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

Effectiveness of an Individualized Training Based on Dynamic Strength Index on Sprinting, Jumping and Change of Direction Performance in Basketball Players: A Randomized Controlled Trial

The dynamic strength index (DSI) is calculated as the ratio between countermovement jump (CMJ) peak force and isometric mid-thigh pull (IMTP) peak force and is said to inform whether ballistic or strength training is warranted for a given athlete. This study assessed the impact of an individualized in-season resistance training program, guided by DSI on basketball players' physical performance. Forty-three elite players (19.4 ± 2.9 years; 1.97 ± 0.08 cm; 89.1 ± 9.5 kg) were divided into an intervention group (IG) (27 players) and a control group (CG) (16 players). The IG was further split based on DSI into a ballistic group (DSI ≤ 0.90, 11 players) and a strength group (DSI > 0.90, 16 players). Over five weeks, participants underwent two weekly resistance sessions, with the IG following a DSI-based program and the CG a standard program. Performance was measured pre- and post-intervention through 20-m sprints, 505 change of direction test, CMJ, and IMTP. There were statistically significant improvements in the IG, notably in sprint times (η2 = 0.12-0.21, p < 0.05) and 505 test (η2 = 0.15-0.16, p < 0.05), predominantly in the strength group. The CG's performance was either unchanged or declined for different variables. Our results suggest that DSI-guided training effectively enhances basketball players' physical performance within a competitive season.

Dose-Response Relationship for External Workload and Neuromsuclar Performance Over a Female, Collegiate, Basketball Season

ABSTRACT

Philipp, NM, Cabarkapa, D, Blackburn, SD, and Fry, AC. Dose-response relationship for external workload and neuromsuclar performance over a female, collegiate, basketball season. J Strength Cond Res 38(5): e253-e263, 2024-The aim of this study was to investigate the relationship between external workload exposure and changes in countermovement jump force-time characteristics over the course of an entire basketball season, in a sample of National Collegiate Athletic Association Division I, female, basketball players. Data for 12 players were retrospectively analyzed, with external workload being quantified by means of an exponentially weighted, acute, and chronic workload, as well as an acute:chronic workload ratio derived from an inertial measurement unit-based system worn by athletes for all practices and games during the regular season. Countermovement jumps were performed on a total of 26 test days over the span of the in-season competitive period. To statistically analyze these relationships, and to account for multiple observations of the same athletes in a data set, linear mixed-effects models with athlete identity (ID) intercept as the random effect were used. Study findings suggested that associations between external workload exposure and respective force-time characteristics after controlling for the random effect of athlete ID were dependent on the specific metric or metric subgroup used, as well as the type of workload exposure (e.g., acute vs. chronic). Force-time signatures from the braking phase (e.g., average braking force) seemed to be particularly associated with higher degrees of acute workload exposure, whereas strategy-based metrics such as countermovement depth showed significant associations with chronic workload exposure. Furthermore, model results suggested the importance of analyzing neuromuscular responses to external workload on an individual basis, rather than across an entire team. Findings might help practitioners in their selection process related to metrics of interest in monitoring neuromuscular fatigue and readiness.

The Effects of Workload Difference Between Limbs in Plyometric and Strength Exercises in Reducing Asymmetry in Change of Direction Ability During Basketball Season

ABSTRACT

Ujaković, F, and Šarabon, N. The effects of workload difference between limbs in plyometric and strength exercises in reducing asymmetry in change of direction ability during basketball season. J Strength Cond Res 37(11): 2282-2288, 2023-The topic of interlimb asymmetries has recently been extensively investigated; despite that, intervention for purpose of reducing them have been narrowly examined. The present study investigated the effects of maximal strength and plyometric resistance training program with 3:1 workload ratio (nondominant to dominant side) on change of direction deficit (CoDdef) asymmetry during the basketball season. Thirty-six highly trained male basketball players (19.3 ± 4.9 years) from different age categories (U-17, U-19, and senior) were divided into 2 groups: the control group ( n = 18) and the intervention group ( n = 18). The intervention group performed once-a-week training that consisted of strength (Bulgarian split squats) and jumping (single-leg countermovement jumps [SLCMJs]) part in which nondominant-to-dominant workload ratio was 3:1 during the 8-week period. Preintervention and postintervention testing included single-leg isometric squat, SLCMJ, 10-m sprint, and 505 test. Analysis of covariance results showed a statistically significant difference with large effect size ( p < 0.05; η2 = 0.26) when preintervention asymmetry was included as covariate. Post hoc analysis showed a statistically significant decrease in mean CoDdef asymmetry between preintervention (11.88%) and postintervention (4.47%) testing ( p < 0.01, effect size [ES] = -1.37). Isometric squat strength increased on nondominant side in the intervention group ( p < 0.05; ES = 0.77). No other performance or asymmetry variable showed significant change. In conclusion, a 3:1 workload of nonspecific movement task in favor of nondominant limb is an effective training strategy to reduce CoDdef asymmetry during basketball season.

Progressing On-Court Rehabilitation After Injury: The Control-Chaos Continuum Adapted to Basketball

BACKGROUND: Sport-specific training is an integral component of returning to sport following injury. Frameworks designed to guide sport-specific rehabilitation need to integrate and adapt to the specific context of elite sport. The control-chaos continuum (CCC) is a flexible framework originally designed for on-pitch rehabilitation in elite football (soccer). The concepts underpinning the CCC transfer to other elite sport rehabilitation environments. CLINICAL QUESTION: How can practitioners and clinicians transfer the CCC to elite basketball, to support planning and return to sport? On-court rehabilitation is a critical sport-specific rehabilitation component of return to sport, yet there are no frameworks to guide practitioners when planning and delivering on-court rehabilitation. KEY RESULTS: Based on our experience working in the National Basketball Association, we report how the CCC framework can apply to elite basketball. We focus on the design and delivery of progressive training in the presence of injury in this basketball-specific edition of the CCC. Given the challenges when quantifying "load" in basketball, we encourage practitioners and clinicians to consider the qualitative aspects of performance such as skill, sport-specific movement, contact, and decision making. CLINICAL APPLICATION: The 5-phase framework describes training progression from high control, a return to on-court running, to high chaos, a return to "live" unrestricted basketball. The model can be adapted to both short- and long-term injuries based on injury and progression criteria. Strength and power "diagnostics" can be strategically implemented to enhance decision making throughout the return to sport continuum. J Orthop Sports Phys Ther 2023;53(9):1-12. Epub: 9 August 2023. doi:10.2519/jospt.2023.11981.

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.

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.

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.

Match Day-1 Reactive Strength Index and In-Game Peak Speed in Collegiate Division I Basketball

Basketball is a game of repeated jumps and sprints. The objective of this study was to examine whether repeated jump assessments the day prior to competition (MD-1) could discriminate between fast and slow in-game performances the following day. Seven NCAA Division I Basketball athletes (4 guards and 3 forwards; 20 ± 1.2 years, 1.95 ± 0.09 m, and 94 ± 15 kg) performed a repeated-hop test on a force platform before and after each practice MD-1 to assess Reactive Strength Index (RSI) and Jump Height (JH). Peak speed was recorded during games via spatial tracking cameras. A median split analysis classified performance into FAST and SLOW relative to individual in-game peak speed. Paired T-tests were performed to assess post- to pre-practices differences. An independent sample T-test was used to assess the differences between FAST and SLOW performances. Cohen’s d effect sizes (ES) were calculated to determine the magnitude of the differences. Statistical significance was set for p ≤ 0.05. Post-practice RSI and JH were significantly higher than pre-training values prior to the FAST but not the SLOW in-game performances. A significant difference was found for MD-1 RSI when comparing FAST and SLOW conditions (p = 0.01; ES = 0.62). No significant between-group differences were obtained in JH (p = 0.07; ES = 0.45). These findings could have implications on the facilitation of reactive strength qualities in conjunction with match-play. Practitioners should evaluate the placement of stimuli to potentiate athlete readiness for competition.