The Effect of Simulation-based Training on Athletic Performances among Female Basketball Players

Abstract

Background: The effectiveness of simulation-based training has been examined in various sports. However, considering the effect of gender and sport on training, it would be interesting to evaluate simulation-based training in female basketball. Objective: The purpose of the study was to examine the effect of simulation-based training on physical fitness and performance indices in female basketball players. Methods: Sixteen female semi-professional basketball players were randomly assigned to experimental (n=8; age, 25±2 years; weight, 62±9 kg; height, 167±8 cm) or control (n=8; age, 24±1 years; weight, 57±9 kg; height, 170±8 cm) groups. The experimental group participated in a six week basketball simulation training program including running with different speeds (jogging to sprinting), agility, jumping, and shuffling. Both groups performed the Cooper 12 min run, line drill, an adjusted T-test, 20 ms print, the Sargent vertical jump and basketball exercise simulation test before and after six weeks of the study period. Control and experimental groups performed typical basketball training, three times weekly. The overall training volume was similar for both groups. Results: The perceived exertion was higher in the simulation-based training than control (p<0.05) group. The findings of this study indicated a significant increase in VO2 max (p=0.001), anaerobic power (p=0.009), explosive leg strength (p=0.036), and total distance covered in basketball exercise simulation test (p=0.001) and decrease of the meantime of one round of basketball exercise simulation test (p=0.001) in the simulation training compared to the control group. Conclusion: Generally incorporation of the simulation-based training in conditioning programs is recommended for improving aerobic, anaerobic and leg explosive strength of basketball players.

The reliability and discriminant validity of physical, technical, and perceptual-physiological measures during a game-specific basketball activity simulation protocol

“…Accordingly, the new simulation protocol may provide researchers and practitioners with more holistic information compared to classic physical fitness tests such as jump, sprint, or change-of-direction assessments that are restricted to a specific form of activity. Furthermore, the simulation protocol could also be applied as a training tool ( Javanmardi et al, 2021 ) in practice. In turn, we also provide useful reliability data for physical, technical, and perceptual-physiological variables measured during the simulation protocol to inform end-users on the inherent measurement error that may be encountered.…”

“…To date, various basketball-specific simulation protocols have been developed ( Kostopoulos et al, 2004 ; Afman et al, 2014 ); however, the Basketball Exercise Simulation Test has been the most popular basketball-specific simulation protocol adopted within the literature ( Scanlan et al, 2012 , 2014 , 2017a , b , 2018 ; Staunton et al, 2017 ; Delextrat et al, 2018 ; Latzel et al, 2018 ; Hovsepian et al, 2021 ; Javanmardi et al, 2021 ; Bourdas et al, 2024 ). This test replicates the intermittent activity profile and distances measured during games in professional, male basketball players competing in the Australian National Basketball League ( Scanlan et al, 2014 ).…”

“…This test replicates the intermittent activity profile and distances measured during games in professional, male basketball players competing in the Australian National Basketball League ( Scanlan et al, 2014 ). In turn, it has been used to comprehensively quantify the demands of game-specific basketball activity ( Latzel et al, 2018 ; Scanlan et al, 2018 ), assess the efficacy of nutritional ( Delextrat et al, 2018 ) and training interventions ( Hovsepian et al, 2021 ), as a training strategy ( Javanmardi et al, 2021 ), as a fatiguing protocol ( Bourdas et al, 2024 ), and to assess monitoring approaches ( Staunton et al, 2017 ; Scanlan et al, 2017a , b ). The original version of the test was developed to simulate the maximum demands likely encountered during games (i.e., 48 min across 4 × 12-min quarters of live playing time) with reported reliability statistics ( Scanlan et al, 2014 ) and various types of supported validity ( Scanlan et al, 2012 , 2014 ).…”