Monitoring Training Loads in Professional Basketball Players Engaged in a Periodized Training Program

Recovery in elite youth basketball players: The responsiveness of the psychophysiological measurements and the role of testosterone concentration

This study investigated the recovery responses to the Total Quality Recovery (TQR), Well-Being questionnaire (WBQ), and Heart Rate (HR) responses to Submaximal Running Test (SRT), and the influence of salivary testosterone concentration (TEST) on these responses in 25 elite youth (U15) male basketball players. TQR, WBQ, and HR measurements were assessed after 48 hours of rest (T1), 24 hours after the 1st day of training (T2) and 24 hours after the 2nd day of training (T3). Salivary sampling was conducted at T1 and T3. A significant decrease was observed for TQR (F = 4.06; p = 0.01) and for WBQ (F = 5.37; p = 0.008) from T1 to T3. No difference among the three-time points was observed for HR and HR Recovery, and the TEST concentration did not influence the results. These results show that TQR and WBQ are sensitive to acute transient alterations in training loads (TL) and may be utilized to monitor recovery in elite youth basketball players. The HR related measurements presented limited responsiveness, and the TEST seems not to influence the recovery of these players who are competing at highest performance level.

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.

Athlete External Load Measures Across a Competitive Season in High School Basketball

ABSTRACT

Askow, AT, Jennings, W, Jagim, AR, Fields, JB, Beaudoin, RG, Sanchez, GM, Weeks, JE, Oliver, JM, and Jones, MT. Athlete external load measures across a competitive season in high school basketball. J Strength Cond Res 37(11): 2206-2212, 2023-The purpose of this retrospective analysis was to quantify in-season external load and to determine if relationships existed between load metrics and basketball performance. Eleven male high school varsity basketball athletes (n = 11; mass 80.5 ± 9.6 kg, height 190.2 ± 9.4 cm, age 17.6 ± 0.7 years) were monitored across a season. PlayerLoad (PL), PL per minute (PL·min -1 ), total jumps, and explosive movements (EMs) were quantified using a commercially available local positioning unit. Basketball-specific performance metrics, including points scored, points allowed, point differentials, and shooting percentages for each quarter and game, were compiled. Data were analyzed using repeated-measure analysis of variance to evaluate differences in load by starting status, session type, game outcome, and game type. Pearson's correlation coefficients were used to assess relationships between load metrics and basketball performance. Statistical significance was set at p < 0.05. The mean values across 23 games for PL, PL·min -1 , total jumps, and EMs were 457 ± 104 AU, 10.9 ± 1.6 AU, 42.6 ± 9.6, and 46.7 ± 7.2, respectively. Relationships were observed ( p < 0.05) between PL and points scored ( r = 0.38) and free throw percentage ( r = 0.21). Further relationships were observed between PL·min -1 and free throw shooting percentage ( r = -0.27), and between points scored and total jumps ( r = 0.28), and EMs ( r = 0.26). Notable differences in game demands were observed for playing status. Meaningful differences in measures of external load were observed between each quarter of play, with the highest measures evident in quarters 1 and 3. Guards and forwards experienced minimal differences in external load during gameplay, and game outcome did not result in differences. Higher point totals corresponded with higher PL, total jumps, and EM.

Analysis of the External and Internal Load in Professional Basketball Players

The quantification of the external load and internal load of professional players is of vital importance since it provides a great deal of information on the state of the physical condition of athletes during competition and training. The aim of the present study was to quantify the external load and internal load of the players of a first level team of the Spanish basketball league for two weeks corresponding to the pre-season 2022/2023. Seventeen load variables were analyzed and organized into kinematics external load, neuromuscular external load, and internal load. All variables were normalized to the same time unit (minute). For this purpose, all training sessions were monitored using inertial devices. The results show significant differences in the external load and internal load variables depending on the task performed and the specific position. Each type of task provokes different responses in the players, with Full Game situations producing the highest values in the kinematic external load variables (p < 0.05). The selection of each type of task must be adjusted to the physical and technical-tactical objective to be developed. Despite the general work carried out in the pre-season, the centers are the players who bear the greatest internal load in this period. For this reason, it is necessary to individualize the training processes from the pre-season.

Changes in countermovement jump force-time characteristic in elite male basketball players: A season-long analyses

Basketball is a sport that is characterized by various physical performance parameters and motor abilities such as speed, strength, and endurance, which are all underpinned by an athlete's efficient use of the stretch-shortening cycle (SSC). A common assessment to measure SSC efficiency is the countermovement jump (CMJ). When performed on a force plate, a plethora of different force-time metrics may be gleaned from the jump task, reflecting neuromuscular performance characteristics. The aim of this study was to investigate how different CMJ force-time characteristics change across different parts of the athletic year, within a sample of elite collegiate male basketball players. Twelve basketball players performed CMJ's on near-weekly basis, combining for a total of 219 screenings. The span of testing was broken down into four periods: pre-season, non-conference competitive period, conference competitive period, and post-season competitive period. Results suggest that basketball players were able to experience improvements and maintenance of performance with regards to various force-time metrics, transitioning from the pre-season period into respective later phases of the in-season period. A common theme was a significant improvement between the pre-season period and the non-conference period. Various force-time metrics were subject to change, while outcome metrics such as jump height remained unchanged, suggesting that practitioners are encouraged to more closely monitor how different force-time characteristics change over extended periods of time.

Assessing the Relationship Between External Workloads and Noncontact Injuries During Summer Conditioning and Preseason Practice in National Collegiate Athletic Association Division 1 Football Players

ABSTRACT

Burghardt, WP, Pfeiffer, KA, and Kuenze, C. Assessing the relationship between external workloads and noncontact injuries during summer conditioning and preseason practice in National Collegiate Athletic Association Division 1 football players. J Strength Cond Res 37(4): 816-822, 2023-The purpose of this study was to prospectively investigate the relationship between noncontact injuries and workload in collegiate football during summer conditioning and preseason training. Workload and noncontact injury data were collected over the summer conditioning and preseason practice periods for a Division 1 National Collegiate Athletic Association football team ( n = 34). Seven- and 21-day exponentially weighted moving averages (EWMA) were calculated daily for each athlete. The acute:chronic ratio (A:C ratio) of these 2 measures was also calculated daily. Injury rates for noncontact injuries were calculated for both periods. Continuous variable modeling (panel logistic regression and restricted cubic spline) was used to assess the relationship of EWMA A:C ratio and noncontact injury using a 3-day lag period. Athletic exposures (AEs) were defined as individual sport training, practice, or competition sessions. Nine injuries were observed (6.97/1,000 AEs), with 4 injuries resulting in lost time (3.09/1,000 AEs). The mean EWMA A:C ratio was 0.92 ± 0.41 (95% confidence interval: 0.03-2.09). Both the panel logistic regression and the restricted cubic spline models showed a significant relationship between EWMA A:C ratio and noncontact injuries. However, the odds ratio (14.16) in the logistic regression had a very large standard error (14.51) and a wide 95% confidence interval (1.90-105.49). The restricted cubic spline model had a pseudo R2 of 0.136. Injury occurrence at given EWMA ratio values was lower than reported in previous research. Although both continuous models demonstrated a significant relationship between the EWMA A:C ratio and subsequent noncontact injuries over the next 3 days, neither model had sufficient goodness of fit to warrant adoption at this time.

Intraseason Changes in Vertical Jumps of Male Professional Basketball Players

This study aimed to analyze basketball players' jumping bhavior in the Squat Jump (SJ), Countermovement Jump (CMJ), and Free Arm Swing CMJ (CMJ Free) during a professional basketball season and check if it is modulated by the players' specific playing position, the time played on court, and the different leagues. Fifty-three male professional basketball players were assessed in three different moments of the season through SJ, CMJ, and CMJ Free. Between the beginning of pre-season (1st assessment) and the second round of the season (3rd assessment), there was a strong increase in performance in the three jumps (SJ Height: 5.6%, η²_P = 0.234, p = 0.007; CMJ Height: 5.1%, η²_P = 0.177, p = 0.007; CMJ Free height: 4.11%, η²_P = 0.142, p = 0.01). There was also a significantly large increase in SJ and CMJ between the 2nd and 3rd assessments and in the CMJ Free between the 1st and 2nd assessments. No significant interactions were found between jumping performance and the group factors (players' specific playing position, time played on court, and league). In conclusion, SJ, CMJ, and CMJ Free performance strongly increases between 1st and 3rd assessment, without being influenced by the specific playing position or the minutes played per game.

Longitudinal monitoring of workloads in women's division I (DI) collegiate basketball across four training periods

Women's collegiate basketball is a fast-growing, dynamic sport that spans 8 or more months, with athletes competing in 30 + games in a season. The aim of this study was to quantify and profile the external load of practices and games during a Power-5 DI Women's Collegiate Basketball season. Specifically, Average PlayerLoad (PL), PlayerLoad per minute (PL*min^-1), High Inertial Movement Analysis (High-IMA), and Jumps were quantified using Catapult Openfield software during four distinct training periods of the year: 8-hour preseason, 20-hour preseason, non-conference, and conference game play. Weekly variations and acute to chronic workload ratios (ACWR) were also examined. Eleven subjects participated in daily external load monitoring during practice and games via Catapult's ClearSky T6 inertial measurement units (IMU). Averages, standard deviations, and confidence intervals were calculated for training period comparisons, and Cohen's d was calculated as a measure of effect size. Findings include normative values to provide context for the demands experienced across an entire season. PL was significantly higher during non-conference play than during any of the other three training periods (p < 0.05). Descriptive data enumerate percent change and ACRW variations throughout the season. These data can be used to describe the physical demands across a season and provide physical profile guidelines for coaches.

External and Internal Load Variables Encountered During Training and Games in Female Basketball Players According to Playing Level and Playing Position: A Systematic Review

Background

Despite the growing global participation of females in basketball and number of studies conducted on the topic, no research has summarized the external and internal load variables encountered by female basketball players during training and games.

Objective

To collate existing literature investigating external and internal load variables during training and games in female basketball players according to playing level (club, high-school, representative, collegiate, semi-professional, and professional) and playing position (backcourt and frontcourt players).

Methods

A systematic review of the literature was performed using PubMed, SPORTDiscus, and Web of Science to identify studies published from database inception until June 11, 2021. Studies eligible for inclusion were observational and cross-sectional studies, published in English, reporting external and/or internal load variables during training sessions and/or games. Methodological quality and bias were assessed for each study prior to data extraction using a modified Downs and Black checklist. Weighted means according to playing level and playing position were calculated and compared if a load variable was reported across two or more player samples and were consistent regarding key methodological procedures including the seasonal phase monitored, minimum exposure time set for including player data (playing time during games), approach to measure session duration, and approach to measure session intensity.

Results

The search yielded 5513 studies of which 1541 studies were duplicates. A further 3929 studies were excluded based on title and abstract review, with 11 more studies excluded based on full-text review. Consequently, 32 studies were included in our review. Due to the wide array of methodological approaches utilized across studies for examined variables, comparisons could only be made according to playing level for blood lactate concentration during games, revealing backcourt players experienced higher lactate responses than frontcourt players (5.2 ± 1.9 mmol·L−1 vs. 4.4 ± 1.8 mmol·L−1).

Conclusions

Inconsistencies in the methods utilized to measure common load variables across studies limited our ability to report and compare typical external and internal loads during training and games according to playing level and position in female basketball players. It is essential that standardized methodological approaches are established for including player data as well as measuring session duration (e.g., total time, live time) and intensity (e.g., consistent rating of perceived exertion scales, intensity zone cut points) in future female basketball research to permit meaningful interpretation and comparisons of load monitoring data across studies.

Differences in Weekly Training Load, Well-Being, and Hormonal Responses between European- and National-Level Professional Male Basketball Players during the Pre-Season Phase

This study aimed to compare the weekly fluctuation in training load (sRPE-load), well-being (perceived fatigue, stress, mood, sleep, and muscle soreness), and hormonal responses [testosterone (T) and cortisol (C)] during the pre-season phase in European- and national-level professional male basketball players. Twenty-one professional male basketball players belonging to European-level (n = 11, age: 25.5 ± 3.6 yr; stature: 199.2 ± 7.1 cm; body mass: 94.1 ± 8.5 kg) and national-level (n = 10, age: 23.5 ± 4.7 yr; stature: 198.0 ± 5.6 cm; body mass: 94.0 ± 8.8 kg) teams were monitored during a 5-week pre-season phase. The European-level team showed higher sRPE-load in week 5 compared to week 3 (within-team difference, p = 0.049; ES = -1.44 [-2.38, -0.5], large) and week 1 (p = 0.018; ES = 1.62 [0.64, 2.61], large), week 4 (p = 0.005; ES = 1.79 [0.78, 2.81], large) and week 5 (p = 0.001; ES = 1.96 [0.92, 3.01], large) of the national-level team. The national-level team documented the lowest sRPE-load in week 5, which was statistically different compared to week 2 (p = 0.022; ES = 1.59 [0.61, 2.58], large) and week 4 (p = 0.001; ES = 1.94 [0.9, 2.98], large) of the European-level team. Moreover, higher stress (p < 0.001; ES = 1.94 [0.93, 2.95], large) and better mood (p = 0.003; ES = 1.79 [0.8, 2.78], large) were found in week 1 compared to week 5 within the European-level team. Additionally, higher values of salivary C were found in week 1 for the European-level team compared to week 2 (p = 0.020; ES = 1.6 [0.61, 2.58], large) and week 4 (p = 0.018; ES = 1.66 [0.64, 2.67], large) of the national-level team. Our results can provide reference values for basketball practitioners regarding the fluctuations of weekly load, well-being, and hormones across the pre-season period in professional male teams competing at European and national levels.

The Ecological Validity of Countermovement Jump to On-Court Asymmetry in Basketball

Jump-based asymmetry is often used as an indicator of sport performance and may be used to discern injury susceptibility. Due to task specificity, however, countermovement jump asymmetry may not be representative of on-court asymmetry. As such, we assessed the association between countermovement jump asymmetry and on-court impact asymmetry metrics (n=3, and n=4, respectively) using linear regressions (α=0.05). Fifteen female basketball athletes completed countermovement jump and on-court sessions across a competitive season. A significant negative association was found between peak landing force asymmetry and both overall and medium acceleration on-court asymmetry (b=–0.1, R ² =0.08, p<0.001; b=–0.1, R ² =0.11, p<0.001, respectively), as well as between peak propulsive force asymmetry and on-court medium acceleration asymmetry (b=–0.24, R ² =0.04, p=0.01). Alternatively, both peak landing and peak propulsive force asymmetry were significantly positively associated with on-court high acceleration asymmetry (b=0.17, R ² =0.08, p<0.001; b=0.35, R ² =0.02, p=0.04, respectively). While some overlap may exist, countermovement jump and on-court impact asymmetry appear to be independent. Thus, sport-specific monitoring may be necessary to adequately monitor injury susceptibility using asymmetry.

RELACIÓN ENTRE METODOLOGÍAS DE CONTROL DE LA CARGA EN EL BALONCESTO PROFESIONAL

El objetivo de este trabajo fue determinar la relación existente entre diferentes metodologías de medición de la carga de entrenamiento en un equipo profesional de baloncesto. 12 jugadores de un mismo equipo fueron sometidos a estructuras de entrenamiento iguales en cuanto a diseño y fueron monitorizados diariamente con frecuencia cardiaca, GPS y percepción subjetiva de esfuerzo. Los resultados indicaron diferencias significativas entre todas las metodologías de control utilizadas. RPE (x2=12.4; P=.015), sRPE (x2=21.5; P<.001), TRIMP (x2=23.5; P<.001), SHRZ (x2=19.3; P<.001) y distancia (x2=21.7; P<.001). Se observó una correlación entre todas ellas exceptuando la variable distancia recorrida; Borg (p=.19; P=79), sRPE (p=.14; P=.299) y sHR-Z (p=.17; P=.197). Estos resultados sugieren que los diferentes métodos de evaluación utilizados para el control de la carga de entrenamiento determinan resultados variables en un equipo de baloncesto profesional. Se consideró que el ratio de esfuerzo percibido por sesión resulta el instrumento más eficaz para el control de la carga de entrenamiento.

RELACIÓN ENTRE LA CARGA INTERNA Y EXTERNA EN ÁRBITROS DE BALONCESTO

El objetivo del presente trabajo consistió en analizar las relaciones existentes entre los parámetros de carga interna (objetiva y subjetiva) y externa. La muestra estuvo compuesta por un total de 15 partidos disputados en el Eurobasket femenino U-16, donde participaron un total de nueve árbitros (6 masculinos y 3 femeninos). Las variables analizadas de carga interna fueron la frecuencia cardiaca y la percepción subjetiva de esfuerzo. Las variables de carga externa se dividieron en cinemáticas y neuromusculares, medidas a través de dispositivos inerciales. Los resultados explican que existen relaciones entre los valores de carga interna objetiva y carga externa, así como entre las variables de carga externa. En cambio, no existen relaciones entre la carga interna subjetiva y las variables de carga interna y externa objetiva, exceptuando el PowerMetabolic. Estos resultados demuestran que la competición y el nivel de los árbitros influyen en gran medida en las variables subjetivas.

The relationship between external and internal load parameters in 3 × 3 basketball tournaments

Purpose

3 × 3 basketball games are characterized by high-intensity accelerations and decelerations, and a high number of changes of direction and jumps. It is played in tournament form with multiple games per day. Therefore, optimal regeneration is crucial for maintaining a high performance level over the course of the tournament. To elucidate how load of a match affects the athletes' bodies (i.e., internal load), muscular responses to the load of 3 × 3 games were analyzed. We aimed to investigate changes in contractility of the m. rectus femoris (RF) and m. gastrocnemius medialis (GC) in response to the load of single 3 × 3 games and a 3 × 3 tournament.

Methods

Inertial movement analysis was conducted to capture game load in 3 × 3. Changes in contractility were measured using tensiomyography (TMG). During a two-day tournament, TMG measurements were conducted in the morning and after each game. Additionally, off-game performance analysis consisting of jump and change-of-direction (COD) tests was conducted the day before the tournament.

Results

Significant changes of the muscle contractility were found for GC with TMG values being higher in the baseline than in the post-game measurements. In contrast to athletes of the GC group, athletes of the RF group responded with either decreased or increased muscle contractility after a single 3 × 3 game. A significant correlation between external and internal load parameters could not be shown. Concerning off-game performance, significant correlations can be reported for COD test duration, CMJ height and ∆Vc as well as COD test duration and ∆Dm. No systematic changes in muscle contractility were found over the course of the tournament in RF and GC.

Conclusion

The athletes' external 3 × 3 game load and their performance level did not seem to affect muscular contractility after a single 3 × 3 game or a complete 3 × 3 tournament within this investigation. This might indicate that elite athletes can resist external load without relevant local muscular fatigue. With respect to the course of the tournament, it can therefore be concluded that the breaks between games seem to be sufficient to return to the initial level of muscle contractility.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-022-00530-1.

Understanding load in netball – An analysis of multiple seasons, phases, and teams

Studies of training and competition load in sport are usually based on data that represents a sample of a league and or annual training program. These studies sometimes explore important factors that are affected by load, such as training adaptations and injury risk. The generalisability of the conclusions of these studies, can depend on how much load varies between seasons, training phases and teams. The interpretation of previous load studies and the design of future load studies should be influenced by an understanding of how load can vary across seasons, training phases and between teams. The current study compared training loads (session rating of perceived exertion x session duration) between all (8) teams in an elite Netball competition for multiple (2) season phases and (2) seasons. A total of 29,545 records of athlete session training loads were included in the analysis. Linear mixed models identified differences between seasons and training phases (p < .05). There were also differences between teams and a complex set of interactions between these three factors (season, phase, and team) (p < .05). While the absolute value of the training loads reported here are only relevant to elite netball, these results illustrate that when data is sampled from a broader context, the range and variation in load may increase. This highlights the importance of cautiously interpreting and generalisation of findings from load studies that use limited data sets.

Fluctuations in External Peak Demands Across Quarters During Basketball Games

The purpose of this study was to compare external peak demands (PDs) across quarters (Q) in basketball. Thirteen elite, junior, male basketball players were monitored using electronic performance tracking systems. There were studied intervals for different time windows to determine the external PD for distance (m); player load; distance covered in four different zones; accelerations; and decelerations. A mixed linear model was run to identify differences among quarters, and the auto-correlation function was carried out to determine fluctuations across the whole game. The results showed significant differences between Q1 vs. Q2 for distance, player load, and standing–walking distance; between Q1 vs. Q3 for distance, player load, and HSR; between Q1 vs. Q4 for distance, player load, standing–walking, and HSR; and between Q3 vs. Q4 for distance and player load. These findings suggest that external PD for running-based demands (distance, player load, and high-speed running) decrease across basketball games with the most notable declines occurring between the first and fourth quarters. Nevertheless, it is important to note that non-significant differences were found between quarters for several external PD variables (jogging, running, acceleration, and deceleration) across different time windows. Findings from the present study reinforce the importance of considering specific PD variables for different functions due to the specific insight each provides.

Non-Time-Loss and Time-Loss Injuries in Secondary School Girls' Volleyball Athletes: A Report From the National Athletic Treatment, Injury, and Outcomes Network Surveillance Program

CONTEXT

Volleyball is a popular sport with a risk of injury to the entire body. Insight into non-time-loss (NTL) and time-loss (TL) injuries is needed to inform seasonal injury trends that may lead to appropriate prevention and management strategies. This study provides a descriptive analysis of volleyball injuries among secondary school athletes.

STUDY DESIGN

Descriptive epidemiology study.

METHODS

Data were collected from 72 secondary schools, representing 135 team seasons of data from the National Athletic Treatment, Injury, and Outcomes Network Surveillance Program (2014-2015 to 2018-2019 academic years). Injury counts, injury rates (IR) per 1000 athlete exposures (AEs), and incidence rate ratios (IRR) were reported with 95% confidence intervals (CIs).

RESULTS

In total, 529 injuries over 193,858 AEs for girls' volleyball were captured, producing an IR of 2.73/1000AEs (95% CI = 2.50-2.96). The overall IR was highest during the preseason compared with regular season (IRR = 1.31, 95% CI = 1.09-1.59). Overall IRs were higher in competition (IR: 3.56, 95% CI = 3.07-4.05) compared with practice (IR: 2.38, 95% CI = 2.12-2.64; IRR = 1.49, 95% CI = 1.25-1.79). Common body locations injured were ankle (n = 141, 26.7%; NTL: n = 56, 21.7%; TL: n = 85, 31.7%), knee (n = 61, 11.5%; NTL: n = 33, 12.8%, TL: n = 28, 10.5%), hand/wrist (n = 59, 11.2%; NTL: n = 32, 12.4%, TL: n = 27, 10.1%), and head/face (n = 62, 11.7%; NTL: n = 14, 5.4%; TL: n = 47, 17.5%).

CONCLUSIONS

Volleyball IRs were highest in preseason and during competition. Most injuries affected the lower-extremity which is notable considering the high upper-extremity load in volleyball. Consideration of strategies to reduce injuries prior to the start of the formal sports season may be needed to help reduce the incidence of preseason injuries.

The prevalence of chronic ankle instability in basketball athletes: a cross-sectional study

Background

Ankle sprain is the most common injury in basketball. Chronic ankle instability develops from an acute ankle sprain may cause negative effects on quality of life, ankle functionality or on increasing risk for recurrent ankle sprains and post-traumatic osteoarthritis. To facilitate a preventative strategy of chronic ankle instability (CAI) in the basketball population, gathering epidemiological data is essential. However, the epidemiological data of CAI in basketball is limited. Therefore, this study aims to investigate the prevalence of CAI in basketball athletes and to determine whether gender, competitive level, and basketball playing position influence this prevalence.

Methods

In a cross-sectional study, in total 391 Taiwanese basketball athletes from universities and sports clubs participated. Besides non-standardized questions about demographics and their history of ankle sprains, participants further filled out the standard Cumberland Ankle Instability Tool applied to determine the presence of ankle instability. Questionnaires from 255 collegiate and 133 semi-professional basketball athletes (male = 243, female = 145, 22.3 ± 3.8 years, 23.3 ± 2.2 kg/m²) were analyzed. Differences in prevalence between gender, competitive level and playing position were determined using the Chi-square test.

Results

In the surveyed cohort, 26% had unilateral CAI while 50% of them had bilateral CAI. Women had a higher prevalence than men in the whole surveyed cohort (X²(1) = 0.515, p = 0.003). This gender disparity also showed from sub-analyses, that the collegiate female athletes had a higher prevalence than collegiate men athletes (X²(1) = 0.203, p = 0.001). Prevalence showed no difference between competitive levels (p > 0.05) and among playing positions (p > 0.05).

Conclusions

CAI is highly prevalent in the basketball population. Gender affects the prevalence of CAI. Regardless of the competitive level and playing position the prevalence of CAI is similar. The characteristic of basketball contributes to the high prevalence. Prevention of CAI should be a focus in basketball. When applying the CAI prevention measures, gender should be taken into consideration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-022-00418-0.

A Systematic Review on Fitness Testing in Adult Male Basketball Players: Tests Adopted, Characteristics Reported and Recommendations for Practice

Background

As basketball match-play requires players to possess a wide range of physical characteristics, many tests have been introduced in the literature to identify talent and quantify fitness in various samples of players. However, a synthesis of the literature to identify the most frequently used tests, outcome variables, and normative values for basketball-related physical characteristics in adult male basketball players is yet to be conducted.

Objective

The primary objectives of this systematic review are to (1) identify tests and outcome variables used to assess physical characteristics in adult male basketball players across all competition levels, (2) report a summary of anthropometric, muscular power, linear speed, change-of-direction speed, agility, strength, anaerobic capacity, and aerobic capacity in adult male basketball players based on playing position and competition level, and (3) introduce a framework outlining recommended testing approaches to quantify physical characteristics in adult male basketball players.

Methods

A systematic review of MEDLINE, PubMed, SPORTDiscus, Scopus, and Web of Science was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify relevant studies. To be eligible for inclusion, studies were required to: (1) be original research articles; (2) be published in a peer-reviewed journal; (3) have full-text versions available in the English language; and (4) include the primary aim of reporting tests used and/or the physical characteristics of adult (i.e., ≥ 18 years of age) male basketball players. Additionally, data from the top 10 draft picks who participated in the National Basketball Association combined from 2011–12 to 2020–21 were extracted from the official league website to highlight the physical characteristics of elite 19- to 24-year-old basketball players.

Results

A total of 1684 studies were identified, with 375 being duplicates. Consequently, the titles and abstracts of 1309 studies were screened and 231 studies were eligible for full-text review. The reference list of each study was searched, with a further 59 studies identified as eligible for review. After full-text screening, 137 studies identified tests, while 114 studies reported physical characteristics in adult male basketball players.

Conclusions

Physical characteristics reported indicate a wide range of abilities are present across playing competitions. The tests and outcome variables reported in the literature highlight the multitude of tests currently being used. Because there are no accepted international standards for physical assessment of basketball players, establishing normative data is challenging. Therefore, future testing should involve repeatable protocols that are standardised and provide outcomes that can be monitored across time. Recommendations for testing batteries in adult male basketball players are provided so improved interpretation of data can occur.

Clinical Trial Registration

This review was registered with the International Prospective Register of Systematic Reviews and allocated registration number CRD42020187151 on 28 April, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40279-021-01626-3.

Influence of Strength Programs on the Injury Rate and Team Performance of a Professional Basketball Team: A Six-Season Follow-Up Study

This study aims to determine possible associations between strength parameters, injury rates, and performance outcomes over six seasons in professional basketball settings. Thirty-six male professional basketball players [mean ± standard deviation (SD): age, 30.5 ± 4.7 years; height, 199.5 ± 9.5 cm; body mass, 97.9 ± 12.9 kg; BMI 24.6 ± 2.5 kg/m2] participated in this retrospective observational study, conducted from the 2008-09 to the 2013-14 season. According to their epidemiological records, each player followed an individual plan designed within different strength training programs: Functional (n = 16), Eccentric (n = 8), or Resistance (n = 12). Seven hundred and fourteen valid records were obtained from 170 individual strength tests during 31 sessions. Tests performed were leg press, squat, and jerk. Parameters recorded were force, power, velocity, peak velocity, and time to peak velocity for strength; time loss injury and muscle injury for injury rate; and games won, games lost, and championships for performance outcomes. All the strength variables and injuries are independent of the strength programs (p < 0.01). The correlation analysis showed very significant relationships between muscular injuries and time to peak velocity (r = 0.94; p < 0.01), significant relationships between force and games lost (r = 0.85; p < 0.05), and muscular injuries with games lost (r = -0.81; p < 0.05) per season. Mean values per season described a possible association of force, time to peak velocity, and muscular injuries with performance outcomes (R 2 = 0.96; p < 0.05). In this specific context, strength variables and injury rate data show no association with a single type of strength training program in this cohort of high-performance basketball players.

Classification and Optimization of Basketball Players’ Training Effect Based on Particle Swarm Optimization

Since the professionalization of basketball in China, the number of teenagers participating in basketball training has gradually increased, which has promoted the improvement of basketball level in China. Teenagers ‘love' for basketball further promotes the improvement of basketball level in China. However, the reality of basketball in China still lags far behind that of developed basketball countries, in which backward training is an important aspect. This paper mainly makes a comprehensive overview of the training effect and classification of basketball players through particle swarm optimization, objectively evaluates the training effect of physical fitness, and proposes corresponding optimization measures, aiming at the scientific optimization of physical training for basketball players in China. In order to rationally arrange the training methods, control the training process, and make the training scientific, the effectiveness of the particle swarm optimization algorithm for the classification of basketball players' training effects is analyzed, and a new population-based optimization method is proposed. The experimental results verify the superiority of the particle swarm optimization algorithm. It is an inevitable choice to enhance the physical strength level of basketball reserve strength by using appropriate methods to train basketball players.

Submaximal Fitness Tests in Team Sports: A Theoretical Framework for Evaluating Physiological State

Team-sports staff often administer non-exhaustive exercise assessments with a view to evaluating physiological state, to inform decision making on athlete management (e.g., future training or recovery). Submaximal fitness tests have become prominent in team-sports settings for observing responses to a standardized physical stimulus, likely because of their time-efficient nature, relative ease of administration, and physiological rationale. It is evident, however, that many variations of submaximal fitness test characteristics, response measures, and monitoring purposes exist. The aim of this scoping review is to provide a theoretical framework of submaximal fitness tests and a detailed summary of their use as proxy indicators of training effects in team sports. Using a review of the literature stemming from a systematic search strategy, we identified five distinct submaximal fitness test protocols characterized in their combinations of exercise regimen (continuous or intermittent) and the progression of exercise intensity (fixed, incremental, or variable). Heart rate-derived indices were the most studied outcome measures in submaximal fitness tests and included exercise (exercise heart rate) and recovery (heart rate recovery and vagal-related heart rate variability) responses. Despite the disparity between studies, these measures appear more relevant to detect positive chronic endurance-oriented training effects, whereas their role in detecting negative transient effects associated with variations in autonomic nervous system function is not yet clear. Subjective outcome measures such as ratings of perceived exertion were less common in team sports, but their potential utility when collected alongside objective measures (e.g., exercise heart rate) has been advocated. Mechanical outcome measures either included global positioning system-derived locomotor outputs such as distance covered, primarily during standardized training drills (e.g., small-sided games) to monitor exercise performance, or responses derived from inertial measurement units to make inferences about lower limb neuromuscular function. Whilst there is an emerging interest regarding the utility of these mechanical measures, their measurement properties and underpinning mechanisms are yet to be fully established. Here, we provide a deeper synthesis of the available literature, culminating with evidence-based practical recommendations and directions for future research.

"The Competitive Season and Off-Season": Preliminary Research concerning the Sport-Specific Performance, Stress, and Sleep in Elite Male Adolescent Basketball Athletes

BACKGROUND

Through scholastic sports programs, adolescent athletes compete to represent their communities. However, few studies investigate the changes in physiological and mental profiles during varied sport periodization among this population. Therefore, the purpose of this study was to compare the changes in sports performance and stress-related biomarkers between the competitive season (CS) and off-season (OS) in elite adolescent basketball players.

METHOD

Nine elite Division I male basketball players (age: 15-18 years. old) participated in this study. Basketball-specific performance, salivary dehydroepiandrosterone sulfate (DHEA-S)/cortisol levels, mood state, and sleep quality were all accessed during the CS and OS periods.

RESULTS

The training load during OS was 26.0% lower than CS (p = 0.001). Muscle mass, aerobic capacity, 10 m sprint, and Abalakov jump (AJ) power during OS were greater than that during CS (+2.2-9.8%, p < 0.05), but planned agility was greater during CS (p = 0.003). The salivary DHEA-S/cortisol was greater during CS than during OS (p = 0.039). The overall mood state and sleep quality did not differ between periods, but the POMS-tension was higher during CS (p = 0.005).

CONCLUSION

The present study demonstrates that muscle mass, aerobic capacity, peak AJ power, and 10 m sprint performance, but not planned agility, were greater during OS compared to CS among elite adolescent basketball players. Furthermore, the stress-related responses reflected by the D/C ratio and mood tension were relatively lower during the OS in these athletes. Thus, this study suggests that coaches and sport science professionals should closely monitor athletes' training states across varied training/competition periods to better react to modifying training or recovery plans.

Biomechanical Loads and Their Effects on Player Performance in NCAA D-I Male Basketball Games

Basketball games and training sessions are characterized by quick actions and many scoring attempts, which pose biomechanical loads on the bodies of the players. Inertial Measurement Units (IMUs) capture these biomechanical loads as PlayerLoad and Inertial Movement Analysis (IMA) and teams collect those data to monitor adaptations to training schedules. However, the association of biomechanical loads with game performance is a relatively unexplored area. The aims of the current study were to determine the statistical relations between biomechanical loads in games and training with game performance. Biomechanical training and game load measures and player-level and team-level game stats from one college basketball team of two seasons were included in the dataset. The training loads were obtained on the days before gameday. A three-step analysis pipeline modeled: (i) relations between team-level game stats and the win/loss probabilities of the team, (ii) associations between the player-level training and game loads and their game stats, and (iii) associations between player-level training loads and game loads. The results showed that offensive and defensive game stats increased the odds of winning, but several stats were subject to positional and individual performance variability. Further analyses, therefore, included total points [PTS], two-point field goals, and defensive rebounds (DEF REB) that were less subject to those influences. Increases in game loads were significantly associated with game stats. In addition, training loads significantly affected the game loads in the following game. In particular, increased loads 2 days before the game resulted in increased expected game loads. Those findings suggested that biomechanical loads were good predictors for game performance. Specifically, the game loads were good predictors for game stats, and training loads 2 days before gameday were good predictors for the expected game load. The current analyses accounted for the variation in loads of players and stats that enabled modeling the expected game performance for each individual. Coaches, trainers, and sports scientists can use these findings to further optimize training plans and possibly make in-game decisions for individual player performance.

Influence of the Pedagogical Model and Experience on the Internal and External Task Load in School Basketball

The methodology used by the teacher in Physical Education sessions conditions the physical fitness of the students, since the design of the tasks determines the physical and physiological demands to which they are exposed. This study aimed to quantify and compare, according to the teaching methodology and students' previous experience, the external (eTL) and internal (iTL) load resulting from the application of three intervention programmes that follow different teaching methodologies to teach school basketball: the Tactical Games Approach (TGA), Direct Instruction (DI) and Service Teacher's Basketball Unit (STBU). The Ratings of Perceived Exertion (RPEs) recorded in the assessments (pre-test/post-test) were also studied. A total of 49 students, aged 11 to 12 and divided into three class groups, from the sixth grade of primary education at a state school in Spain, participated in the study. Teaching-learning programs were randomly assigned to student groups. All the sessions were monitored with inertial devices that made it possible to record physical activity and convert the information into kinematic parameters. The results indicated that during the sessions, the students who followed the TGA method recorded higher values of eTL (player load; DI = 4.92, TGA = 6.95, STBU = 2.99) and iTL (mean heart rate; DI = 142.94, TGA = 157.12, STBU = 143.98). In addition, during the evaluation tests, they presented heart rate levels similar to those obtained by the students in the other programmes. However, they spent more time doing high-intensity activity, working longer in the running (DI = 3.42, TGA = 11.26, STBU = 8.32) and sprinting speed ranges (DI = 0.00, TGA = 0.12, STBU = 0.11), and presenting better physical fitness. During the assessments, students with no prior basketball experience showed higher levels of top speed; experienced students had higher levels of heart rate. The TGA method favours the physical condition and health of primary education students, which is why this method is recommended when planning Physical Education sessions.

Exploring Physical Fitness Profile of Male and Female Semiprofessional Basketball Players through Principal Component Analysis-A Case Study

Basketball is a sport in continuous evolution, being one of these key aspects of the players' physical fitness that has an impact on the game. Therefore, this study aimed to characterize and identify the physical fitness level and profiles of basketball players according to sex. Total of 26 semi-professional basketball players were assessed (13 male, 13 female) through inertial devices in different previously validated fitness tests. T-test for independent samples and principal component analysis were used to analyze sex-related differences and to identify physical fitness profiles. The results showed differences according to sex in all physical fitness indexes (p < 0.01; d > 1.04) with higher values in males, except in accelerometer load during small-sided games (p = 0.17; d < 0.20). Four principal components were identified in male and female basketball players, being two common ([PC1] aerobic capacity and in-game physical conditioning, [PC4 male, PC3 female] unipodal jump performance) and two different profiles (male: [PC2] bipodal jump capacity and acceleration, [PC3] curvilinear displacement; female: [PC2] bipodal jump capacity and curvilinear displacement, [PC4] deceleration). In conclusion, training design must be different and individualized according to different variables, including physical fitness profiles between them. For practical applications, these results will allow knowing the advantages and weaknesses of each athlete to adapt training tasks and game systems based on the skills and capabilities of the players in basketball.

Longitudinal Hydration Assessment in Collegiate Basketball Players Over Various Training Phases

ABSTRACT

Heishman, AD, Daub, BD, Miller, RM, Freitas, EDS, and Bemben, MG. Longitudinal hydration assessment in collegiate basketball players over various training phases. J Strength Cond Res 35(4): 1089-1094, 2021-To the best of our knowledge, previous literature has not longitudinally examined hydration status in collegiate basketball players. Therefore, the purpose of this investigation was to examine the prepractice hydration status of collegiate basketball players across various training phases for 2 consecutive years. Retrospective analyses examined prepractice urine-specific gravity (USG) assessments obtained from National Collegiate Athletic Association (NCAA) Division I male basketball players during the preseason and competitive season, for 2 consecutive years. The first year (year 1 = Y1) of analysis consisted of 15 athletes and the second year (year 2 = Y2) consisted of 16 athletes, with 8 athletes in both seasons. Hydration status was classified based on the National Athletic Trainers' criteria: (a) euhydrated, USG < 1.020; (b) hypohydrated, USG = 1.020-1.030; and (c) significantly hypohydrated, USG > 1.030. Additional comparisons examined the association of minutes played with hydration status and changes in hydration status for athletes returning from Y1 to Y2. The results indicated 55-65.7% of cases showed levels of significant hypohydration during the preseason and competitive seasons for both years. Preseason hydration status was significantly better than the competitive season (Y1, p = 0.008; Y2, p = 0.005). Despite significant differences in minutes played (p < 0.001), no differences in hydration status were observed. Returning athletes displayed no differences in hydration status between Y1 and Y2. Collegiate basketball players show levels of hypohydration when longitudinally examined across various training phases. Although hydration may be improved in the preseason, alternative factors such as average game minutes played and length in program may not influence hydration status.

Positional Differences in the Most Demanding Scenarios of External Load Variables in Elite Futsal Matches

The aims of this study were to analyze the peak physical demands in elite futsal by quantifying the most demanding scenarios of match play and to identify the differences between playing positions (defenders, wingers, and pivots) and the seasonal trend for five different rolling average time windows (30, 60, 120, 180, and 300 s). The most demanding scenarios of external load from distance, speed, acceleration, and deceleration variables were obtained from 14 elite futsal players using a local positioning system during 15 official matches in the premier Spanish Futsal League (2018-2019 season). The results showed an extremely large effect of the time window for all dependent variables in all positional groups. Another important finding of this study was that, in regard to the seasonal trend, only defenders reported clear moderate-large positive trends for high-speed running (>18 km⋅h-1) efforts, high-acceleration efforts, and high-deceleration efforts. Finally, moderate-large individual differences in player means for all dependent variables and clear differences between games for most dependent variables were found, suggesting how likely contextual factors may exert an influence on how "demanding" the most demanding scenarios are. The findings of this study provide coaches and strength and conditioning coaches further knowledge of the peak physical demands in elite futsal competition. This valuable information may lead to a more precise position-specific training prescription.

The Business End of the Season: A Comparison Between Playoff and Regular-Season Workloads in Professional Basketball Players

PURPOSE

To quantify and compare the internal workloads experienced during the playoffs and regular season in basketball.

METHODS

A total of 10 professional male basketball players competing in the Italian first division were monitored during the final 6 weeks of the regular season and the entire 6-week playoff phase. Internal workload was quantified using the session rating of perceived exertion (s-RPE) method for all training sessions and games. A 2-way repeated-measures analysis of variance (day type × period) was utilized to assess differences in daily s-RPE between game days, days within 24 hours of games, and days >24 hours from games during the playoffs and regular season. Comparisons in weekly training, game, and total workloads were made between the playoffs and regular season using paired t tests and effect sizes.

RESULTS

A significant interaction between day and competitive period for s-RPE was found (P = .003, moderate). Lower s-RPE was apparent during playoff and regular-season days within 24 hours of games than all other days (P < .001, very large). Furthermore, s-RPE across days >24 hours from playoff games was different than all other days (P ≤ .01, moderate-very large). Weekly training (P = .009, very large) and total (P < .001, moderate) s-RPE were greater during the regular season than playoffs, whereas weekly game s-RPE was greater during the playoffs than the regular season (P < .001, very large).

CONCLUSIONS

This study presents an exploratory investigation of internal workload during the playoffs in professional basketball. Players experienced greater training and total weekly workloads during the regular season than during the playoffs with similar daily game workloads between periods.

Monitoring Training Load and Perceived Recovery in Female Basketball: Implications for Training Design

Sansone, P, Tschan, H, Foster, C, and Tessitore, A. Monitoring training load and perceived recovery in female basketball: Implications for training design. J Strength Cond Res 34(10): 2929-2936, 2020-This study investigated the relationship between internal training load and perceived recovery of semi-professional female basketball players during the competitive season. Eleven female players were monitored for 14 weeks during the in-season phase. For each event (training and game), data were collected as follows: (a) Total Quality Recovery (TQR) score before the event (TQRpre); (b) session Rating of Perceived Exertion (sRPE) 20 minutes after completion of the event, to calculate training load (s-TL) of the event; and (c) TQR scores 12 (TQRpost12) and 24 hours (TQRpost24) after the event. Data were analyzed for daily, weekly, and mesocycle (regular season; regional play-off; and national play-off) time frames. Daily analysis showed that: TQRpost12 was lower than TQRpre (p < 0.001) and TQRpost24 (p < 0.001); s-TL had a moderate negative correlation with TQRpost12 (r = -0.48, p = 0.002); the difference between TQRpre and RPE (TS-Δ) had a very large positive correlation with TQRpost12 (r = 0.70, p < 0.001); and TQRpost24 was not significantly correlated with training parameters. Weekly analysis highlighted a very large negative correlation between the acute:chronic workload ratio and TQR collected at the start of the following week (TQRfw) (r = -0.86, p < 0.001). Finally, although weekly TL and TQRfw did not differ between mesocycles, their correlation increased in the later seasonal phases. This study demonstrated negative relationships between training load and recovery of semi-professional female basketball players at daily, weekly, and mesocycle levels. Therefore, concurrently monitoring training and recovery with the sRPE method and TQR scale is recommended for designing training schedules in basketball.

Monitoring the External and Internal Load Under 2 Teaching Methodologies

González-Espinosa, S, Antúnez, A, Feu, S, and Ibáñez, SJ. Monitoring the external and internal load under 2 teaching methodologies. J Strength Cond Res 34(10): 2920-2928, 2020-The purpose of this study was to analyze and compare the physical demands produced by the implementation of 2 sport teaching methods during a class and their relation with the learning achieved by the students. Two intervention programs were used to teach the sport of basketball, one based on the direct instruction (DI) method and the other on the tactical-game approach (TGA). The intervention programs were administered to 4 groups of students, 2 for each methodology, with 88 students participating in the study. A total of 10 practical sessions were given, as well as a pre-test and post-test. The practical sessions and the tests were recorded with an inertial system for monitoring and recording physical activity and movement in real time. Differences were found between the methodologies in the teaching sessions in the variables m·min, acc·min, PL·min, and HRmax (p < 0.000). In the assessment tests, there were also differences between both methodologies in the walk and sprint variables (p < 0.005). The results obtained from the analysis of the sessions using each methodology show that the TGA method obtained better results in the variables of external and internal loads than the DI methodology. The TGA methodology permitted a greater development of the students' physical fitness. Moreover, performance in play was not associated with the achievement of higher values in the results of external and internal load in the tests. The students trained with the TGA methodology recorded better performance indicators in the game. These results lead us to recommend physical education teachers to use a student-centered approach in their lessons because it improved both the students' physical fitness and their sports performance.

Measuring Physical Demands in Basketball: An Explorative Systematic Review of Practices

BACKGROUND

Measuring the physical work and resultant acute psychobiological responses of basketball can help to better understand and inform physical preparation models and improve overall athlete health and performance. Recent advancements in training load monitoring solutions have coincided with increases in the literature describing the physical demands of basketball, but there are currently no reviews that summarize all the available basketball research. Additionally, a thorough appraisal of the load monitoring methodologies and measures used in basketball is lacking in the current literature. This type of critical analysis would allow for consistent comparison between studies to better understand physical demands across the sport.

OBJECTIVES

The objective of this systematic review was to assess and critically evaluate the methods and technologies used for monitoring physical demands in competitive basketball athletes. We used the term 'training load' to encompass the physical demands of both training and game activities, with the latter assumed to provide a training stimulus as well. This review aimed to critique methodological inconsistencies, establish operational definitions specific to the sport, and make recommendations for basketball training load monitoring practice and reporting within the literature.

METHODS

A systematic review of the literature was performed using EBSCO, PubMed, SCOPUS, and Web of Science to identify studies through March 2020. Electronic databases were searched using terms related to basketball and training load. Records were included if they used a competitive basketball population and incorporated a measure of training load. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration # CRD42019123603), and approved under the National Basketball Association (NBA) Health Related Research Policy.

RESULTS

Electronic and manual searches identified 122 papers that met the inclusion criteria. These studies reported the physical demands of basketball during training (n = 56), competition (n = 36), and both training and competition (n = 30). Physical demands were quantified with a measure of internal training load (n = 52), external training load (n = 29), or both internal and external measures (n = 41). These studies examined males (n = 76), females (n = 34), both male and female (n = 9), and a combination of youth (i.e. under 18 years, n = 37), adults (i.e. 18 years or older, n = 77), and both adults and youth (n = 4). Inconsistencies related to the reporting of competition level, methodology for recording duration, participant inclusion criteria, and validity of measurement systems were identified as key factors relating to the reporting of physical demands in basketball and summarized for each study.

CONCLUSIONS

This review comprehensively evaluated the current body of literature related to training load monitoring in basketball. Within this literature, there is a clear lack of alignment in applied practices and methodological framework, and with only small data sets and short study periods available at this time, it is not possible to draw definitive conclusions about the true physical demands of basketball. A detailed understanding of modern technologies in basketball is also lacking, and we provide specific guidelines for defining and applying duration measurement methodologies, vetting the validity and reliability of measurement tools, and classifying competition level in basketball to address some of the identified knowledge gaps. Creating alignment in best-practice basketball research methodology, terminology and reporting may lead to a more robust understanding of the physical demands associated with the sport, thereby allowing for exploration of other research areas (e.g. injury, performance), and improved understanding and decision making in applying these methods directly with basketball athletes.

Seasonal Variations in Game Activity Profiles and Players' Neuromuscular Performance in Collegiate Division I Basketball: Non-conference vs. Conference Tournament

Basketball has a high demand on a player's neuromuscular system due to a high volume of explosive high-intensity actions. This study aimed to examine the seasonal variations on game demands and players' neuromuscular performance during the Non-Conference (NON-CONF) and Conference (CONF) seasons in NCAA Division I Men's Basketball. Seven NCAA Division I Basketball players' (20 ± 1.2 years, 1.95 ± 0.1 m, and 94 ± 15 kg) match activity profiles were tracked in 17 home games (7 NON-CONF; 10 CONF); furthermore, players performed a repeat hop test on a force platform the day before competition to assess neuromuscular performance. A t-test for paired samples was used to analyze the differences between NON-CONF and CONF. Results indicated no significant differences in Total Distance, Peak Speed, Acceleration, and Deceleration loads when comparing NON-CONF and CONF match-play. Regarding neuromuscular performance, Jump Height (p = 0.03; ES = 0.43) was negatively affected during CONF. Moreover, a trend toward a decline in Peak Force (p = 0.06; ES = 0.38) was found in CONF. Conversely, no differences were obtained regarding Reactive Strength Index and Contact Time. In conclusion, match-play demands remained constant across the season whilst neuromuscular outputs were inhibited during the CONF season.

Countermovement Jump Reliability Performed With and Without an Arm Swing in NCAA Division 1 Intercollegiate Basketball Players

Heishman, AD, Daub, BD, Miller, RM, Freitas, EDS, Frantz, BA, and Bemben, MG. Countermovement jump reliability performed with and without an arm swing in NCAA Division 1 intercollegiate basketball players. J Strength Cond Res 34(2): 546-558, 2020-The countermovement jump (CMJ) is routinely used in athlete performance to quantify adaptions to training, as well as monitor neuromuscular readiness and fatigue. However, controversy remains in whether to incorporate an arm swing during the CMJ (CMJ AS) or keep the hands placed on the hips (CMJ NAS). Incorporating the arms provides a higher degree of sport-specificity that may yield improved reliability, especially in skilled jumpers. By contrast, the hands-on-hips approach isolates lower extremity force production and eliminates potential arm-swing variation. Therefore, the purpose of this study was to establish the reliability of CMJ typical (CMJ-TYP), CMJ concentric alternative (CMJ-Conc-ALT), and CMJ eccentric alternative (CMJ-Ecc-ALT) variables obtained during the CMJ AS and CMJ NAS. Twenty-two (men = 14, women = 8) NCAA Division 1 collegiate basketball players performed 3 CMJ AS and 3 CMJ NAS on a force plate, in a randomized order. To assess the test-retest reliability, participants returned 1 week later to perform 3 additional CMJ AS and 3 CMJ NAS. Intraclass correlation coefficient (ICC) and coefficient of variation (CV) were used to assess intersession and intrasession reliability for the various CMJ variables. A majority of CMJ-TYP and several CMJ-Conc-ALT and CMJ-Ecc-ALT variables exhibited adequate intersession and intrasession reliability (ICC > 0.700 and CV <10%) during both the CMJ AS and the CMJ NAS. Countermovement jump AS may provide more pertinent information about long-term changes in sport-specific performance, whereas the CMJ NAS may be more beneficial for detecting acute changes in neuromuscular fatigue and athlete readiness.

Effects of Six Weeks of High-Intensity Functional Training on Physical Performance in Participants with Different Training Volumes and Frequencies

High-intensity functional training (HIFT) is characterized by presenting high volumes and training intensities with constantly varied exercises. The aim of this study was to analyze the internal training load and the effects of high-intensity functional training on physical performance in subjects with different training volumes and frequencies. A total of 31 volunteers involved in high-intensity functional training (14 men and 17 women) were divided according to their training volumes and frequencies (high training-volume and frequency-HTVF; (n = 17) (nine women and eight men; age: 31.0 ± 6.3 years; height: 168.8 ± 8.1 cm, body weight: 73.6 ± 11.9 kg; BMI: 25.96 kg/m²) and moderate training volume and frequency-MTVF; (n = 14) (eight women and six men; age: 26.6 ± 4.7 years; height: 167.2 ± 8.6 cm, body weight: 75.8 ± 18.0 kg; BMI: 27.33 kg/m²)). The internal training load was determined using the session-rating of perceived exertion method. The monotony index (MI) and training strain (TS) were used to determine training variability during the training weeks. Countermovement vertical jump height, 20-m sprinting and handgrip strength were assessed at baseline and after six weeks of training. There was a time effect for MI ((F_{(5, 145)} = 5.942; p = 0.0001)), TS ((F_{(5, 145)} = 5.734; p = 0.0001)), weekly internal training load ((F_{(4.006, 116.87)} = 4.188; p = 0.003)) and mean weekly internal training load ((F_{(4.006, 116.87)} = 4.188; p = 0.003)). There was no increase in performance in either group for countermovement vertical jump height ((F_(1,29) = 6.081; p = 0.050)), sprinting ((F_(1,29) = 1.014; p = 0.322)), right handgrip strength ((F_(1,29) = 2.522; p = 0.123)) or left handgrip strength ((F_(1,29) = 2.550; p = 0.121)). The current findings suggest that six weeks of high-intensity functional training was not able to increase performance in either group. Therefore, different volumes and frequencies do not seem to influence the increase in physical performance of HIFT practitioners.

The Impact of Training Load on Sleep During a 14-Day Training Camp in Elite, Adolescent, Female Basketball Players

PURPOSE

To quantify the sleep/wake behaviors of adolescent, female basketball players and to examine the impact of daily training load on sleep/wake behaviors during a 14-day training camp.

METHODS

Elite, adolescent, female basketball players (N = 11) had their sleep/wake behaviors monitored using self-report sleep diaries and wrist-worn activity monitors during a 14-day training camp. Each day, players completed 1 to 5 training sessions (session duration: 114 [54] min). Training load was determined using the session rating of perceived exertion model in arbitrary units. Daily training loads were summated across sessions on each day and split into tertiles corresponding to low, moderate, and high training load categories, with rest days included as a separate category. Separate linear mixed models and effect size analyses were conducted to assess differences in sleep/wake behaviors among daily training load categories.

RESULTS

Sleep onset and offset times were delayed (P < .05) on rest days compared with training days. Time in bed and total sleep time were longer (P < .05) on rest days compared with training days. Players did not obtain the recommended 8 to 10 hours of sleep per night on training days. A moderate increase in sleep efficiency was evident during days with high training loads compared with low.

CONCLUSIONS

Elite, adolescent, female basketball players did not consistently meet the sleep duration recommendations of 8 to 10 hours per night during a 14-day training camp. Rest days delayed sleep onset and offset times, resulting in longer sleep durations compared with training days. Sleep/wake behaviors were not impacted by variations in the training load administered to players.

Differences in Weekly Load Distribution Over Two Euroleague Seasons with a Different Head Coach

The weekly training management and competition loads are important aspects to optimize the performance of professional basketball players. The objectives of the study were (a) to describe the weekly external load (EL), as well as the internal response (IR), of elite basketball players over two consecutive seasons with a different head coach and (b) to compare weekly loads of different competitive densities. The data were collected from 27 elite players from the same team competing in the Spanish first division league (ACB) and EuroLeague during 2017–2018 and 2018–2019 seasons. EL was measured using microsensor technology to determine PlayerLoad values, expressed in arbitrary units (AU). Session rating of perceived exertion (sRPE) was used for IR quantification. Comparisons between the two seasons and of weeks with different competitive densities were made. The inter-week load variability was moderate-high for both seasons. The highest EL values were measured during the weeks with three games (W3) (W3 > W0 > W2 > W1), while the most demanding week for players’ IR was observed during weeks with no competition (W0). Additionally, higher EL (d = 0.31) and IR (d = 0.37) values were observed in season 2018–2019 compared to 2017–2018. The results obtained in this study contributed new data on the internal and external load required by professional basketball players in weeks with different number of games and showed that different coaching strategies may demand a different external and internal workload in consecutive seasons. Furthermore, the results highlighted the need to carry out an adequate load management program.

A Systematic Review of the External and Internal Workloads Experienced During Games-Based Drills in Basketball Players

PURPOSE

To systematically quantify the external and internal workloads reported during games-based drills in basketball and identify the effects of different modifiable factors on the workloads encountered.

METHODS

PubMed, Scopus, MEDLINE, and SPORTDiscus databases were searched for original research published up until January 2, 2019. The search included terms relevant to workload, games-based drills, and basketball. Studies were screened using predefined selection criteria, and methodological quality was assessed prior to data extraction.

RESULTS

The electronic search yielded 8,284 studies with 3,411 duplicates. A total of 17 studies met the inclusion criteria for this review, with quality scores ranging from 9 to 10 out of 11. Factors regularly modified during games-based drills among the included studies were team size, playing area, playing and rest time, and game alterations. Games-based drills containing smaller team sizes elicited greater external and internal workloads compared to larger team sizes. Furthermore, full-court games-based drills elicited greater external and internal workloads compared to half-court drills, while continuous games-based drills elicited greater internal workloads compared to intermittent drills.

CONCLUSIONS

This review provides a comprehensive collation of data indicating the external and internal workloads reported during different games-based drills in various samples of basketball players. Furthermore, evidence is provided for basketball coaches to consider when prescribing games-based drills and modifying factors during drills across the season. Current literature suggests that smaller team sizes and full-court playing areas elicit greater external and internal workloads than larger team sizes and half-court drills, respectively. Furthermore, continuous games-based drills elicit greater internal workloads than intermittent drills.

Peak Match Demands in Young Basketball Players: Approach and Applications

Background: The aim of this study is to describe the peak match demands and compare them with average demands in basketball players, from an external load point of view, using different time windows. Another objective is to determine whether there are differences between positions and to provide an approach for practical applications. Methods: During this observational study, each player wore a micro technology device. We collected data from 12 male basketball players (mean ± SD: age 17.56 ± 0.67 years, height 196.17 ± 6.71 cm, body mass 90.83 ± 11.16 kg) during eight games. We analyzed intervals for different time windows using rolling averages (ROLL) to determine the peak match demands for Player Load. A separate one-way analysis of variance (ANOVA) was used to identify statistically significant differences between playing positions across different intense periods. Results: Separate one-way ANOVAs revealed statistically significant differences between 1 min, 5 min, 10 min, and full game periods for Player Load, F (3,168) = 231.80, η_p² = 0.76, large, p < 0.001. It is worth noting that guards produced a statistically significantly higher Player Load in 5 min (p < 0.01, η_p² = −0.69, moderate), 10 min (p < 0.001, η_p² = −0.90, moderate), and full game (p < 0.001, η_p² = −0.96, moderate) periods than forwards. Conclusions: The main finding is that there are significant differences between the most intense moments of a game and the average demands. This means that understanding game demands using averages drastically underestimates the peak demands of the game. This approach helps coaches and fitness coaches to prepare athletes for the most demanding periods of the game and present potential practical applications that could be implemented during training and rehabilitation sessions.

External Workload Can Be Anticipated During 5 vs. 5 Games-Based Drills in Basketball Players: An Exploratory Study

This study determined whether external workload could be anticipated during 5 vs. 5 games-based drills in basketball. Thirteen semi-professional, male basketball players were monitored during 5 vs. 5 training drills across the season. External workload was determined using PlayerLoad™ (AU∙min-1). The reference workload for each drill was calculated across all sessions, using bootstrapping. The bootstrap mean workload and 95% confidence intervals (CI) were then calculated for session 1, sessions 1-2, and continued for remaining sessions (1-3, 1-4, etc.), and were compared with those of the reference workload. The minimum sessions to anticipate workload for each drill was identified when the first normative value fell within ±5% or ±10% of the reference workload 95% CI. The minimum sessions were then tested to determine the accuracy to which workload could be anticipated. Three to four sessions were needed to anticipate workload within ±5%, while 2-3 sessions were needed to anticipate workload within ±10%. External workload was anticipated in 0-55% of future sessions using an error range of ±5%, and in 58-89% of sessions using an error range of ±10%. External workload during 5 vs. 5 games-based drills can be anticipated in most sessions using normative values established during a short-term monitoring period with an error range of ±10%.

Seasonal changes in physical capacities of basketball players according to competitive levels and individual responses

Purpose

The aim of this study was to quantify changes in physical capacities of thirty-eight basketball players selected from different teams, as well as from varying competitive levels (i.e. Division I, Division II and Division III) during the preparation and in-season periods.

Methods

Pre (T1) and post (T2) preparation period and during regular season (T3), the players completed a Yo-Yo Intermittent Recovery test—level 1. Following a 3 to 8 days-break, players performed a 6-min continuous running test (Mognoni’s test), a counter-movement jump test and a 5-min high-intensity intermittent running test.

Results

Blood lactate concentration measured after the Mognoni’s test was significantly reduced from T1 to T2, and from T2 to T3 (P<0.001, ƞ² = 0.424). The distance covered during the Yo-Yo Intermittent Recovery test was significantly increased only from T1 to T2 in Division II and III (P<0.001, ƞ² = 0.789). Similarly, the physiological responses to high-intensity intermittent running test were improved only from T1 to T2 (all P<0.001, ƞ² = 0.495 to 0.652). Despite significant changes observed in running tests from T1 to T2, at individual level 35–55% of players did not show a very likely improvement. Relative peak power produced during vertical jumps at T3 by Division I players was increased compared to T1 (ANOVA interaction, P = 0.037, ƞ² = 0.134).

Conclusions

The main improvements in physical capacities occurred during the preparation period, when the aerobic fitness and the ability to sustain high-intensity intermittent efforts were moderately-to-largely improved. However, it appears that the preparation period does not consistently impact on vertical jump variables. Aerobic fitness and force/power production during vertical jumps appear to improve across the competitive season (slightly-to-moderately). Physical tests should be used to identify weaknesses in physical performance of players and to monitor their fatigue status, with the aim to develop individualized training programs.

Investigating the workload, readiness and physical performance changes during intensified 3-week preparation periods in female national Under18 and Under20 basketball teams

This study aimed to investigate between- and within-team changes in workload [PlayerLoad (PL), training impulse (TRIMP) and session rate of perceived exertion training load (sRPE-TL)], readiness [heart rate variability (HRV)], and physical performance [20-m sprint test (including 10-m split time), countermovement jump (CMJ) and yo-yo intermittent recovery test level 1 (YYIR1)] during 3-week intensified preparation periods in female, national Under18 (n = 12, age = 18.0 ± 0.5y, stature = 180.4 ± 7.5 cm, body mass = 72.7 ± 9.3 kg) and Under20 (n = 12, age = 19.6 ± 0.8y, stature = 178.6 ± 6.4 cm, body mass = 68.0 ± 5.9 kg) basketball teams. Under18 team revealed small-to-moderate statistically significantly higher values in workload [PL: p = 0.010; ES = Small; TRIMP: p = 0.004; ES = Moderate; sRPE-TL: p < 0.001; ES = Moderate] and moderately lower readiness values (p = 0.023; ES = Moderate) compared to Under20. Within-team analysis showed no differences in workload in Under20 and statistically significant reduction (p < 0.05) in Week3 (taper period) in Under18. Pre- and post-preparation changes showed Under18 increasing only YYIR1 performance (p < 0.001; ES = Very large). Differently, Under20 statistically improved in 10-m split time (p = 0.003; ES = Moderate), CMJ (p = 0.025; ES = Moderate) and YYIR1 (p < 0.001; ES = Large). A constant adequate workload positively benefits players' readiness and physical performances during short intensified preparation periods. Conversely, using high workload with periodization strategies encompassing short overload and taper phases induced positive changes on players' aerobic performance, lower readiness values and no changes in anaerobic performances.

Training load and match-play demands in basketball based on competition level: A systematic review

Basketball is a court-based team-sport that requires a broad array of demands (physiological, mechanical, technical, tactical) in training and competition which makes it important for practitioners to understand the stress imposed on the basketball player during practice and match-play. Therefore, the main aim of the present systematic review is to investigate the training and match-play demands of basketball in elite, sub-elite, and youth competition. A search of five electronic databases (PubMed, SportDiscus, Web of Science, SCOPUS, and Cochrane) was conducted until December 20^th, 2019. Articles were included if the study: (i) was published in English; (ii) contained internal or external load variables from basketball training and/or competition; and (iii) reported physiological or metabolic demands of competition or practice. Additionally, studies were classified according to the type of study participants into elite (20), sub-elite (9), and youth (6). A total of 35 articles were included in the systematic review. Results indicate that higher-level players seem to be more efficient while moving on-court. When compared to sub-elite and youth, elite players cover less distance at lower average velocities and with lower maximal and average heart rate during competition. However, elite-level players have a greater bandwidth to express higher velocity movements. From the present systematic review, it seems that additional investigation on this topic is warranted before a “clear picture” can be drawn concerning the acceleration and deceleration demands of training and competition. It is necessary to accurately and systematically assess competition demands to provide appropriate training strategies that resemble match-play.

Comparing the External Loads Encountered during Competition between Elite, Junior Male and Female Basketball Players

The aim of the present study was to compare external loads (EL) between elite, junior, male and female basketball players. Male (n = 25) and female players (n = 48) were monitored during 11 competitive matches (3 matches per team). EL was measured using local positioning system and microsensor technology to determine total, high-intensity (14–21 km·h⁻¹), and sprint (>21 km·h⁻¹) distance (m) covered, total (n) and relative (n·min⁻¹) accelerations and decelerations, ratio of accelerations:decelerations, and total (arbitrary units [AU]) and relative (AU·min⁻¹) player load. EL was compared between sexes overall and according to each playing position (guards, forwards, and centers). Males covered larger (p < 0.05) high-intensity and sprint distances, and completed more (p < 0.05) decelerations than females; while female players experienced a greater (p < 0.05) ratio of accelerations:decelerations. Greater decelerations (p < 0.05) were observed for males in the guard position compared to females, while more (p < 0.05) accelerations·min⁻¹ were apparent for females in the forward position compared to males. The current findings indicate differences in EL, particularly the high-intensity and acceleratory demands, exist between elite, junior, male and female basketball players during competition and are affected by playing position. These outcomes can be used in developing sex- and position-specific training plans, and in turn improving the physical preparedness of junior basketball players for competition demands at the elite level.

Quantification of the Perceived Training Load in Young Female Basketball Players

Otaegi, A and Los Arcos, A. Quantification of the perceived training load in young female basketball players. J Strength Cond Res 34(2): 559-565, 2020-The purposes of this study were (a) to compare training session, match, and weekly perceived training load (TL) between U15 and U16 female basketball players and (b) within the teams, to assess the relationship between perceived TL and the changes in physical fitness performance during an in-season 9-week period. Twenty-one female players from U15 and U16 female teams from the same Spanish club participated in the study. Before and after the study, players were tested to determine physical fitness performance (using Yo-Yo IR1, countermovement jump, T-Test, and 15 m sprint). Each player declared her perceived exertion (PE) for the whole training session and match using Foster's 0-10 scale. Training week perceived TL was higher for the U16 players than the U15 players; U16 players considered the training and matches to be more difficult. In both teams, the perceived TL of the last training session of the week was significantly lower (Effect sizes = large-very large) than the other sessions. Although substantial negative associations (r = 0.52-0.78) were detected between the changes in physical fitness performance and the accumulated volume, sum of PEs and perceived TL in the U15 players, these associations were unclear in the U16 players. The basketball coaches-periodized training goals are to attain the highest session perceived TLs in the middle of the week and to reduce it considerably in the last training session. The U16 and U15 players accumulated perceived TL in different ways. Although the practice volume was similar in both teams, the older players consider the sessions more difficult. The relationship between the perceived TL and the changes in physical fitness performance varied between teams. Based on our findings, we propose that the PE-based dose-response model should be applied with caution in young female basketball players.