Validation of Internal and External Load Metrics in NCAA D1 Women's Beach VolleyballShow full item record
Title | Validation of Internal and External Load Metrics in NCAA D1 Women's Beach Volleyball |
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Author | Tometz, Matthew James |
Date | 2020 |
Genre | Thesis |
Degree | Master of Science |
Abstract | The purpose of this study was to determine the validity of internal and external load metrics in NCAA D1 women’s beach volleyball. Participants included 13 NCAA D1 women’s beach volleyball players (age: 20.26 ± 1.41 years). A total of 578 data points were analyzed from 51 team training sessions including practice, games, and conditioning from the pre-season semester from August to Decemember (15 weeks). The participants wore Polar Team Pro heart rate monitors with GPS during each training session to assess internal and external loads. Participants completed a session-rating of perceived exertion (sRPE) questionnaire after every session. Daily environmental condition variables (ECV) were collected during team training sessions to identify potential confounding variables. Statistically significant relationships (p < 0.01) were found between TRIMP and sRPE Load (0.81), TRIMP and DC (0.78), and sRPE Load and DC (0.82). A regression model yielded sRPE Load could predict TRIMP with the equation: TRIMPTometz = 78.735 + (sRPE Load * 0.28); this equation predicts 65% of the variance of TRIMP. These findings support sRPE Load as a valid alternative to TRIMP when monitoring internal load in NCAA D1 women’s beach volleyball. Additionally, sRPE Load may be more practical and accessible for teams. Distance covered during training should be considered when periodizing and monitoring load because of its relationship with internal loads. ECV should be considered for the safety of the athletes but not for load monitoring. Primary insight into load monitoring provides an opportunity for practitioners to engage in interprofessional education and collaborative practice. |
Link | https://repository.tcu.edu/handle/116099117/39884 |
Department | Kinesiology |
Advisor | Jevas, Stephanie A. |
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- Masters Theses [4182]
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