Finding the signal in the noise-interday reliability and seasonal sensitivity of 84 countermovement jump variables in professional basketball players
This study examined the measurement characteristics of countermovement jump (CMJ) variables in basketball athletes using different variable selection criteria. Test-retest reliability (noise) and seasonal variability (signal) CMJ data were collected from 13 professional basketball athletes playing for the same club throughout 1 competitive season. Interday reliability (coefficient of variation [CV] and intraclass correlation coefficients) were calculated over 3 preseason tests conducted on 3 consecutive days. To evaluate sensitivity, signal-to-noise ratio (SNR) was calculated by dividing seasonal variability (CV) from 8 in-season CMJ tests (collected from November to February) by preseason reliability (CV). Players performed 3 CMJs each testing day, and 3 data analysis techniques were applied: a single variable from the trial with either the best jump height (BestJH; calculated by flight time) or the best flight time to contraction time (BestFT:CT) and mean output across 3 jumps (Mean3). Mean3 was the most reliable data analysis technique, with 79 and 82 of 84 variables displaying lower interday CVs compared with BestJH and BestFT:CT, respectively. Overall, many CMJ measures display seasonal changes that are greater than the inherent noise, with 77 variables producing SNR of >1.00 for Mean3 compared with 65 and 58 variables for BestJH and BestFT:CT, respectively. To improve reliability and sensitivity, it is recommended that practitioners use the average of multiple CMJ trials and regularly reassess measurement characteristics specific to their cohort and environment.
© Copyright 2023 The Journal of Strength and Conditioning Research. National Strength & Conditioning Association. All rights reserved.
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| Notations: | sport games |
| Tagging: | Reliabilität Countermovement-Sprung |
| Published in: | The Journal of Strength and Conditioning Research |
| Language: | English |
| Published: |
2023
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| Online Access: | https://doi.org/10.1519/JSC.0000000000004182 |
| Volume: | 37 |
| Issue: | 2 |
| Pages: | 394-402 |
| Document types: | article |
| Level: | advanced |