Literature DB >> 14599233

Systems modelling of the relationship between training and performance.

Tim Taha1, Scott G Thomas.   

Abstract

Mathematical models may provide a method of describing and predicting the effect of training on performance. The current models attempt to describe the effects of single or multiple bouts of exercise on the performance of a specific task on a given day. These models suggest that any training session increases fitness and provokes a fatigue response. Various methods of quantifying the training stimulus (training impulse, absolute work, psychophysiological rating) and physical performance (criterion scale, arbitrary units) are employed in these models. The models are empirical descriptions and do not use current knowledge regarding the specificity of training adaptations. Tests of these models with published data indicate discrepancies between the predicted and measured time course of physiological adaptations, and between the predicted and measured performance responses to training. The relationship between these models and the underlying physiology requires clarification. New functional models that incorporate specificity of training and known physiology are required to enhance our ability to guide athletic training, rehabilitation and research.

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Year:  2003        PMID: 14599233     DOI: 10.2165/00007256-200333140-00003

Source DB:  PubMed          Journal:  Sports Med        ISSN: 0112-1642            Impact factor:   11.136


  40 in total

1.  Modelling the transfers of training effects on performance in elite triathletes.

Authors:  G P Millet; R B Candau; B Barbier; T Busso; J D Rouillon; J C Chatard
Journal:  Int J Sports Med       Date:  2002-01       Impact factor: 3.118

Review 2.  Individual differences in response to regular physical activity.

Authors:  C Bouchard; T Rankinen
Journal:  Med Sci Sports Exerc       Date:  2001-06       Impact factor: 5.411

3.  Optimizing athletic performance by influence curves.

Authors:  J R Fitz-Clarke; R H Morton; E W Banister
Journal:  J Appl Physiol (1985)       Date:  1991-09

Review 4.  Assembling control models from pulmonary gas exchange dynamics.

Authors:  G D Swanson
Journal:  Med Sci Sports Exerc       Date:  1990-02       Impact factor: 5.411

5.  Reduced training maintains performance in distance runners.

Authors:  J A Houmard; D L Costill; J B Mitchell; S H Park; R C Hickner; J N Roemmich
Journal:  Int J Sports Med       Date:  1990-02       Impact factor: 3.118

Review 6.  What is fatigue?

Authors:  Brian R MacIntosh; Dilson E Rassier
Journal:  Can J Appl Physiol       Date:  2002-02

7.  Blood lactate during exercise: time course of training adaptation in humans.

Authors:  G A Gaesser; D C Poole
Journal:  Int J Sports Med       Date:  1988-08       Impact factor: 3.118

8.  Modeling human performance in running.

Authors:  R H Morton; J R Fitz-Clarke; E W Banister
Journal:  J Appl Physiol (1985)       Date:  1990-09

Review 9.  Spinal and supraspinal factors in human muscle fatigue.

Authors:  S C Gandevia
Journal:  Physiol Rev       Date:  2001-10       Impact factor: 37.312

10.  Early adaptations in gas exchange, cardiac function and haematology to prolonged exercise training in man.

Authors:  H J Green; G Coates; J R Sutton; S Jones
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1991
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  14 in total

1.  Assessing the limitations of the Banister model in monitoring training.

Authors:  Philippe Hellard; Marta Avalos; Lucien Lacoste; Frederic Barale; Jean-Claude Chatard; Gregoire P Millet
Journal:  J Sports Sci       Date:  2006-05       Impact factor: 3.337

2.  A mathematical model for quantifying training.

Authors:  Philip R Hayes; Mike D Quinn
Journal:  Eur J Appl Physiol       Date:  2009-05-26       Impact factor: 3.078

Review 3.  The quantification of training load, the training response and the effect on performance.

Authors:  Jill Borresen; Michael Ian Lambert
Journal:  Sports Med       Date:  2009       Impact factor: 11.136

Review 4.  The analysis and utilization of cycling training data.

Authors:  Simon A Jobson; Louis Passfield; Greg Atkinson; Gabor Barton; Philip Scarf
Journal:  Sports Med       Date:  2009       Impact factor: 11.136

5.  Modeling of performance and ANS activity for predicting future responses to training.

Authors:  Sébastien Chalencon; Vincent Pichot; Frédéric Roche; Jean-René Lacour; Martin Garet; Philippe Connes; Jean Claude Barthélémy; Thierry Busso
Journal:  Eur J Appl Physiol       Date:  2014-10-31       Impact factor: 3.078

Review 6.  Relationships Between Training Load Indicators and Training Outcomes in Professional Soccer.

Authors:  Arne Jaspers; Michel S Brink; Steven G M Probst; Wouter G P Frencken; Werner F Helsen
Journal:  Sports Med       Date:  2017-03       Impact factor: 11.136

Review 7.  Is there Evidence for the Suggestion that Fatigue Accumulates Following Resistance Exercise?

Authors:  Ryo Kataoka; Ecaterina Vasenina; William B Hammert; Adam H Ibrahim; Scott J Dankel; Samuel L Buckner
Journal:  Sports Med       Date:  2021-10-06       Impact factor: 11.928

8.  A comparison of methods for quantifying training load: relationships between modelled and actual training responses.

Authors:  L K Wallace; K M Slattery; Aaron J Coutts
Journal:  Eur J Appl Physiol       Date:  2013-10-09       Impact factor: 3.078

9.  Effects of intensity distribution changes on performance and on training loads quantification.

Authors:  Hourcade Jean-Christophe; Noirez Philippe; Sidney Michel; Toussaint Jean-François; Desgorces François
Journal:  Biol Sport       Date:  2017-10-12       Impact factor: 2.806

Review 10.  The impact of triathlon training and racing on athletes' general health.

Authors:  Veronica Vleck; Gregoire P Millet; Francisco Bessone Alves
Journal:  Sports Med       Date:  2014-12       Impact factor: 11.136

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