Peak Match Demands in Young Basketball Players: Approach and Applications

Effects of small-sided games training programs on physiological and physical adaptations of youth basketball players: A systematic review

The primary objective of this study was to systematically investigate the physiological and physical fitness adaptations resulting from small-sided games (SSGs) training programs in basketball players competing at youth competitive levels, as compared to other training approaches and/or control groups. To achieve this, we conducted a literature search on PubMed, Scopus, SPORTDiscus, and Web of Science, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. From the initial 626 studies retrieved, five were considered eligible for the current study. Among the five included articles, four conducted comparisons between the effects of SSGs and running-based high-intensity interval training. Regarding this, the four studies revealed a significant improvement in the final velocity during the 30-15 Intermittent Fitness Test, ranging from 4.07% to 7.29% following SSG-based interventions. This improvement was not significantly different from the comparator group. Additionally, two studies indicated that the SSGs group showed a significant advantage in change-of-direction time, with improvements ranging from -2.11% to 6.69% after interventions, and these results were not significantly different from the comparator group. However, the effects on repeated sprint ability yielded contradictory findings; two studies reported significant improvements ranging from -5.00% to -2.16%, while two others did not show significant effects following SSGs-based interventions. Similarly, in the linear sprint, the results of SSGs-based interventions were inconsistent. In summary, based on the available research, it can be concluded that SSG-based training is effective in significantly enhancing aerobic performance and change of direction, comparable to alternative approaches. However, the effects on repeated sprint ability and sprint performance are not consistently demonstrated.

A Narrative Review of the Most Demanding Scenarios in Basketball: Current Trends and Future Directions

Since the analysis of most demanding scenarios (MDS) in basketball has improved the practical knowledge about match demands and possible impacts for the training process, it seems important to summarize the scientific evidence providing useful information and future directions related to MDS. This review assesses the results reflected in the available literature about the MDS in basketball, synthesizing and discussing data from scientific papers, and then providing relevant insights about terminology, sex and sample size, competition category, workload variables recorded, technology used, method of calculation, time windows analyzed, and activities evaluated related to MDS. Therefore, the present narrative review would be of practical use for coaches, scientists, athletes as well as strength and conditioning trainers exploring the current trends and future directions related to MDS in basketball.

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.

MONITORIZACIÓN DE UN MICROCICLO COMPETITIVO EN BALONCESTO FEMENINO PROFESIONAL MEDIANTE DISPOSITIVOS INERCIALES

La implementación de estrategias efectivas de control de carga en el entrenamiento es primordial para mejorar el rendimiento. El objetivo fue caracterizar las demandas soportadas durante un microciclo competitivo de un equipo profesional de baloncesto femenino y su interacción con la competición. Diez jugadoras se equiparon con un dispositivo inercial y una banda de frecuencia cardíaca. Se analizó la carga soportada por las jugadoras durante el entrenamiento y la competición mediante variables de Carga Externa: (i) Distancia recorrida, (ii) Distancia recorrida a alta intensidad, (iii) Playerload, (iv) Saltos, (v) Aceleraciones y Deceleraciones, y (vi) Velocidad máxima y media; y variables de Carga Interna: (i) Frecuencia cardíaca media y máxima, (ii) Zonas de % Frecuencia Cardíaca Máxima. Se analizaron diferencias entre el entrenamiento y la competición mediante un análisis ANOVA, observando que la competición fue la condición más exigente en todas las variables estudiadas a excepción de los saltos por minuto.

Multidisciplinary Neuromuscular and Endurance Interventions on Youth Basketball Players: A Systematic Review with Meta-Analysis and Meta-Regression

The main aims of this systematic review with meta-analysis and meta-regression were to describe the effect of multidisciplinary neuromuscular and endurance interventions, including plyometric training, mixed strength and conditioning, HIIT basketball programs and repeated sprint training on youth basketball players considering age, competitive level, gender and the type of the intervention performed to explore a predictive model through a meta-regression analysis. A structured search was conducted following PRISMA guidelines and PICOS model in Medline (PubMed), Web of Science (WOS) and Cochrane databases. Groups of experiments were created according to neuromuscular power (vertical; NPV and horizontal; NPH) and endurance (E). Meta-analysis and sub-groups analysis were performed using a random effect model and pooled standardized mean differences (SMD). A random effects meta-regression was performed regressing SMD for the different sub-groups against percentage change for NPV and NPH. There was a significant positive overall effect of the multidisciplinary interventions on NPV, NPH and E. Sub-groups analysis indicate differences in the effects of the interventions on NPV and NPH considering age, gender, competitive level and the type of the intervention used. Considering the current data available, the meta-regression analysis suggests a good predictability of U-16 and plyometric training on jump performance. Besides, male and elite level youth basketball players had a good predictability on multidirectional speed and agility performance.

The Distribution of Match Physical Activities Relative to the Most Demanding Scenarios in Professional Basketball Players

The purpose of this study was to examine the distribution of physical activities relative to the most demanding scenarios across playing positions during official basketball match-play. Twelve professional basketball players were monitored during twelve matches using a local positioning system. Peak physical demands were measured via total distance covered, distance covered >18 km·h^-1, and the number of accelerations and decelerations >3 m·s^-2 captured over 30- and 60-s rolling averages. The results showed that players were exposed to more than one high-demanding scenario in all variables and time epochs examined. Additionally, total distance covered presented the greatest number of moderate-demanding scenarios (40-80% of most demanding scenarios), whereas distance covered >18 km·h^-1, and accelerations and decelerations >3 m·s^-2 presented the greatest proportion of low-demanding scenarios (<40% of most demanding scenarios). Regarding positional differences, backcourt players generally experienced a higher number of scenarios than frontcourt players in most variables, especially in total distance covered. For this variable, scenarios between 20 and 70% of most demanding scenarios during the 30-s epoch (p < 0.001; ES = 0.420.78), and scenarios between 50 and 90% of most demanding scenarios during the 60-s epoch (p < 0.001; ES = 0.400.64) showed significant differences between backcourt and frontcourt players. Our data suggest that match physical activities are position-dependent and variable-dependent. In addition, peak physical demands appear to be repeated during basketball competition. These results may be considered by practitioners to complement average values and most demanding scenarios when prescribing individualized training programs to optimize team performance.

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.

Quantifying Training and Game Demands of a National Basketball Association Season

Purpose: There are currently no data describing combined practice and game load demands throughout a National Basketball Association (NBA) season. The primary objective of this study was to integrate external load data garnered from all on-court activity throughout an NBA season, according to different activity and player characteristics. Methods: Data from 14 professional male basketball players (mean ± SD; age, 27.3 ± 4.8 years; height, 201.0 ± 7.2 cm; body mass, 104.9 ± 10.6 kg) playing for the same club during the 2017-2018 NBA season were retrospectively analyzed. Game and training data were integrated to create a consolidated external load measure, which was termed integrated load. Players were categorized by years of NBA experience (1-2y, 3-5y, 6-9y, and 10 + y), position (frontcourt and backcourt), and playing rotation status (starter, rotation, and bench). Results: Total weekly duration was significantly different (p < 0.001) between years of NBA playing experience, with duration highest in 3-5 year players, compared with 6-9 (d = 0.46) and 10+ (d = 0.78) year players. Starters experienced the highest integrated load, compared with bench (d = 0.77) players. There were no significant differences in integrated load or duration between positions. Conclusion: This is the first study to describe the seasonal training loads of NBA players for an entire season and shows that a most training load is accumulated in non-game activities. This study highlights the need for integrated and unobtrusive training load monitoring, with engagement of all stakeholders to develop well-informed individualized training prescription to optimize preparation of NBA players.

Higher Playing Times Accumulated Across Entire Games and Prior to Intense Passages Reduce the Peak Demands Reached by Elite, Junior, Male Basketball Players

The aim of this study was to analyze the effects of different factors on the external peak demands (PD) encountered by elite, junior, male basketball players in games, including the (1) total playing time during games and (2) playing time accumulated directly prior to each PD episode. Workload variables included the PD for total distance, distance covered in different intensity zones, accelerations >2 m·s-2 (ACC), decelerations <-2 m·s-2 (DEC), and PlayerLoad. PD were calculated across different sample durations for each variable. Linear mixed models were used to identify differences in PD between groups based on playing times. PD for total distance (5-min window), high-speed running (>18 km·h-1) distance (2-min window), and ACC (30-s, 45-s, 1-min, 2-min, and 5-min windows) were significantly (p < .05) higher for players who completed lower total playing times (16.6 ± 2.4 min) than players who completed higher total playing times (25.0 ± 3.4 min). The PD for total distance (30-s, 45-s, 1-min, and 2-min windows), high-speed running distance (30-s and 5-min windows), and PlayerLoad (1-min and 2-min windows) were significantly (p < .05) higher for players who accumulated lower playing times before each PD episode than players who accumulated higher playing times before each PD episode. Players who undertake less playing time overall and prior to each PD episode can reach higher peak external loads aggregated across varied time windows. These findings can inform tactical coaching decisions during games for high external loads to be accomplished during important passages of play.

Specific Absolute Velocity Thresholds during Male Basketball Games Using Local Positional System; Differences between Age Categories

The aim of this study was (I) to establish absolute specific velocity thresholds during basketball games using local positional system (LPS) and (II) to compare the speed profiles between various levels of competitions. The variables recorded were total distance (TD); meters per minute (m·min); real time (min); maximum speed (Km h−1), distance (m), percentage distance, and percentage duration invested in four speed zones (standing–walking; jogging; running; and high-speed running). Mean and standard deviation (±SD) were calculated, and a separate one-way analysis of variance was undertaken to identify differences between competitions. TD (3188.84 ± 808.37 m) is covered by standing–walking (43.51%), jogging (36.58%), running (14.68%), and sprinting (5.23%) activities. Overall, 75.22% of the time is invested standing–walking, jogging (18.43%), running (4.77%), and sprinting (1.89%). M·min (large effect size), % duration zone 2 (moderate effect size); distance zone 4 (large effect size), and % distance zone 4 (very large effect size) are significantly higher during junior than senior. However, % distance zone 1 (large effect size) and % duration zone 1 (large effect size) were largely higher during senior competition. The findings of this study reveal that most of the distance and play time is spent during walking and standing activities. In addition, the proportion of time spent at elevated intensities is higher during junior than in senior competition.

Not All About the Effort? A Comparison of Playing Intensities During Winning and Losing Game Quarters in Basketball

PURPOSE

To compare peak and average intensities encountered during winning and losing game quarters in basketball players.

METHODS

Eight semiprofessional male basketball players (age = 23.1 [3.8] y) were monitored during all games (N = 18) over 1 competitive season. The average intensities attained in each quarter were determined using microsensors and heart-rate monitors to derive relative values (per minute) for the following variables: PlayerLoad, frequency of high-intensity and total accelerations, decelerations, changes of direction, jumps, and total inertial movement analysis events combined, as well as modified summated-heart-rate-zones workload. The peak intensities reached in each quarter were determined using microsensors and reported as PlayerLoad per minute over 15-second, 30-second, 1-minute, 2-minute, 3-minute, 4-minute, and 5-minute sample durations. Linear mixed models and effect sizes were used to compare intensity variables between winning and losing game quarters.

RESULTS

Nonsignificant (P > .05), unclear-small differences were evident between winning and losing game quarters in all variables.

CONCLUSIONS

During winning and losing game quarters, peak and average intensities were similar. Consequently, factors other than the intensity of effort applied during games may underpin team success in individual game quarters and therefore warrant further investigation.

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.

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.

Accelerometry as a method for external workload monitoring in invasion team sports. A systematic review

Accelerometry is a recent method used to quantify workload in team sports. A rapidly increasing number of studies supports the practical implementation of accelerometry monitoring to regulate and optimize training schemes. Therefore, the purposes of this study were: (1) to reflect the current state of knowledge about accelerometry as a method of workload monitoring in invasion team sports according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and (2) to conclude recommendations for application and scientific investigations. The Web of Science, PubMed and Scopus databases were searched for relevant published studies according to the following keywords: "accelerometry" or "accelerometer" or "microtechnology" or "inertial devices", and "load" or "workload", and "sport". Of the 1383 studies initially identified, 118 were selected for a full review. The main results indicate that the most frequent findings were (i) devices' body location: scapulae; (b) devices brand: Catapult Sports; (iii) variables: PlayerLoadTM and its variations; (iv) sports: rugby, Australian football, soccer and basketball; (v) sex: male; (vi) competition level: professional and elite; and (vii) context: separate training or competition. A great number of variables and devices from various companies make the comparability between findings difficult; unification is required. Although the most common location is at scapulae because of its optimal signal reception for time-motion analysis, new methods for multi-location skills and locomotion assessment without losing tracking accuracy should be developed.