Isometric Strength Differences in the Athletic Shoulder Test in Female Volleyball Players




Abstract:
Volleyball is a sport that requires both lower- and upper-body power, particularly during explosive actions such as attacking and serving. Interestingly, while assessments like the countermovement jump are widely used to evaluate athletes’ neuromuscular performance, upper-body testing protocols remain less commonly implemented in this sport. In response to this gap, a fairly new upper-body test known as the Athletic Shoulder (ASH) test has begun to be incorporated into evaluations within this cohort, aiming to measure isometric shoulder strength across three positions: I (180°), Y (135°), and T (90°). The purpose of this study was to examine positional differences in isometric strength during the ASH test among elite female volleyball players. Thirteen professional athletes competing at the SuperLeague level performed three maximal isometric contractions in each position using a force plate system. Significant differences were observed across positions (p<0.001). Force output in the I position was significantly higher than both Y (p<0.001, g=1.793) and T (p<0.001, g=2.880), with Y also exceeding the T (p=0.015, g=1.439). These findings emphasize the importance of incorporating the ASH test into regular athlete monitoring protocols in volleyball, as they help coaches identify potential weaknesses, develop individualized training programs, and better understand athletes’ overall functional capacity.

CITATION:

IEEE format

D. Čabarkapa, V. Banković, N. Trunić, “Isometric Strength Differences in the Athletic Shoulder Test in Female Volleyball Players,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2025, pp. 481-486. doi:10.15308/Sinteza-2025-481-486

APA format

Čabarkapa, D., Banković, V., Trunić, N. (2025). Isometric Strength Differences in the Athletic Shoulder Test in Female Volleyball Players. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2025-481-486

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