Literature DB >> 19124896

Using mathematical modeling in training planning.

Thierry Busso1, Luc Thomas.   

Abstract

This report aims to discuss the strengths and weaknesses of the application of systems modeling to analyze the effects of training on performance. The simplifications inherent to the modeling approach are outlined to question the relevance of the models to predict athletes' responses to training. These simplifications include the selection of the variables assigned to the system's input and output, the specification of model structure, the collection of data to estimate the model parameters, and the use of identified models and parameters to predict responses. Despite the gain in insight to understand the effects of an intensification or reduction of training, the existing models would not be accurate enough to make predictions for a particular athlete in order to monitor his or her training.

Mesh:

Year:  2006        PMID: 19124896     DOI: 10.1123/ijspp.1.4.400

Source DB:  PubMed          Journal:  Int J Sports Physiol Perform        ISSN: 1555-0265            Impact factor:   4.010


  8 in total

Review 1.  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

2.  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

3.  Modelling the HRV Response to Training Loads in Elite Rugby Sevens Players.

Authors:  Sean Williams; Stephen West; Dan Howells; Simon P T Kemp; Andrew A Flatt; Keith Stokes
Journal:  J Sports Sci Med       Date:  2018-08-14       Impact factor: 2.988

4.  Training load responses modelling and model generalisation in elite sports.

Authors:  Frank Imbach; Stephane Perrey; Romain Chailan; Thibaut Meline; Robin Candau
Journal:  Sci Rep       Date:  2022-01-28       Impact factor: 4.996

5.  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

6.  Modeling the responses to resistance training in an animal experiment study.

Authors:  Antony G Philippe; Guillaume Py; François B Favier; Anthony M J Sanchez; Anne Bonnieu; Thierry Busso; Robin Candau
Journal:  Biomed Res Int       Date:  2015-01-28       Impact factor: 3.411

7.  The development and prediction of athletic performance in freestyle swimming.

Authors:  Arkadiusz Stanula; Adam Maszczyk; Robert Roczniok; Przemysław Pietraszewski; Andrzej Ostrowski; Adam Zając; Marek Strzała
Journal:  J Hum Kinet       Date:  2012-05-30       Impact factor: 2.193

8.  A Fitness-Fatigue Model of Performance in Peripheral Artery Disease: Predicted and Measured Effects of a Pain-Free Exercise Program.

Authors:  Nicola Lamberti; Giovanni Piva; Federico Businaro; Lorenzo Caruso; Anna Crepaldi; Pablo Jesùs Lòpez-Soto; Fabio Manfredini
Journal:  J Pers Med       Date:  2022-03-04
  8 in total

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