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The Quantification of Training Load, the Training Response and the Effect on Performance

Overview of attention for article published in Sports Medicine, October 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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5 news outlets
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41 X users
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3 patents
facebook
1 Facebook page

Citations

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457 Dimensions

Readers on

mendeley
1176 Mendeley
Title
The Quantification of Training Load, the Training Response and the Effect on Performance
Published in
Sports Medicine, October 2012
DOI 10.2165/11317780-000000000-00000
Pubmed ID
Authors

Jill Borresen, Michael Ian Lambert

Abstract

Historically, the ability of coaches to prescribe training to achieve optimal athletic performance can be attributed to many years of personal experience. A more modern approach is to adopt scientific methods in the development of optimal training programmes. However, there is not much research in this area, particularly into the quantification of training programmes and their effects on physiological adaptation and subsequent performance. Several methods have been used to quantify training load, including questionnaires, diaries, physiological monitoring and direct observation. More recently, indices of training stress have been proposed, including the training impulse, which uses heart rate measurements and training load, and session rating of perceived exertion measurements, which utilizes subjective perception of effort scores and duration of exercise. Although physiological adaptations to training are well documented, their influence on performance has not been accurately quantified. To date, no single physiological marker has been identified that can measure the fitness and fatigue responses to exercise or accurately predict performance. Models attempting to quantify the relationship between training and performance have been proposed, many of which consider the athlete as a system in which the training load is the input and performance the system output. Although attractive in concept, the accuracy of these theoretical models has proven poor. A possible reason may be the absence of a measure of individuality in each athlete's response to training. Thus, in the future more attention should be directed towards measurements that reflect individual capacity to respond or adapt to exercise training rather than an absolute measure of changes in physiological variables that occur with training.

X Demographics

X Demographics

The data shown below were collected from the profiles of 41 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 13 1%
Spain 10 <1%
United Kingdom 7 <1%
United States 6 <1%
South Africa 4 <1%
Germany 4 <1%
France 2 <1%
Canada 2 <1%
Netherlands 1 <1%
Other 8 <1%
Unknown 1119 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 235 20%
Student > Bachelor 165 14%
Student > Ph. D. Student 132 11%
Researcher 93 8%
Student > Postgraduate 72 6%
Other 246 21%
Unknown 233 20%
Readers by discipline Count As %
Sports and Recreations 630 54%
Medicine and Dentistry 67 6%
Agricultural and Biological Sciences 45 4%
Nursing and Health Professions 36 3%
Social Sciences 19 2%
Other 108 9%
Unknown 271 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 74. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 October 2023.
All research outputs
#589,237
of 25,734,859 outputs
Outputs from Sports Medicine
#549
of 2,896 outputs
Outputs of similar age
#3,160
of 202,634 outputs
Outputs of similar age from Sports Medicine
#71
of 980 outputs
Altmetric has tracked 25,734,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,896 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 57.2. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 202,634 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 980 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.