Literature DB >> 33725208

Using Field Based Data to Model Sprint Track Cycling Performance.

Hamish A Ferguson1, Chris Harnish2, J Geoffrey Chase3.   

Abstract

Cycling performance models are used to study rider and sport characteristics to better understand performance determinants and optimise competition outcomes. Performance requirements cover the demands of competition a cyclist may encounter, whilst rider attributes are physical, technical and psychological characteristics contributing to performance. Several current models of endurance-cycling enhance understanding of performance in road cycling and track endurance, relying on a supply and demand perspective. However, they have yet to be developed for sprint-cycling, with current athlete preparation, instead relying on measures of peak-power, speed and strength to assess performance and guide training. Peak-power models do not adequately explain the demands of actual competition in events over 15-60 s, let alone, in World-Championship sprint cycling events comprising several rounds to medal finals. Whilst there are no descriptive studies of track-sprint cycling events, we present data from physiological interventions using track cycling and repeated sprint exercise research in multiple sports, to elucidate the demands of performance requiring several maximal sprints over a competition. This review will show physiological and power meter data, illustrating the role of all energy pathways in sprint performance. This understanding highlights the need to focus on the capacity required for a given race and over an event, and therefore the recovery needed for each subsequent race, within and between races, and how optimal pacing can be used to enhance performance. We propose a shift in sprint-cyclist preparation away from training just for peak power, to a more comprehensive model of the actual event demands.

Entities:  

Year:  2021        PMID: 33725208      PMCID: PMC7966696          DOI: 10.1186/s40798-021-00310-0

Source DB:  PubMed          Journal:  Sports Med Open        ISSN: 2198-9761


  108 in total

1.  A metabolic basis for impaired muscle force production and neuromuscular compensation during sprint cycling.

Authors:  Matthew W Bundle; Carrie L Ernst; Matthew J Bellizzi; Seth Wright; Peter G Weyand
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2006-07-13       Impact factor: 3.619

2.  Influence of different racing positions on mechanical and electromyographic patterns during pedalling.

Authors:  S Dorel; A Couturier; F Hug
Journal:  Scand J Med Sci Sports       Date:  2008-02-04       Impact factor: 4.221

3.  Cycling power output produced during flat and mountain stages in the Giro d'Italia: a case study.

Authors:  Stefan Vogt; Yorck Olaf Schumacher; Andreas Blum; Kai Roecker; Hans-Hermann Dickhuth; Andreas Schmid; Lothar Heinrich
Journal:  J Sports Sci       Date:  2007-10       Impact factor: 3.337

4.  Metabolic response of type I and II muscle fibers during repeated bouts of maximal exercise in humans.

Authors:  A Casey; D Constantin-Teodosiu; S Howell; E Hultman; P L Greenhaff
Journal:  Am J Physiol       Date:  1996-07

5.  Relation between Peak Power Output in Sprint Cycling and Maximum Voluntary Isometric Torque Production.

Authors:  Mehdi Kordi; Stuart Goodall; Paul Barratt; Nicola Rowley; Jonathan Leeder; Glyn Howatson
Journal:  J Electromyogr Kinesiol       Date:  2017-06-10       Impact factor: 2.368

6.  Factors Affecting Cyclists' Chances of Success in Match-Sprint Tournaments.

Authors:  Kathryn E Phillips; Will G Hopkins
Journal:  Int J Sports Physiol Perform       Date:  2019-02-22       Impact factor: 4.010

7.  Estimation of the contribution of the various energy systems during maximal work of short duration.

Authors:  O Serresse; G Lortie; C Bouchard; M R Boulay
Journal:  Int J Sports Med       Date:  1988-12       Impact factor: 3.118

8.  Muscle glycogenolysis and H+ concentration during maximal intermittent cycling.

Authors:  L L Spriet; M I Lindinger; R S McKelvie; G J Heigenhauser; N L Jones
Journal:  J Appl Physiol (1985)       Date:  1989-01

9.  How to assess performance in cycling: the multivariate nature of influencing factors and related indicators.

Authors:  A Margherita Castronovo; Silvia Conforto; Maurizio Schmid; Daniele Bibbo; Tommaso D'Alessio
Journal:  Front Physiol       Date:  2013-05-21       Impact factor: 4.566

Review 10.  The Training and Development of Elite Sprint Performance: an Integration of Scientific and Best Practice Literature.

Authors:  Thomas Haugen; Stephen Seiler; Øyvind Sandbakk; Espen Tønnessen
Journal:  Sports Med Open       Date:  2019-11-21
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  1 in total

Review 1.  Power profiling and the power-duration relationship in cycling: a narrative review.

Authors:  Peter Leo; James Spragg; Tim Podlogar; Justin S Lawley; Iñigo Mujika
Journal:  Eur J Appl Physiol       Date:  2021-10-27       Impact factor: 3.078

  1 in total

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