The Relationships Between External and Internal Workloads During Basketball Training and Games

3 × 3 Basketball: Neuromuscular Fatigue Develops While External Intensities Are Maintained in Late Tournament Stages

PURPOSE

To evaluate physical demands and acute neuromuscular responses in official 3 × 3 basketball tournaments.

METHODS

Thirty-three male players (age: 23.1 [5.6] y) were monitored during 2 tournaments, featuring 3 group games (GG1, GG2, and GG3) on day 1 and the round of 16 (R16), quarterfinal (QF), semifinal (SF), and final games on day 2. External intensity (movement intensity) was measured using microsensors. Bilateral countermovement-jump testing was conducted before the start of the tournaments and immediately after each game using MyJump Lab to measure jump height, time to takeoff (TTTO), and modified Reactive Strength Index (RSImod).

RESULTS

Linear mixed models revealed no significant differences for movement intensity (P = .195) but a practically meaningful decrease (>smallest worthwhile change [SWC]) in the QF compared with GG1, GG2, GG3, R16, and SF. No significant (P = .128) or practically meaningful differences were found for jump height. TTTO was shorter following GG3 compared with baseline (P = .027, effect size: moderate). Practically meaningful (>SWC) decreases in TTTO were found from baseline to post-GG1, GG2, and GG3, while TTTO increased on day 2 compared with day 1 and after SF and Final compared with R16 and QF. RSImod significantly (all P < .05) and practically improved (>SWC) from baseline to post-GG1, GG2, and GG3 (effect size: trivial); practically meaningful changes were also identified on day 2, with poorer RSImod following QF compared with all day 1 games and poorer values post-SF compared with post-GG3.

CONCLUSIONS

While players maintained in-game physical intensities across tournament stages, neuromuscular status worsened on day 2, suggesting the presence of fatigue. Strategies aimed at supporting players' physical performances in late 3 × 3 tournament stages should be identified.

The Relationships Between Training-Load Models in 3 × 3 Basketball Games

PURPOSE

To quantify the relationship between load models during official games of the novel 3 × 3 basketball sport.

METHODS

Forty-one adult male players were monitored across three 3 × 3 basketball official tournaments. Players wore Firstbeat Sports microsensors to quantify external (Movement Load) and internal physiological (summated-heart-rate-zones [SHRZ]) loads. Additionally, rating of perceived exertion (RPE) scores were obtained after each game to calculate session RPE (sRPE) loads as internal perceived load. Repeated-measures correlation analyses were performed to assess the relationships between Movement Load and internal loads (SHRZ and sRPE), and between SHRZ and sRPE.

RESULTS

External load (Movement Load) and internal physiological load (SHRZ) had a very large correlation (r = .76, P < .001). External load was also largely correlated with internal perceived load (sRPE; r = .57, P < .001). The correlation between SHRZ and sRPE was moderate (r = .47, P < .001).

CONCLUSION

During 3 × 3 basketball games, large to very large relationships exist between external- and internal-load variables. This information allows practitioners to anticipate internal responses of players to games based on the external load imposed, thus optimizing training-load prescription strategies.

Description and Classification of Training Drills, Based on Biomechanical and Physiological Load, in Elite Basketball

The aim of this study was to understand and describe the physiological and biomechanical demands of various tasks used in basketball training and, subsequently, to provide a practical application of these tasks in a typical training week. Twelve basketball players had their external load variables monitored across 179 training sessions (2896 samples) using local positioning system technology. These variables included total distance covered, distance covered at various intensity levels, accelerations, decelerations, PlayerLoad™, and explosive efforts. The analysis revealed significant differences in both physiological and biomechanical loads across various drills. Specifically, tasks with more space and fewer defenders, such as 3v0 full court, impose higher physiological loads compared to tasks with less space and more defenders, like 5v5 full court. The difference in physiological load between these tasks was statistically significant (p < 0.05) with a moderate effect size (ES: -0.60, 95% CI: [-0.99, -0.22]). In terms of biomechanical load, drills with increased defensive pressure, such as 5v5 full court, exhibited significantly higher values compared to less specific drills, such as 5v0 full court, with a very large effect size (ES: 1.37, 95% CI: [1.04, 1.70], p < 0.01). Additionally, comparisons between 5v5 full court and 3v0 full court for biomechanical load produced a very large effect size (ES: 1.67, 95% CI: [1.37, 1.97], p < 0.01), indicating a substantial difference in load demands. The results indicate that tasks with more space and fewer defenders impose higher physiological loads, while those with less space and more defenders increase the biomechanical load. For training design, it is recommended to schedule tasks with a higher biomechanical load at the beginning of the session and those with a physiological orientation toward the end. Understanding the distinct demands of different drills can help coaches structure training sessions more effectively to optimize player load and performance development throughout the week.

Relationship of Individual Athlete External Load, Session Rating of Perceived Exertion, and Athlete Playing Status Across a Collegiate Women's Basketball Season

External (EL) and internal (IL) load are commonly used methods used to quantify training load in team sports. Playing time and playing position may influence the training loads for specific athletes throughout a season. The purpose of the current study was to evaluate the effect of athlete playing status and individual in-season practices on EL and IL across a collegiate women's basketball season. Female basketball athletes were classified as high-minute (HMA; ≥15 min/game) or low-minute (LMA; <15 min/game) and wore microsensors during 53 practices for a total of 583 data points. EL was obtained via an inertial measurement unit (IMU) device that contained a triaxial accelerometer to obtain three-dimensional positioning data. IL and strength training (ST) load were determined via session rating of perceived exertion (sRPE) to create a daily summated value. Descriptive statistics indicate that athletes experienced individual differences in EL, ST, and IL throughout the season. A growth model showed that HMAs experienced higher EL than LMAs at the start of the season for practices (90.21 AU). Across all athletes, IL increased across the season (40.11 AU) and for each 1 unit of change in EL, IL increased by 1.04 AU. Repeated measures correlations identified a large relationship between IL and EL (r = 0.51, p < 0.001). A location-scale model indicated that the within-person variability of IL across all athletes was 3.29 AU but was not due to athlete playing status. It is recommended to base in-season training on individual loads and game demands to promote athlete readiness and improved sport performance.

Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review

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.

Quarterly fluctuations in external and internal loads among professional basketball players

Purpose

This study aims to explore the variations in external and internal loads on a quarter-by-quarter basis among professional Chinese basketball players. It emphasizes the crucial impact of these variations on optimizing athletic performance and match strategies.

Method

An observational longitudinal study design was employed, involving sixteen male players from the National Basketball League during the 2024 season in China. Data collection was facilitated through the use of Catapult S7 devices for measuring external loads and session ratings of perceived exertion (sRPE) for assessing internal loads. Linear mixed-effects models were utilized for the statistical analysis to identify differences in workload intensities across game quarters based on player positions. The Pearson correlation coefficient was used to examine the relationship between external and internal load throughout the game.

Results

The analysis uncovered significant positional differences in workload intensities across game quarters. Guards were found to have a higher PlayerLoad™ (PL) per minute in the first quarter, while centers demonstrated an increase in high-intensity accelerations and jumps in the fourth quarter. Furthermore, a significant moderate correlation between sRPE and PL was observed across all game quarters, indicating a link between physical exertion and athletes' perceptions of effort.

Conclusion

The study offers new insights into the dynamic physical demands faced by basketball players and the importance of using both objective and subjective measures for a comprehensive assessment of athlete performance and wellbeing. The findings underscore the interconnectedness of physical exertion and athlete perception, providing a foundation for future research and practical applications in the field of basketball science.

Effect of Level of Competition and Drill Typology on Internal and External Load in Male Volleyball Players During the Preseason Period

PURPOSE

This study aimed at evaluating the effect of level of competition and drill typology on loads during the preseason period in male volleyball players.

METHODS

Internal (percentage of peak heart rate [HR] and summated HR zone) and external (PlayerLoad per minute, total and high accelerations per minute [tACCmin and hACCmin], decelerations per minute [tDECmin and hDECmin], and jumps per minute [tJUMPmin and hJUMPmin]) loads were monitored across a 5-week preseason period in 12 Division 1 (age: 22.5 [3.9] y; stature: 188 [6.2] cm; body mass: 85 [11.6] kg; training experience: 9.4 [4.2] y) and 12 Division 2 (age: 20.7 [2.9] y; stature: 186 [6.2] cm; body mass: 77.8 [9.6] kg; training experience: 5.6 [2.3] y) male volleyball players. Furthermore, differences in load were assessed for each drill typology (warm-up, conditioning, technical, tactical, and integral).

RESULTS

No effects (P > .05) of level of competition on the internal (except for summated HR zone, P = .05) and external loads (except for tJUMPmin, P = .002) were found. Differently, drill typologies showed an effect (P < .001) on all the investigated internal- and external-load measures. The main post hoc results revealed higher (P < .05) percentage of peak HR, summated HR zone, PlayerLoad per minute, and tACCmin in warm-up and conditioning drills, while higher (P < .05) hDECmin and hJUMPmin were found in tactical and integral drills.

CONCLUSIONS

These results suggest that volleyball coaches use warm-up and conditioning drills when aiming at increasing the internal loads, PlayerLoad per minute, and tACCmin, while tactical and integral drills should be preferred to enhance the number of hDECmin and hJUMPmin.

Examining the Effects of Altitude on Workload Demands in Professional Basketball Players during the Preseason Phase

Basketball involves frequent high-intensity movements requiring optimal aerobic power. Altitude training can enhance physiological adaptations, but research examining its effects in basketball is limited. This study aimed to characterize the internal/external workload of professional basketball players during preseason and evaluate the effects of altitude and playing position. Twelve top-tier professional male basketball players (Liga Endesa, ACB; guards: n = 3, forwards: n = 5, and centers: n = 4) participated in a crossover study design composed of two training camps with nine sessions over 6 days under two different conditions: high altitude (2320 m) and sea level (10 m). Internal loads (heart rate, %HRMAX) and external loads (total distances covered across speed thresholds, accelerations/decelerations, impacts, and jumps) were quantified via wearable tracking and heart rate telemetry. Repeated-measures MANOVA tested the altitude x playing position effects. Altitude increased the total distance (+10%), lower-speed running distances (+10-39%), accelerations/decelerations (+25-30%), average heart rate (+6%), time in higher-intensity HR zones (+23-63%), and jumps (+13%) across all positions (p < 0.05). Positional differences existed, with guards accruing more high-speed running and centers exhibiting greater cardiovascular demands (p < 0.05). In conclusion, a 6-day altitude block effectively overloads training, providing a stimulus to enhance fitness capacities when structured appropriately. Monitoring workloads and individualizing training by playing position are important when implementing altitude training, given the varied responses.

Individualizing Basketball-Specific Interval Training Using Anaerobic Speed Reserve: Effects on Physiological and Hormonal Adaptations

PURPOSE

We compared the adaptive responses to supramaximal high-intensity interval training (HIIT) individualized according to anaerobic speed reserve (ASR), the 30-15 Intermittent Fitness Test (VIFT), and velocity associated with maximum oxygen uptake (MAS) to determine which approach facilitates more identical adaptations across athletes with different profiles.

METHODS

Thirty national-level basketball players (age = 28.4 [5] y; body mass = 88.9 [6.3] kg; height = 190 [4.8] cm) were randomly assigned to 3 training groups performing 2 sets of 4, 6, 8, 6, 8, and 10-minute runs (from first to sixth week, respectively), consisting of 15-second running at Δ%20ASR (MAS + 0.2 × ASR), 95%VIFT, and 120%MAS, with 15 seconds recovery between efforts and a 3-minute relief between sets.

RESULTS

All 3 interval interventions significantly (P < .05) enhanced maximum oxygen uptake (V˙O2max), oxygen pulse (V˙O2/HR), first and second ventilatory threshold (VT1 and VT2), cardiac output (Q˙max), stroke volume, peak and average power output, testosterone levels, and testosterone-to-cortisol ratio following the training period. Different values of interindividual variability (coefficient of variation) for the percentage changes of the measured variables were observed in response to HIITASR, HIITvIFT, and HIITMAS for V˙O2max (8.7%, 18.8%, 34.6%, respectively), V˙O2/HR (9.5%, 15.0%, 28.6%), VT1 (9.6%, 19.6%, 34.6%), VT2 (21.8%, 32.4%, 56.7%), Q˙max (8.2%, 16.9%, 28.8%), stroke volume (7.9%, 15.2%, 23.5%), peak power output (20%, 22%, 37.3%), average power output (21.1%, 21.3%, 32.5%), testosterone (52.9%, 61.6%, 59.9%), and testosterone-to-cortisol ratio (55.1%, 59.5%, 57.8%).

CONCLUSIONS

Supramaximal HIIT performed at Δ%20ASR resulted in more uniform physiological adaptations than HIIT interventions prescribed using VIFT or MAS. Although hormonal changes do not follow this approach, all the approaches induced an anabolic effect.

Analysis of In-Season External Load and Sport Performance in Women's Collegiate Basketball

ABSTRACT

Brown, FSA, Fields, JB, Jagim, AR, Baker, RE, and Jones, MT. Analysis of in-season external load and sport performance in women's collegiate basketball. J Strength Cond Res 38(2): 318-324, 2024-Quantifying and monitoring athlete workload throughout a competitive season is a means to manage player readiness. Therefore, the purpose of the current study was to quantify practice and game external loads and to assess the relationship between such loads and basketball-specific performance metrics across a women's collegiate basketball season. Thirteen National Collegiate Athletic Association Division I women basketball athletes (age 20.08 ± 1.55 years) wore Global Positioning Systems sensors equipped with triaxial accelerometers for 29 games and 66 practices during the 2019-20 season. A multivariate analysis of variance was used to assess differences in external load between high- and low-minute players and across quarters within games ( p < 0.05). Bivariate Pearson correlation coefficients were run to determine relationships between external loads and metrics of basketball performance. Findings indicated that high- and low-minute athletes experienced different loads during games and practices ( p < 0.001). External loads differed by quarter, such that player load (PL) was highest in Q4 ( p = 0.007), PL·min -1 was highest in Q1 and lowest in Q4 ( p < 0.001), and explosive ratio (i.e., ratio of PL and explosive efforts) was lowest in Q3 ( p = 0.45). Relationships existed between PL·min -1 and field goals ( r = 0.41; p = 0.02) and between the explosive ratio and free throws ( r = 0.377 p = 0.04). These results can be used to inform design of training sessions with the intent to prepare athletes for the demands of the competitive season. It is recommended that future research continue to explore the relationship of sport-specific performance metrics and athlete external load.

Weekly Fluctuations in, and Associations Between, Salivary Hormone Responses, Load, and Well-Being During the Pre-season in Professional Male Basketball Players

ABSTRACT

Kamarauskas, P, Scanlan, A, Ferioli, D, and Conte, D. Weekly fluctuations in, and associations between, salivary hormone responses, load, and well-being during the pre-season in professional male basketball players. J Strength Cond Res 38(1): 128-135, 2024-This study aimed to (a) quantify weekly fluctuations in hormonal responses (testosterone [T], cortisol [C], and their ratio [T:C]), external (PlayerLoad [PL] and PL·minute-1) and internal (session rating of perceived exertion load [sRPE-load], summated heart rate zones [SHRZs], and percentage of maximal heart rate [%HRmax]) load measures, and well-being measured using a self-reported questionnaire and (b) determine the associations between weekly changes in hormonal responses and load measures with weekly changes in well-being during the pre-season phase in basketball players. Twenty-one professional male basketball players (age: 26.2 ± 4.9 years) were monitored during a 5-week pre-season phase. Linear mixed models were used to determine weekly differences in each variable and associations between weekly changes in hormonal and load variables with weekly changes in well-being. Findings revealed that T (p < 0.001) and T:C (p = 0.002) increased toward the end of the pre-season phase. Moreover, higher (p < 0.05) external (PL·minute-1) and internal (%HRmax) load intensities were evident during the first 3 weeks of the pre-season, with no significant fluctuations in other load variables. Weekly changes in PL and sRPE-load were negatively associated (p < 0.05) with weekly changes in well-being, albeit weak in magnitudes (R2 = 0.061-0.105). These results highlight that a periodized approach was undertaken across the pre-season predominantly predicated on altering weekly load intensities, which coincided with positive hormonal responses toward the end of the pre-season. In addition, weak relationships were evident between weekly changes in hormonal responses and load measures with well-being, emphasizing that a low commonality may be present between these constructs.

Investigating the effects of athlete-reported pre-training well-being and recovery on subsequent training loads in basketball players

BACKGROUND

Basketball players' external and internal training loads have been extensively monitored. However, no study has evaluated if pre-training athlete-reported conditions influence them. Therefore, this study investigated the effects of athlete-reported pre-training well-being and recovery on subsequent external load intensity, perceived exertion scores and their ratio (efficiency index) in youth basketball training.

METHODS

The external load (EL) intensity (EL∙min-1), ratings of perceived exertion (RPE) and efficiency index (EL∙min-1:RPE) of 15 youth basketball players (age: 15.2±0.3 years) were monitored during team-based training sessions. Before each session, players reported their levels of perceived recovery (using a modified 10-point Total Quality Recovery, TQR, scale), fatigue, sleep quality, muscle soreness, mood, and stress. Statistical analyses were performed via linear mixed models.

RESULTS

EL∙min-1 was higher when player reported better pre-training recovery (P= 0.001). Higher RPE scores and lower efficiency indexes were registered in players reporting better pre-training conditions, respectively. Specifically, RPE scores were higher when players reported better TQR, fatigue, muscle soreness and stress scores (all P<0.05), while training efficiency was, conversely, lower in correspondence of better TQR and sleep (all P<0.05).

CONCLUSIONS

This study identified influences of athlete-reported pre-training well-being and recovery on subsequent external intensity, RPE and efficiency index in youth basketball players. Recovery and well-being indicators could be monitored seen their influence on subsequent training loads. Current findings can be considered by basketball sport scientist when selecting athlete monitoring questionnaires and when interpreting training load outputs.

An Investigation of Surface EMG Shorts-Derived Training Load during Treadmill Running

The purpose of this study was two-fold: (1) to determine the sensitivity of the sEMG shorts-derived training load (sEMG-TL) during different running speeds; and (2) to investigate the relationship between the oxygen consumption, heart rate (HR), rating of perceived exertion (RPE), accelerometry-based PlayerLoadTM (PL), and sEMG-TL during a running maximum oxygen uptake (V˙O2max) test. The study investigated ten healthy participants. On day one, participants performed a three-speed treadmill test at 8, 10, and 12 km·h-1 for 2 min at each speed. On day two, participants performed a V˙O2max test. Analysis of variance found significant differences in sEMG-TL at all three speeds (p < 0.05). A significantly weak positive relationship between sEMG-TL and %V˙O2max (r = 0.31, p < 0.05) was established, while significantly strong relationships for 8 out of 10 participants at the individual level (r = 0.72-0.97, p < 0.05) were found. Meanwhile, the accelerometry PL was not significantly related to %V˙O2max (p > 0.05) and only demonstrated significant correlations in 3 out of 10 participants at the individual level. Therefore, the sEMG shorts-derived training load was sensitive in detecting a work rate difference of at least 2 km·h-1. sEMG-TL may be an acceptable metric for the measurement of internal loads and could potentially be used as a surrogate for oxygen consumption.

Construct Validity and Applicability of a Team-Sport-Specific Change of Direction Test

Cuts and changes of direction (COD) are frequent movements during games in team sports. Since those movements are seen as a key performance variable, COD assessments are included in performance diagnostics. However, some tests are criticized as they seem to be confounded by variables such as linear sprinting. Therefore, it is suggested that not only total COD time should be assessed, but also the athletes' COD movements should be examined more closely. For example, split times could be analyzed in tests with more than one COD like the Team-Sport-Specific COD (TSS-COD) test. We aimed to investigate the construct validity of the TSS-COD test, focusing on the homogeneity of the different test parts. We also tested how far sprint performance mapped onto COD performance. Test data were analyzed from 154 elite male and female volleyball and basketball athletes. A Fitlight© System was used to assess duration of the TSS-COD test. For the sprint tests, magnetic gates (Humotion GmbH) were used to measure sprint time. Explorative principal component analysis (PCA) was conducted including the test interval duration and the athletes' 5, 10, and 20 m sprint performance, to test the validity of the TSS-COD test. PCA results showed that the start interval formed a factor separate from the other COD sub-intervals. In addition, sprint performance was separated from all COD interval measures. The findings of the PCA were confirmed by split-half validation. Since sprint and COD performance represent independent performance domains within this analysis, we suggest the TSS-COD test to be a valid test to assess COD performance.

STRENGTH AND QUALITY TRAINING OF BASKETBALL PLAYERS

ABSTRACT Introduction: Quality exercise training of young people is a fundamental basic requirement for developing physical fitness in college basketball teaching. Objective: Enhance exercise training in young basketball players. Methods: A random selection of 50 student volunteers was made for this research. The strength and quality of basketball players of different ages were analyzed. The experimental group was subjected to specific strength training, while the control group was subjected to routine physical exercises. The experiment period was 12 weeks, and the specific technical indicators of the athletes were collected before and after the end of the experiment. The collected data were statistically treated and discussed in light of the scientific literature. Results: No significant difference was found between the two groups in the initial test score (P>0.05). The experimental group’s performance in exercise was better than the control group after 12 weeks (P<0.01). The experimental group demonstrated better performance than the control group in the standing jump, 15-meter reentry, and forward jump, corroborating the significantly different data between the two groups (P<0.01). Conclusion: This study aimed to study the unique role of strength training in the physical training of young basketball players. Special strength training positively affects upper limb muscle training in young basketball players. The lower extremities of basketball players showed expressive functional gains with special strength training. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

POSITIVE CORRELATION MODEL IN BASKETBALL ON ATHLETES’ PHYSICAL TRAINING

ABSTRACT Introduction The athletic capacity improvement in basketball players is closely connected with their training. It is believed that the focus on training by basketball players can contribute to the gain of strength, speed, agility, and endurance. Objective Analyze the specific methods in the players’ training scoring the critical factors for improving physical conditioning. Methods Correlation statistics were used to analyze the factors that affected the physical performance of basketball players. Periodic physical training programs were designed by relating training load to the competition schedule to evaluate the essential parameters (strength, speed, explosive strength, cardiorespiratory endurance, coordination, flexibility, agility, and accuracy) and the changes in physical fitness. Results Basketball players’ strength, agility, endurance, and speed improved after physical training. There are considerable differences in several fitness indices before and after training (P<0.05). Conclusion Periodic physical training of basketball players can improve their physical fitness. Physical training is an essential tool to improve basketball in China. Evidence Level II; Therapeutic Studies - Investigating the result.

Effect of Situational and Individual Factors on Training Load and Game Performance in Liga Femenina 2 Basketball Female Players

There is research that has shown how individual characteristics and performance indicators influence the load in basketball; however, studies on the influence of situational variables on performance are lacking. The aim of this study was to determine the influence of certain situational and individual variables on the training load (weekly load, game load and pre-game recovery) and the individual performance (statistical game evaluation) of female basketball players of Liga Femenina 2 during competition. The 28 games played by the 13 players of a group B team of the Liga Femenina 2 of the Spanish Basketball Federation (FEB) during the 2020/2021 season were analyzed. Data on rate of perceived exertion (RPE), perceived performance and recovery were collected through the Quanter mobile application as well as performance statistics from the FEB website. Five mixed linear analyses for repeated measures were performed to evaluate the effect of each situational and individual variable on each dependent variable (weekly load, game load, game RPE, pre-game recovery, and game statistical assessment). The results show how the weekly load increases after playing against a low-level opponent (p < 0.001). In games, the players who play the most minutes and accumulate the most load are also the most valued (p < 0.001). The pre-game recovery worsens as the season progresses (p < 0.001). After playing against a high-level opponent, the pre-game recovery values for the next game are lower (p = 0.031). The results obtained indicate that the situational and individual variables should be taken into account to monitor the workload. These results help coaches and physical trainers to better plan training weeks, taking into account the situational variables studied.

Techniques to derive and clean acceleration and deceleration data of athlete tracking technologies in team sports: A scoping review

The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.

HIGH-INTENSITY PHYSICAL ABILITY TRAINING OF TEENAGER BASKETBALL PLAYERS

ABSTRACT Introduction: The antagonism of basketball is very prominent during the game. Athletes with good physical fitness will have great advantages in basketball games. Objective: To study the influence of physical exercise on the physical fitness of young athletes. Methods: This article uses mathematical statistics to investigate and analyze the physical training status of young basketball players. Results: After studying various training methods, we found that impedance training can improve the physical fitness of young athletes. Basketball physical training includes strength, speed, endurance, sensitivity, etc. Conclusion: Young basketball players need to adopt a variety of training methods. Group sports can effectively improve the physical fitness of young basketball players and increase the winning probability of the team in the game. Level of evidence II; Therapeutic studies - investigation of treatment results.

Assessing the Relationship Between External and Internal Match Loads in Elite Women's Rugby Sevens

PURPOSE

To assess the relationship between external and internal load during official women's rugby seven matches.

METHODS

Six backs (age = 24.2 [3.2] y; height = 161.5 [7.3] cm; body mass = 59.5 [5.0] kg; playing experience = 5.3 [1.5] y) and 8 forwards (age = 22.4 [2.7] y; height = 167.0 [4.8] cm; body mass = 70.6 [5.6] kg; playing experience = 5.0 [1.5] y) belonging to the women's rugby seven Brazilian national team were monitored across 3 international tournaments during the 2019-20 season, with 2 players excluded from the analysis since they did not participate in any investigated match. Total distance (TD), distance during high-intensity running 18.1 to 20.0 km·h-1 and >20 km·h-1 (sprinting), number of accelerations >1.8 m·s-2 (ACC), and of decelerations <1.8 m·s-2 were used as match load volume measures, while their relative values (TD per minute, high-intensity running per minute, sprinting per minute, ACC per minute, and decelerations per minute) were used as external load match intensity measures. Internal load intensity and volume were assessed using the session rating of perceived exertion (sRPE) and its value multiplied by match duration (sRPE-ML), respectively. Spearman correlations and linear mixed models were used to assess the relationships between internal and external load measures.

RESULTS

A very large relationship (ρ = .830, P < .001) was found between sRPE-ML and TD, with linear mixed models showing that TD statistically affected sRPE-ML (P < .001). Linear mixed models analysis showed that ACC per minute was also affecting the sRPE-ML (P = .017), while sprinting (P = .007) and ACC per minute (P = .005) were the only 2 measures statistically affecting sRPE. However, weak relationships (trivial to large) were found for these and all other measures.

CONCLUSIONS

These results highlight that TD is the main external load measure able to anticipate the internal load responses measured via sRPE-ML in elite women's rugby sevens.

Posture Monitoring of Basketball Training Based on Intelligent Wearable Device

The relevant content of China's sport work clearly pointed out that it is necessary to improve the physical and mental health of the citizens. Combining the current development hotspots of mobile smart terminals and smart wearable devices, smart wearable devices are analyzed from the function and development history in order to find an effective combination of smart wearable devices and sports work. This article describes the youth as the main body receiving grassroots physical education of nonsports special students and basketball enthusiasts. In the process of physical education teaching, the problem of pain points is more prominent because most teenagers in the basketball education at the grass-roots level do not have the opportunity to get one-to-one private counseling. When there are problems in the operation, students cannot be guided to conduct training or practice by themselves. This paper aims to meet the demand of real-time monitoring of dribbling posture in basketball dribbling training and proposes a low-cost product solution to help teenagers carry out basketball dribbling training by themselves: intelligent wearable product of head wrist and dribbling assistant DribbleAid, which is used to monitor common bad posture problems of users in dribbling training and give corresponding reminders to deal with users' pain points. In this work, various experiments have been carried out for the proposed method and system. A large number of experimental results show that the method designed in this paper can effectively monitor the basketball training posture.

A Comparison of the External and Internal Demands Imposed during Conditioning Training and Match-Play in Semi-Professional and Development Female Netball Players

This case series, team-based study aimed to compare the demands imposed during conditioning training and match-play in netball players. Female netball players competing at semi-professional (n = 9, age: 22.2 ± 3.8 years) and development (n = 9, age: 22.3 ± 2.9 years) levels had their internal (rating of perceived exertion (RPE)) and external (relative PlayerLoad (PL) in total and in the forwards, sideways, and vertical vectors) loads measured during conditioning-based training sessions and matches in a season. Demand variables were compared between conditioning and match-play across all players and according to position in each playing level. Conditioning training imposed higher relative PL in total and in each vector compared to match-play in semi-professional and development players (small to large effects). In contrast, RPE was significantly (p = 0.006) higher during match-play than conditioning training in semi-professional and development players (medium effects). Furthermore, according to playing position, significantly higher relative PL variables were evident during conditioning training than match-play in wing attack and goalkeeper semi-professional players and in goal attack, goal shooter, goal keeper, and goal defence development players. These results suggest conditioning training practices elicit adequate external intensities but inadequate internal intensities relative to match-play across positions in semi-professional and development netball players.

Weekly Fluctuations in Salivary Hormone Responses and Their Relationships With Load and Well-Being in Semiprofessional, Male Basketball Players During a Congested In-Season Phase

PURPOSE

To assess weekly fluctuations in hormonal responses and their relationships with load and well-being during a congested in-season phase in basketball players.

METHODS

Ten semiprofessional, male basketball players were monitored during 4 congested in-season phase weeks consisting of 3 weekly matches. Salivary hormone variables (testosterone [T], cortisol [C], and T:C ratio) were measured weekly, and external load (PlayerLoad™ and PlayerLoad per minute), internal load session rating of perceived exertion, percentage of maximum heart rate (HR), summated HR zones, and well-being were assessed for each training session and match.

RESULTS

Significant (P < .05) moderate to large decreases in T were found in the third and fourth weeks compared with the first week. Nonsignificant moderate to large decreases in C were apparent in the last 2 weeks compared with previous weeks. Summated HR zones and perceived sleep significantly (P < .05) decreased in the fourth week compared with the first week; whereas, percentage of maximum HR significantly (P < .05) decreased in the fourth week compared with the second week. No significant relationships were found between weekly changes in hormonal responses and weekly changes in load and overall wellness.

CONCLUSIONS

A congested schedule during the in-season negatively impacted the hormonal responses of players, suggesting that T and C measurements may be useful to detect fluctuations in hormone balance in such scenarios. The nonsignificant relationships between weekly changes in hormonal responses and changes in load and well-being indicate that other factors might induce hormonal changes across congested periods in basketball players.

Relationship Between External and Internal Load Measures in Youth Beach Handball

PURPOSE

Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players.

METHODS

A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoad™, accelerations, decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (ρ) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad™ as the independent variable, and players as random effect.

RESULTS

The lowest significant (P < .05) relationship was for high jumps with objective (ρ = .56) and subjective (ρ = .49) IL. The strongest relationship was for PlayerLoad™ with objective (ρ = .9) and subjective (ρ = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75-33.31); SE = 5.26, and R2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00-7330.6); SE = 21.87; and R2 = .71 for the subjective IL.

CONCLUSIONS

Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.

External, Internal, Perceived Training Loads and Their Relationships in Youth Basketball Players Across Different Positions

PURPOSE

To quantify external, internal, and perceived training loads and their relationships in youth basketball players across different playing positions.

METHODS

Fourteen regional-level youth male players (age: 15.2 [0.3] y) were monitored during team-based training sessions across 10 in-season weeks. The players were monitored with BioHarness-3 devices, to measure external (Impulse Load, in Newtons per second) and internal (summated-heart-rate zones [SHRZ], in arbitrary units [AU]) loads, and with the session rating of perceived exertion (sRPE, in AU) method to quantify perceived training load. Multiple linear mixed models were performed to compare training loads between playing positions (backcourt and frontcourt). Repeated-measures correlations were performed to assess the relationships between the load models, for all players and within playing positions.

RESULTS

External load (backcourt: 13,599 [2260] N·s; frontcourt: 14,934 [2173] N·s) and sRPE (backcourt: 345 [132] AU; frontcourt: 505 [158] AU) were higher in the frontcourt (P < .05, effect size: moderate), while SHRZ was similar between positions (backcourt: 239 [45] AU; frontcourt: 247 [43] AU) (P > .05; effect size: trivial). The correlations were as follows: large between the external load and SHRZ (r = .57, P < .001), moderate between SHRZ and sRPE (r = .45, P < .001), and small between the external load and sRPE (r = .26, P = .02). The correlation magnitudes were equivalent for external load-SHRZ (large) and SHRZ-sRPE (moderate) across positions, but different for the external load-sRPE correlation (small in backcourt; moderate in frontcourt).

CONCLUSIONS

In youth basketball, small-large commonalities were found between the training dose (external load) and players' responses (internal and perceived loads). Practitioners should carefully manage frontcourt players' training loads because they accumulate greater external and perceived loads than backcourt  players do.

Using Metabolomics to Differentiate Player Positions in Elite Male Basketball Games: A Pilot Study

Purpose: The current study compared metabolic profiles and movement patterns between different player positions and explored relationships between indicators of internal and external loads during elite male basketball games.

Methods: Five main players from 14 basketball teams (n = 70) were selected as subjects and defined as backcourt (positions 1–3) or frontcourt (positions 4–5) players. Video-based time motion analysis (VBTMA) was performed based on players’ individual maximal speeds. Movements were classified into high and low intensity running with and without ball, high and low intensity shuffling, static effort and jumps. Saliva samples were collected before and after 40-min basketball games with metabolomics data being analyzed by multivariate statistics. Independent t-tests were used to compare VBTMA.

Results: Frequency, duration, and distance of high and low intensity running and -shuffling were higher in backcourt players, whereas static effort duration and frequency as well as jump frequency were higher in frontcourt players (all p ≤ 0.05). The levels of taurine, succinic acid, citric acid, pyruvate, glycerol, acetoacetic acid, acetone, and hypoxanthine were higher in backcourt players, while lactate, alanine, 3-methylhistidine were higher and methionine was lower in frontcourt players (all p < 0.05). High intensity running with ball was significantly associated by acetylecholine, hopoxanthine, histidine, lactic acid and leucine in backcourt players (p < 0.05).

Conclusion: We demonstrate different metabolic profiles of backcourt and frontcourt players during elite male basketball games; while aerobic metabolic changes are more present in backcourt players, frontcourt players showed lager changes in anaerobic metabolic pathways due to more static movements.