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

Determination of change of direction deficit thresholds across a spectrum of angles in basketball players

Change of direction deficit (CODD) offers valuable insights into a player's balance between linear and multidirectional speed. However, there are still no established reference values for CODD. The objectives of this study were to determine CODD thresholds for various change of direction angles in basketball players according to gender and analyse the relationships between CODD and execution time in speed tests. One hundred and thirty basketball players (46% female; age: 23.7 ± 5.29 years; height: 189.1 ± 11.1 cm; body mass: 84.3 ± 15.7 kg) undertook 10-m linear and change of direction speed test at 45º, 90º and 180º. A k-means cluster analysis was conducted to standardise CODD thresholds and a one-way analysis of variance to identify the differences between clusters. The results revealed angulation-specific CODD thresholds, ranging from 3% to 8%, 17% to 25% and 43% to 51% for 45º, 90º and 180º cutting angles, respectively for the pooled sample. Furthermore, differences inter-clusters (p < 0.05) were observed for execution time at all cutting angles for both genders. Therefore, strength and conditioning coaches are encouraged to assess CODD as a highly valid variable for evaluating change of direction performance and to use current CODD thresholds to tailor training programmes according to each athlete's needs.

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.

Female basketball game performance is influenced by menstrual cycle phase, age, perceived demands and game-related contextual factors

This study evaluated the influence of physical and perceived game demands, menstrual cycle phase, perceived recovery, individual and game-related contextual factors on competitive performance in professional, female basketball players.11 professional female players (age: 20.6 ± 2.7 years) were monitored for game-related statistics (Performance Index Rating, PIR; rebounds, REB; effective field goal %, eFG%; turnovers, TO), objective (PlayerLoad per minute, PL·min-1) and subjective (RPE) game loads, pre-game perceived recovery (Total Quality Recovery, TQRpre), menstrual phase (follicular; luteal) and game-related contextual factors (game location; game outcome; score differential; opponent level) during 12 official games. Separate linear mixed models were used to evaluate the influence of RPE, PL·min-1, TQRpre, menstrual phase, contextual factors, and individual characteristics (age; playing position) on game-related statistics.Higher PIR and eFG% were found for older players and those who reported higher RPE (all p < 0.05). Higher age also led to less TO (p = 0.042). eFG% was higher when players reported higher TQRpre ;(p = 0.010). Better shooting (eFG%) and rebounding (REB) performances were found during the follicular menstrual phase (p < 0.05). More REB were collected in won games (p = 0.002).This study suggests that the co-influences of perceptual, menstrual-related, individual and game-related contextual factors should be considered to optimise female basketball players' performance.

A new database of the analysis of the physiological needs in amateur female basketball during official matches

The PHYAFB database is a valuable resource for studying the physiological demands of female amateur basketball players during high-stress official games. It contains heart rate data from ten players aged 18 to 26, collected during ten crucial relegation phase matches, with 348,232 HR samples in CSV and Excel formats for easy access and analysis. The database includes Python source code for initial examination. The primary aim of the PHYAFB database is to provide a useful reference for other teams facing similar situations. Furthermore, the database represents a unique and valuable resource for sports scientists, coaches, and trainers seeking to comprehend the physiological demands of female basketball players during official competitions. Through the analysis of heart rate data, coaches and trainers can identify the intensity and duration of physical activity during games, enabling the development of more effective training programs. Additionally, the database can be used to compare the physiological demands placed on male and female basketball players or to investigate the impact of different game strategies on player performance.

The discriminative, criterion, and longitudinal validity of small-sided games to assess physical fitness in female basketball players

The validity of small-sided games (SSG) for assessing physical fitness was evaluated in 21 female basketball players from senior (n = 8), under-18 years (n = 6), and under-16 years (n = 7) age categories. Players underwent fitness testing (countermovement jump [CMJ], agility T-test, repeated-sprint ability (RSA) test, and Yo-Yo Intermittent Recovery Test [YYIRT1]) and 3vs3-SSG before and after a 6-week preseason. Player demands were monitored during SSG using local positioning system and heart rate technology. Regarding discriminative validity, senior players produced better CMJ, agility T-test, and YYIRT1 performance (p  < 0.05, effect size [ES] = 1.72-2.25), and more distance and PlayerLoad (p  < 0.05, ES = 1.53-2.47) during SSG than under-18 players following the preseason. For criterion validity, total distance and distance completing high-intensity decelerations during SSG were significantly (p  < 0.05) correlated with CMJ (r = 0.44-0.66), YYIRT1 (r = 0.43-0.63), agility T-test (total distance only, r=-0.51), and RSA test performance (r=-0.49 to -0.52) among all players combined following the preseason. Regarding longitudinal validity, significantly better agility T-test and YYIRT1 performance (p ≤ 0.001, ES = 0.88-0.93) alongside lower heart rate during SSG (p = 0.001, ES = 0.88) were evident for all players combined following the preseason. These results partially support the validity of 3vs3-SSG to assess physical fitness in female basketball players.

A comparative study of Chinese women 3 × 3 basketball players exercise load in Tokyo Olympic preparation cycle

Objective: The aim of this study was to compare the variances in-game loads exhibited by Chinese women's 3 × 3 basketball team across different stages of the preparation cycle for the Tokyo Olympic Games, and to summarize the fundamental regulations governing Chinese women's 3 × 3 basketball training and games, in order to establish a theoretical research foundation for the team's new preparation cycle. Methods: This study measured load-related data during the preparation and main competition periods of the 2019-2021 Tokyo Olympics, from April to August 2019 and from April to June 2021. The aim was to compare the changes and differences in a load of competition during different stages and to explore patterns of load changes during the preparation period. This study used wearable devices authorized by FIFA and NBA, along with the Catapult GPS performance monitoring system from Australia (Catapult&Polar Team) as instruments for collecting sports load data. The OptimEye S5 device was worn around the athlete's neck to collect data prior to the game, while the Open Field™ system was utilized for data editing and report generation post-game. Results: Compared to the primary competition load during the 2019 preparation period, the 2021 preparation period exhibited significant increases and decreases (p < 0.05) in competition load, high-intensity load, the number of explosive moves, the number of high-intensity acceleration, several changes to the left and right, and the number of explosive jumps. During the 2021 preparation period, the mean heart rate, mean heart rate percentage, and mean speed of the race demonstrated significant decreases in comparison to the race during the 2019 preparation period (p < 0.05). Throughout the training period spanning from 2019 to 2021, no significant differences were observed in running distance and maximum speed (p > 0.05). Conclusion: The findings of this study reveal that the national training team has fostered positive adaptive changes in athletes, resulting in a significant enhancement in both load and sports performance science data during competition from 2019 to 2021.

The incidence rate of ACL injuries and ankle sprains in basketball players: A systematic review and meta-analysis

OBJECTIVE

To quantify the incidence rate of anterior cruciate ligament (ACL) injuries and ankle sprains according to player sex, playing level, and exposure setting (training vs. games) in basketball players.

METHODS

PubMed, MEDLINE, Google Scholar, and ScienceDirect were searched. Only studies reporting the number of ACL injuries and/or ankle sprains alongside the number of athlete-exposures (training sessions and/or games) in basketball players were included.

RESULTS

Thirty studies (17 reporting ACL injuries and 16 reporting ankle sprains) were included in the meta-analysis. Higher (p < 0.05) ACL injury incidence rates per 1000 athlete-exposures were recorded in females (female: 0.20 95% confidence intervals [0.16-0.25]; male: 0.07 [0.05-0.08]; female-to-male ratio: 3.33 [3.10-3.57]), in players competing at higher playing levels (amateur: 0.06 [0.04-0.09]; intermediate: 0.16 [0.13-0.20]; elite: 0.25 [0.14-0.64]), and in games (games: female, 0.27 [0.21-0.32]; male, 0.06 [0.03-0.08]; training: female, 0.03 [0.02-0.05]; male: 0.01 [0.00-0.02]; game-to-training ratio: 7.90 [4.88-12.91]). Higher (p < 0.05) ankle sprain incidence rates per 1000 athlete-exposures were observed in males (female: 0.82 [0.61-1.03]; male: 0.90 [0.61-1.19]; female-to-male ratio: 0.91 [0.83-0.99]), in players competing at higher playing levels (amateur: 0.54 [0.51-0.57]; intermediate: 1.12 [1.00-1.24]; elite: 1.87 [1.29-2.46]), and in games (games: 2.51 [1.85-3.16]; training: 0.80 [0.52-0.80]; game-to-training ratio: 2.77 [2.35-3.26]).

CONCLUSION

According to player sex, ACL injury incidence rate is higher in females, while ankle sprain incidence rate is greater in males. ACL injury and ankle sprain incidence rates are greater in players competing at higher playing levels and during games compared to training.