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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. [ABSTRACT FROM AUTHOR]

Lower-body strength and power are commonly measured performance qualities across a number of sports. In recent years, more attention has been given to relationships, primarily between lower-body strength and linear speed performance. While still limited, evidence is in agreement that lower-body strength positively contributes to linear speed performance. However, what is less well understood is if there comes a point in an athlete's development, at which, further working on increasing maximal strength may not fully compliment additional gains in speed performance. Within this study, authors aimed to provide practitioners with lower-body strength and power thresholds that can discriminate between slow and fast performers, within a group of collegiate American football players. The sample was further divided into a high-body and low-body weight group, and authors hypothesized that by using logistic regression, supplemented with receiver operator curve analyses, optimal cut-off points (i.e., relative lower-body strength thresholds) that are able to significantly discriminate between slow and fast linear speed performers may be identified. Findings indicate that optimal cut-off scores differed between the groups of athletes, as well as the lower body strength and power tests. All models were able to significantly distinguish between slower and faster performers, and area under the curve values ranged from 0.695 to 0.903. Although thresholds will likely vary based on factors such as sex, training age, and sport, findings from this investigation may be used to benchmark athletes and to further individualize training aimed at improving linear speed performance. [ABSTRACT FROM AUTHOR]