The Effect of Differential Repeated Sprint Training on Physical Performance in Female Basketball Players: A Pilot Study.

This pilot study aimed to determine the effects of differential learning in sprint running with and without changes of direction (COD) on physical performance parameters in female basketball players and to determine the feasibility of the training protocol. Nine female basketball players completed 4 weeks of repeated sprint training (RST) with (COD, n = 4) or without (NCOD, n = 5) changes of direction. A battery of sprints (0-10 and 0-25 m), vertical jumps (counter movement jump (CMJ), drop jump, and single-leg CMJs), and COD tests were conducted before and after intervention. NCOD completed two sets of ten sprints of 20 m, whereas COD performed 20 m sprints with a 180 degree turn at 10 m, returning to the starting line. Before each sprint, participants were instructed to provide different fluctuations (i.e., differential learning) in terms of varying the sprint. Both groups had 30 s of passive recovery between two sprints and 3 min between sets. A significant effect of time for the 0-10 m sprint, CMJ, and single leg-CMJ asymmetries were observed. Adding "erroneous" fluctuation during RST seems to be a suitable and feasible strategy for coaches to enhance physical performance in young female basketball players. However, further studies including larger samples and controlled designs are recommended to strengthen present findings.

Want to Impact Physical, Technical, and Tactical Performance during Basketball Small-Sided Games in Youth Athletes? Try Differential Learning Beforehand.

This study aimed to analyze the acute effect of small-sided games, based on differential learning, on the physical, technical, and positioning performance of young basketball players. Eight basketball players under 13 (U13) participated in this study. A total of eight sessions involving half-court small-sided games (4 sets × 3 min + 1 min of passive recovery) under randomly different numerical relations were performed. Before each trial, players were verbally instructed to perform the drill in one of the conditions, in random order. Pre- and post-tests were performed in the 4v4 half-court format, in each session. External load and positional data were collected via a WIMU PRO local positioning system. Individual heart rate monitoring was used to assess the internal load. Game videos also collected notational data. The results revealed that, after the intervention, the players significantly decreased the total distance covered, the peak acceleration, average speed, training impulse, and the spatial exploration index; conversely, the results confirmed an increase in the number of dribbles. Small-sided games under randomly different numerical relations imposed acute effects in distinct variables during 4v4 half-court games. However, further studies are warranted, including longer interventions and parallel-group designs, to confirm if the training-induced effects of this method are significantly better compared to other approaches.

The Effect of Variability of Practice at Execution Redundancy Level in Skilled and Novice Basketball Players.

We investigated the effect of practice variability through execution redundancy in skilled and novice basketball players on free throw skills. Twelve skilled basketball players and 12 novices (mean age = 25.4 years, SD = 4.3) were divided into four groups (skilled constant, skilled variable, novice constant, and novice variable). After a pretest, participants practiced free throw action. The variable groups threw the ball over an obstacle of varying heights on each trial in random order, whereas the obstacle's height was fixed for the constant groups. After 7 and 14 consecutive days of practice, participants performed two posttests with constant and variable distances from the basket. The results showed that practicing different solutions of a task did not affect the performance of skilled players but had an immediate negative effect on the performance of novice players. Learning a complex task is the result of learning task-related parameters, and practice variability can create a mismatch between task difficulty and new learner skill levels.