.342) was observed in ABK performance. No significant group x time effects were seen in squat jump (p = 0.449, η_p² = 0.028), drop jump (p = 0.143, η_p² = 0.099), or counter movement jump (p = 0.304, η_p² = 0.05). A significant interaction effect was also observed in points per game (p = 0.049, η_p² = 0.149), while a non-significant but medium effect was seen in minutes per game (p = 0.166, η_p² = 0.094).

Conclusions

CrM supplementation in conjunction with resistance and plyometric training increased the lower-limb ABK power and scoring performance in U16 basketball players.

Energetics of Floor Gymnastics: Aerobic and Anaerobic Share in Male and Female Sub-elite Gymnasts

Background

Artistic gymnastics is a popular Olympic discipline where female athletes compete in four and male athletes in six events with floor exercise having the longest competition duration in Women’s and Men’s artistic gymnastics (WAG, MAG). To date no valid information on the energetics of floor gymnastics is available although this may be important for specific conditioning programming. This study evaluated the metabolic profile of a simulated floor competition in sub-elite gymnasts.

Methods

17 (9 male, 8 female) sub-elite gymnasts aged 22.5 ± 2.6y took part in a floor-training-competition where oxygen uptake was measured during and until 15 min post-exercise. Additionally, resting and peak blood lactate concentration after exercise were obtained. The PCr-LA-O2 method was used to calculate the metabolic energy and the relative aerobic (WAER), anaerobic alactic (WPCr) and anaerobic lactic (WBLC) energy contribution. Further, the athletes completed a 30 s Bosco-jumping test, a countermovement jump and a drop jump.

Results

The competition scores were 9.2 (CI:8.9–9.3) in WAG and 10.6 (CI:10.4–10.9) in MAG. The metabolic profile of the floor routine was mainly aerobic (58.9%, CI: 56.0–61.8%) followed by the anaerobic alactic (24.2%, CI: 21.3–27.1%) and anaerobic lactic shares (16.9%, CI:14.9–18.8%). While sex had a significant (p = .010, d = 1.207) large effect on energy contribution, this was not the case for competition duration (p = .728, d = 0.061). Relative energy contribution of WAG and MAG differed in WAER (64.0 ± 4.7% vs. 54.4 ± 6.8%, p = .004, d = 1.739) but not in WPCr (21.3 ± 6.1% vs. 26.7 ± 8.0%, p = .144, d = 0.801) and WBLC (14.7 ± 5.4% vs. 18.9 ± 4.2%, p = .085, d = 0.954). Further no correlation between any energy share and performance was found but between WPCr and training experience (r = .680, p = .044) and WBLC and competition level (r = .668, p = .049).

Conclusion

The results show a predominant aerobic energy contribution and a considerable anaerobic contribution with no significant difference between anaerobic shares. Consequently, gymnastic specific aerobic training should not be neglected, while a different aerobic share in WAG and MAG strengthens sex-specific conditioning. All in all, the specific metabolic share must secure adequate energy provision, while relative proportions of the two anaerobic pathways seem to depend on training and competition history.

Reliability of the 3-Component Model of Aerobic, Anaerobic Lactic, and Anaerobic Alactic Energy Distribution (PCr-LA-O2) for Energetic Profiling of Continuous and Intermittent Exercise

Purpose: To assess the test–retest reliability of the continuous (PCr-LA-O2) and intermittent (PCr-LA-O2int) version of the 3-component model of energy distribution in an applied setting. Methods: Sixteen male handball players (age 23 [3] y, height 185 [7] cm, weight 85 [14] kg) completed the 30–15 Intermittent Fitness Test (30–15IFT) twice. Performance was assessed by peak speed (speed of the last successfully completed stage of the 30–15IFT [VIFT], in kilometers per hour) and time to exhaustion (in seconds). Oxygen uptake (in milliliters per kilogram per minute) and blood lactate concentrations (in millimoles per liter) were obtained before, during, and until 15 minutes after exercise. Total metabolic energy (in joules per kilogram), total metabolic power (in watts per kilogram), and energy shares (in joules per kilogram and percentage) of the aerobic (energy contribution of the aerobic system [WAERint]), anaerobic lactic, and anaerobic alactic (anaerobic alactic energy [WPCrint]) systems were calculated using both model versions, respectively. Results: Test–retest reliability was very good for VIFT (limits of agreement [LoA]: −1.13 to 0.63 km·h−1, coefficient of variation [CV%] 1.68), time to exhaustion (LoA: −101 to 38 s, CV% 2.92), peak oxygen uptake (LoA: −2.68 to 4.04 mL·min−1·kg−1, CV% 1.48), and peak heart rate (−6.9 to 7.7 beats·min−1, CV% 1.1), but moderate for change in blood lactate concentration (LoA: −3.84 to 4.07 mmol·L−1, CV% 11.43). Reliability of the modeled total energy and its fractions were high for total metabolic energy (LoA: −1489 to 1177 J·kg−1, CV% 2.88), total metabolic power (LoA: −2.0 to 1.9 W·kg−1, CV% 3.58), contribution of aerobic (LoA: −1673 to 1283 J·kg−1, CV% 3.62), WAERint (LoA: −1760 to 2160 J·kg−1, CV% 6.04), and moderate for anaerobic alactic (LoA: −368 to 439 J·kg−1, CV% 14.85), WPCrint (LoA: −1707 to 988 J·kg−1, CV% 9.98), and energy share of anaerobic lactic concentration (LoA: −229 to 235 J·kg−1, CV% 11.43). Conclusion: Considering the inherent fluctuations of the underlying energetics, the reliabilities of both versions of the 3-component model of energy distribution are acceptable for applied settings.

Effects of sprint distance and repetition number on energy system contributions in soccer players

Background/objective

This study aims to compare the effect of sprint distance and repetition number on performance, physiological responses, and energy systems contributions.

Methods

Eighteen male university league soccer players (age: 19.9 ± 1.6 years, height: 177.9 ± 4.7 cm, body mass: 72.4 ± 6.3 kg, percentage body fat: 8.9 ± 1.8, training experience: 7.4 ± 1.6 years) completed two different repeated sprint protocols: 20 × 20 m (20 × 20) and 10 × 40 m (10 × 40) with 15s and 30s rest intervals, respectively. Oxygen uptake (VO₂) were measured during the rest, exercise, and recovery phases. Rest and peak blood lactate concentrations were determined. Using VO₂ and lactate values, the energy system contributions were calculated using a mono-exponential model and mathematical calculations. Energy systems contributions and total energy expenditure (TEE) were calculated both for the entire protocol (overall) and for the sprints only.

Results

Ratings of perceived exertion (RPE), peak and mean heart rate (HR) responses were significantly higher in the 20 × 20 whereas lactate response was higher in the 10 × 40. TEE was similar between the 10 × 40 (586.3 ± 60.8 kJ) and 20 × 20 (595.6 ± 57.5 kJ). For overall estimations, the 10 × 40 and 20 × 20 presented similar results of oxidative (47.5 ± 5.4 vs 45.7 ± 5.1 kJ min⁻¹) and phosphagen (44.7 ± 5.4 vs (42.9 ± 4.8 kJ min⁻¹) systems contributions whereas glycolytic contribution was higher in the 10 × 40 (15.5 ± 2.2 vs 12.8 ± 2.3 kJ min⁻¹). For sprints only estimation, the phosphagen (257.6 ± 31.5 vs 225.2 ± 28.2 kJ min⁻¹), glycolytic (89.4 ± 13.4 vs 67.3 ± 12.5 kJ min⁻¹), and oxidative (76.9 ± 6.9 vs 72.0 ± 7.9 2 kJ min⁻¹) systems contributions were higher in the 10 × 40.

Conclusions

Although HR and RPE responses were higher in the 20 × 20, phosphagen (during sprints) and glycolytic (during both sprints and overall protocol) were higher in the 10 × 40 protocol. Therefore, the 10 × 40 protocol seems more reasonable for developing or evaluating the anaerobic systems.

Energy pathway contributions during 60-second upper-body Wingate test in Greco-Roman wrestlers: intermittent versus single forms

This study aimed to investigate the energy pathway contributions and physiological and performance responses between a 10 × 6-second intermittent sprint test (IST) and a 60-second single maximal test (SMT). Seventeen highly trained male Greco-Roman wrestlers participated in this study. Participants completed the 60-second upper-body Wingate tests, both intermittent and single forms. The contributions of the oxidative, glycolytic, and ATP-PCr pathways were estimated using mathematical methods based on lactate values and oxygen consumption kinetics of rest, exercise, and recovery phases. The main findings indicated that total energy expenditure (TEE) and the contribution of oxidative, glycolytic, and ATP-PCr pathways were 514 kJ, 45%, 11%, and 44% for IST (overall: sprints + rest intervals); 333 kJ, 14%, 17%, and 69% for IST (sprints only); and 159 kJ, 31%, 38%, and 31% for SMT, respectively. TEE and ATP-PCR pathway contributions were higher in the IST (both overall and sprint only), whereas glycolytic pathway contribution and delta lactate were higher in the SMT. Absolute oxidative contribution was similar, but relative oxidative contribution was higher in the SMT. Additionally, mean power was higher in the IST than SMT, whereas peak power, peak and mean heart rate, and ratings of perceived exertion were similar.

Energetic Profiles of the Yo-Yo Intermittent Recovery Tests 1 and 2

Purpose: To analyze the energetic profiles of the Yo-Yo Intermittent Recovery Tests 1 and 2 (YYIR1 and YYIR2). Methods: Intermittent running distance (IR1D and IR2D), time to exhaustion (IR1T and IR2T), and total recovery time between shuttles (IR1R and IR2R) were measured in 10 well-trained male athletes (age 24.4 [2.0] y, height 182 [1] cm, weight 75.8 [7.9] kg). Respiratory gases and blood lactate (BLC) were obtained preexercise, during exercise, and until 15 min postexercise. Metabolic energy, average metabolic power , and energy share (percentage of aerobic [WAER], anaerobic lactic [WBLC], and anaerobic alactic energy system [WPCr]) were calculated using the PCr-La-O2 method. Results: Peak oxygen consumption was possibly higher in YYIR2 (60.3 [5.1] mL·kg−1·min−1) than in YYIR1 (P = .116, 57.7 [4.5] mL·kg−1·min−1, d = −0.58). IR1D, IR1T, and IR1R were very likely higher than IR2D, IR2T, and IR2R, respectively (P < .001, 1876 [391] vs 672 [132] m, d = −2.83; P < .001, 916 [175] vs 304 [57] s, d = −3.03; and P < .001, 460 [100] vs 150 [40] s, d = −2.83). Metabolic energy was most likely lower in YYIR2 than in YYIR1 (P < .001, 493.5 [118.1] vs 984.8 [171.7] kJ, d = 3.24). Average metabolic power was most likely higher in YYIR2 than in YYIR1 (P < .001, 21.5 [1.7] vs 14.5 [2.2] W·kg−1, d = 3.54). When considering aerobic phosphocreatine restoration during breaks between shuttles, WAER (P = .693, 49% [10%] vs 48% [5%], d = −0.16) was similar, WPCr (P = .165, 47% [11%] vs 42% [6%], d = −0.54) possibly higher, and WBLC (P < .001, 4% [1%] vs 10% [3%], d = 1.95) almost certainly lower in YYIR1 than in YYIR2. Conclusions: WAER and WPCr are predominant in YYIR1 and YYIR2 with almost identical WAER. Higher IR1D and IR1T in YYIR1 result in higher metabolic energy but lower average metabolic power and slightly lower peak oxygen consumption. Higher IR1R allows for higher reliance on WPCr in YYIR1, while YYIR2 requires a higher fraction of WBLC.

Physical and Physiological Profiles of Aerobic and Anaerobic Capacities in Young Basketball Players

Current trends in the analysis of the physical fitness of athletes are based on subjecting the athlete to requirements similar to those found in competition. Regarding physical fitness, a thorough study of the capacities that affect the development of team sports in different ages and gender is required since the demands are not equivalent. The objective of this paper was to characterize the physical-physiological demands of athletes in an aerobic and anaerobic test specific to basketball players, as well as the evolution of the variables according to age and gender. The research was carried out in 149 players from different training categories (n = 103 male; n = 46 female). The athletes performed two field tests that evaluated both aerobic capacity and lactic anaerobic capacity. Each athlete was equipped with an inertial device during the tests. Sixteen variables (equal in both tests) were analyzed. Three of them evaluated technical-tactical aspects, four variables of objective internal load, six kinematic variables of objective external load (two related to distance and four related to accelerometry) and three neuromuscular variables of objective external load. The obtained results show significant differences in the variables analyzed according to the age and gender of the athletes. They are mainly due to factors related to the anthropometric maturation and development inherent in age and have an impact on the efficiency and technical and tactical requirements of the tests carried out and, therefore, on the obtained results in the tests.

Comparison of maturation and physical performance in basketball athletes of different playing positions

Abstract The aim of this study was to compare the characteristics of somatic maturation, anthropometric and physical performance (vertical jump and aerobic power) in young basketball players of different playing positions (under 13 years) and analyze these relationships using Peak Height Velocity (PHV) as a measure of somatic maturation. For this, 26 male athletes were evaluated. Anthropometric variables were: body mass, standing and sitting height, and length of lower limbs. Maturation was determined by age at PHV. Physical performance was determined by lower limb power (counter movement jump - CMJ) and aerobic power (Intermittent Recovery Test) tests. MANOVA reported significant differences (p<0.05) among playing positions regarding variables Maturity Offset, estimated PHV age, standing height, sitting height, estimated leg length, body mass and Yo-Yo IR1. In addition, it was identified that point guards reached estimated PHV at later age than their peers who act as small forwards and centers. Regarding CMJ, no significant differences were identified among playing positions, but in relation to aerobic power, point guards and small forwards presented higher performance. These findings confirm that maturation has great effect on growth and physical performance measures and the estimated PHV age is an applicable tool in young athletes, mainly aiding professionals in structuring the teaching-learning- training process in this age group.