Literature DB >> 19910822

Performance modeling in an Olympic 1500-m finalist: a practical approach.

Stephen J McGregor1, Rachael K Weese, Ian K Ratz.   

Abstract

The purpose of this study was to test if a simplified impulse-response (IR) model would correlate with competition performances in an elite middle-distance runner over a period of 7 years that encompassed two Olympiads. Daily recorded pace and time obtained from training logs of this individual for the years 2000 to 2006 were used to calculate the impulse (training stress score, or TSS). The daily TSS was used to generate acute and chronic training loads (ATL and CTL, respectively), and a model response output, or p(t), was calculated based on the relationship p(t) = CTL - ATL. Competition performances (800 m-1 mile) were converted to Mercier scores (MS) and compared to p(t) and model parameters TSS, ATL, and CTL. MS was positively correlated with model output response p(t) (p < 0.01) and negatively with ATL (p < 0.01). Quadratic relationships were also observed between MS and both p(t) and CTL (p < 0.001), potentially indicating an optimal balance between fitness, fatigue, and performance. The results of this study demonstrate that the output of this simplified IR modeling approach correlates with performance in at least 1 elite athlete. Further studies are necessary to determine the generalizability of this method, but coaches may wish to use this approach to analyze previous training and performance relationships and iteratively modify training to optimize performance.

Entities:  

Mesh:

Year:  2009        PMID: 19910822     DOI: 10.1519/JSC.0b013e3181bf88be

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  4 in total

Review 1.  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

2.  Metabolic factors limiting performance in marathon runners.

Authors:  Benjamin I Rapoport
Journal:  PLoS Comput Biol       Date:  2010-10-21       Impact factor: 4.475

3.  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

4.  High resolution MEMS accelerometers to estimate VO2 and compare running mechanics between highly trained inter-collegiate and untrained runners.

Authors:  Stephen J McGregor; Michael A Busa; James A Yaggie; Erik M Bollt
Journal:  PLoS One       Date:  2009-10-06       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.