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Published in: Sport Sciences for Health 2/2014

01-08-2014 | Original Article

Repeated sprint ability tests and intensity–time curvature constant to predict short-distance running performances

Authors: Wladimir Rafael Beck, Alessandro Moura Zagatto, Claudio Alexandre Gobatto

Published in: Sport Sciences for Health | Issue 2/2014

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Abstract

Purpose

Anaerobic efforts are commonly required through repeated sprint during efforts in many sports, making the anaerobic pathway a target of training. Nevertheless, to identify improvements on such energetic way it is necessary to assess anaerobic capacity or power, which is usually complex. For this purpose, authors have postulated the use of short running performances to anaerobic ability assessment. Thus, the aim of this study was to find a relationship between running performances on anaerobic power, anaerobic capacity or repeated sprint ability.

Methods

Thirteen military performed maximal running of 50 (P50), 100 (P100) and 300 (P300) m on track, beyond of running-based anaerobic sprint test (RAST; RSA and anaerobic power test), maximal anaerobic running test (MART; RSA and anaerobic capacity test) and the W′ from critical power model (anaerobic capacity test).

Results

By RAST variables, peak and average power (absolute and relative) and maximum velocity were significantly correlated with P50 (r = −0.68, p = 0.03 and −0.76, p = 0.01; −0.83, p < 0.01 and −0.83, p < 0.01; and −0.78, p < 0.01), respectively. The maximum intensity of MART was negatively and significantly correlated with P100 (r = −0.59) and W′ was not statistically correlated with any of the performances.

Conclusion

MART and W′ were not correlated with short running performances, having a weak performance predicting probably due to its longer duration in relation to assessed performances. Observing RAST outcomes, we postulated that such a protocol can be used during daily training as short running performance predictor.
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Metadata
Title
Repeated sprint ability tests and intensity–time curvature constant to predict short-distance running performances
Authors
Wladimir Rafael Beck
Alessandro Moura Zagatto
Claudio Alexandre Gobatto
Publication date
01-08-2014
Publisher
Springer Milan
Published in
Sport Sciences for Health / Issue 2/2014
Print ISSN: 1824-7490
Electronic ISSN: 1825-1234
DOI
https://doi.org/10.1007/s11332-014-0180-2

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