Establishing a duration standard for the calculation of session rating of perceived exertion in NCAA division I men`s soccer
Objectives: The purpose of this study was to determine the best predictor of training and/or match load using session RPE. Design and Methods: 20 NCAA DI male soccer players participated in the study during the 2014 and 2015 competitive seasons. Players completed 15.20 ± 1.05 matches for a total of 304 individual data points and 29.90 ± 1.89. training sessions for a total of 598 individual data points. GPS variables (total distance, High-intensity running distance, and Player load) were analyzed with session RPE using Pearson product-moment correlations. To evaluate various methods of session RPE, "match duration" was recorded using eight different definitions: total match duration including warm-up and half-time, total match duration and warm-up, total match duration and half-time, total match duration only, minutes played including warm-up and half-time, minutes played and warm-up, minutes played and half-time, and minutes played only. A one-way ANOVA with repeated measures was used to determine if differences existed between the eight session RPE calculations. Results: Results from the ANOVA showed that all session RPE measures were significantly different from one another (P < 0.05). Very large correlations were reported between session RPE calculated using minutes played and total distance (0.81), while session RPE calculated using match duration showed less magnitude (0.57). Conclusions: Minutes played should be used to calculate session RPE as it was found to most closely reflect the actual workloads incurred during competitive matches.
© Copyright 2017 Journal of Trainology. Toyo Gakuen University. All rights reserved.
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| Notations: | sport games |
| Published in: | Journal of Trainology |
| Language: | English |
| Published: |
2017
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| Online Access: | https://doi.org/10.17338/trainology.6.1_26 |
| Volume: | 6 |
| Issue: | 1 |
| Pages: | 36-30 |
| Document types: | article |
| Level: | advanced |