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Using Microsensor Technology to Quantify Match Demands in Collegiate Women's Volleyball
Travis G Vlantes1, Tucker Readdy
1Intercollegiate Athletics, Kinesiology and Health, University of Wyoming, Laramie, Wyoming.
Journal of Strength and Conditioning Research
|September 1, 2017
Summary
This study quantified volleyball match demands using microsensor technology and session rating of perceived exertion (S-RPE). Positional differences in player load and jumps were significant, informing tailored training programs.
Area of Science:
- Sports Science
- Biomechanics
- Exercise Physiology
Background:
- Understanding the physical demands of collegiate women's volleyball is crucial for optimizing performance and preventing injuries.
- Previous research has often relied on subjective measures, necessitating objective quantification of internal and external loads.
Purpose of the Study:
- To quantify the internal and external load demands of NCAA Division I women's volleyball competitions.
- To investigate the relationship between objective microsensor data and subjective session rating of perceived exertion (S-RPE).
- To identify position-specific load differences to inform targeted training.
Main Methods:
- Eleven collegiate volleyball players were equipped with microsensor technology (Optimeye S5) during 15 matches.
- Data collected included player load (PL), high impact PL, percentage of HI PL, explosive efforts (EEs), and jumps.
- Session rating of perceived exertion (S-RPE) was recorded post-match.
Main Results:
- Setters exhibited the highest mean player load and jump counts.
- Playing 4 or 5 sets significantly increased player load compared to 3 sets.
- Significant positional differences (p < 0.01) were found in % HI PL and jumps, with large effect sizes.
- Defensive specialists reported the highest mean S-RPE values.
Conclusions:
- Microsensor technology effectively quantifies internal and external load demands in women's volleyball.
- Significant positional variations in match demands necessitate position-specific training.
- This data enables coaches to design targeted programs for peak performance and reduced injury risk.

