Literature DB >> 20963438

The development of physiological profiles and identification of training needs in NCAA female collegiate rowers using isoperformance curves.

David H Fukuda1, Kristina L Kendall, Abbie E Smith, Teddi R Dwyer, Jeffrey R Stout.   

Abstract

The purpose of this study was to propose a systematic method for the identification of training strategies and team selection using isoperformance curves. Rowing is a sport that relies on both aerobic and anaerobic energy contributions during a standard 2,000 m competition. The critical velocity model combines both aerobic (critical velocity, CV) and anaerobic (anaerobic rowing capacity, ARC) parameters in a single two-dimensional graphic display. The concept of isoperformance curves, a series of linear equations corresponding to minimum performance standards, allows for an objective overview of a large group of athletes of varying talent. The purpose of this study was to develop physiological profiles from the CV test, and to evaluate results with isoperformance curves to identify training strategies for collegiate rowers. Thirty-five female collegiate rowers completed four time trials over various distances (400, 600, 800, and 1,000 m). CV and ARC were calculated and compared between novice and varsity athletes. CV values for the varsity group were significantly higher than the novice group (P = 0.016). No significant differences were found between groups for ARC (P = 0.068). Mean and individual CV and ARC values were plotted on the x- and y-axes, respectively, and junior, collegiate, and elite isoperformance curves were developed using 2,000 m times from recent indoor rowing competitions. Stratification of athletes through isoperformance curves was used to identify specific training interventions (anaerobic and/or aerobic) needed to improve their 2,000 m performance. The information drawn from isoperformance curves and the parameters of the CV test can be used to provide an objective view of physiological capabilities and training needs on both an individual and team basis.

Mesh:

Year:  2010        PMID: 20963438     DOI: 10.1007/s00421-010-1683-4

Source DB:  PubMed          Journal:  Eur J Appl Physiol        ISSN: 1439-6319            Impact factor:   3.078


  37 in total

1.  Modeling the relationship between velocity and time to fatigue in rowing.

Authors:  David W Hill; Catherine Alain; Michael D Kennedy
Journal:  Med Sci Sports Exerc       Date:  2003-12       Impact factor: 5.411

2.  A physiological description of critical velocity.

Authors:  D W Hill; C S Ferguson
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1999-02

Review 3.  The critical power and related whole-body bioenergetic models.

Authors:  R Hugh Morton
Journal:  Eur J Appl Physiol       Date:  2005-11-12       Impact factor: 3.078

4.  Reliability of power output during rowing changes with ergometer type and race distance.

Authors:  Clara Soper; Patria A Hume
Journal:  Sports Biomech       Date:  2004-07       Impact factor: 2.832

5.  Quantifying training intensity distribution in elite endurance athletes: is there evidence for an "optimal" distribution?

Authors:  K Stephen Seiler; Glenn Øvrevik Kjerland
Journal:  Scand J Med Sci Sports       Date:  2006-02       Impact factor: 4.221

Review 6.  Critical power: implications for determination of V˙O2max and exercise tolerance.

Authors:  Andrew M Jones; Anni Vanhatalo; Mark Burnley; R Hugh Morton; David C Poole
Journal:  Med Sci Sports Exerc       Date:  2010-10       Impact factor: 5.411

7.  Training methods and intensity distribution of young world-class rowers.

Authors:  Arne Guellich; Stephen Seiler; Eike Emrich
Journal:  Int J Sports Physiol Perform       Date:  2009-12       Impact factor: 4.010

8.  The effects of a pre-workout supplement containing caffeine, creatine, and amino acids during three weeks of high-intensity exercise on aerobic and anaerobic performance.

Authors:  Abbie E Smith; David H Fukuda; Kristina L Kendall; Jeffrey R Stout
Journal:  J Int Soc Sports Nutr       Date:  2010-02-15       Impact factor: 5.150

9.  Energy expenditure during simulated rowing.

Authors:  F C Hagerman; M C Connors; J A Gault; G R Hagerman; W J Polinski
Journal:  J Appl Physiol Respir Environ Exerc Physiol       Date:  1978-07

Review 10.  Applied physiology of rowing.

Authors:  F C Hagerman
Journal:  Sports Med       Date:  1984 Jul-Aug       Impact factor: 11.136

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  1 in total

1.  On the use of isoperformance curves for profiling and identification of training needs.

Authors:  Stuart Jolly
Journal:  Eur J Appl Physiol       Date:  2012-03-13       Impact factor: 3.078

  1 in total

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