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Sports Medicine

, Volume 48, Issue 3, pp 641–658 | Cite as

The Relationships Between Internal and External Measures of Training Load and Intensity in Team Sports: A Meta-Analysis

  • Shaun J. McLarenEmail author
  • Tom W. Macpherson
  • Aaron J. Coutts
  • Christopher Hurst
  • Iain R. Spears
  • Matthew Weston
Systematic Review

Abstract

Background

The associations between internal and external measures of training load and intensity are important in understanding the training process and the validity of specific internal measures.

Objectives

We aimed to provide meta-analytic estimates of the relationships, as determined by a correlation coefficient, between internal and external measures of load and intensity during team-sport training and competition. A further aim was to examine the moderating effects of training mode on these relationships.

Methods

We searched six electronic databases (Scopus, Web of Science, PubMed, MEDLINE, SPORTDiscus, CINAHL) for original research articles published up to September 2017. A Boolean search phrase was created to include search terms relevant to team-sport athletes (population; 37 keywords), internal load (dependent variable; 35 keywords), and external load (independent variable; 81 keywords). Articles were considered for meta-analysis when a correlation coefficient describing the association between at least one internal and one external measure of session load or intensity, measured in the time or frequency domain, was obtained from team-sport athletes during normal training or match-play (i.e., unstructured observational study). The final data sample included 122 estimates from 13 independent studies describing 15 unique relationships between three internal and nine external measures of load and intensity. This sample included 295 athletes and 10,418 individual session observations. Internal measures were session ratings of perceived exertion (sRPE), sRPE training load (sRPE-TL), and heart-rate-derived training impulse (TRIMP). External measures were total distance (TD), the distance covered at high and very high speeds (HSRD ≥ 13.1–15.0 km h−1 and VHSRD ≥ 16.9–19.8 km h−1, respectively), accelerometer load (AL), and the number of sustained impacts (Impacts > 2–5 G). Distinct training modes were identified as either mixed (reference condition), skills, metabolic, or neuromuscular. Separate random effects meta-analyses were conducted for each dataset (n = 15) to determine the pooled relationships between internal and external measures of load and intensity. The moderating effects of training mode were examined using random-effects meta-regression for datasets with at least ten estimates (n = 4). Magnitude-based inferences were used to interpret analyses outcomes.

Results

During all training modes combined, the external load relationships for sRPE-TL were possibly very large with TD [r = 0.79; 90% confidence interval (CI) 0.74 to 0.83], possibly large with AL (r = 0.63; 90% CI 0.54 to 0.70) and Impacts (r = 0.57; 90% CI 0.47 to 0.64), and likely moderate with HSRD (r = 0.47; 90% CI 0.32 to 0.59). The relationship between TRIMP and AL was possibly large (r = 0.54; 90% CI 0.40 to 0.66). All other relationships were unclear or not possible to infer (r range 0.17–0.74, n = 10 datasets). Between-estimate heterogeneity [standard deviations (SDs) representing unexplained variation; τ] in the pooled internal–external relationships were trivial to extremely large for sRPE (τ range = 0.00–0.47), small to large for sRPE-TL (τ range = 0.07–0.31), and trivial to moderate for TRIMP (τ range= 0.00–0.17). The internal–external load relationships during mixed training were possibly very large for sRPE-TL with TD (r = 0.82; 90% CI 0.75 to 0.87) and AL (r = 0.81; 90% CI 0.74 to 0.86), and TRIMP with AL (r = 0.72; 90% CI 0.55 to 0.84), and possibly large for sRPE-TL with HSRD (r = 0.65; 90% CI 0.44 to 0.80). A reduction in these correlation magnitudes was evident for all other training modes (range of the change in r when compared with mixed training − 0.08 to − 0.58), with these differences being unclear to possibly large. Training mode explained 24–100% of the between-estimate variance in the internal–external load relationships.

Conclusion

Measures of internal load derived from perceived exertion and heart rate show consistently positive associations with running- and accelerometer-derived external loads and intensity during team-sport training and competition, but the magnitude and uncertainty of these relationships are measure and training mode dependent.

Notes

Acknowledgements

The authors express gratitude to the authors who provided additional data for the studies included in this meta-analysis. We are extremely grateful to Professor Greg Atkinson for his useful scientific discussions and statistical advice during the preparation of the paper.

Compliance with Ethical Standards

Funding

No sources of funding or financial support were used to assist in the preparation of this article.

Conflicts of interest

Shaun J. McLaren, Tom W. Macpherson, Aaron J. Coutts, Christopher Hurst, Iain R. Spears, and Matthew Weston have no conflicts of interest relevant to the content of this article.

Supplementary material

40279_2017_830_MOESM1_ESM.pdf (905 kb)
Supplementary material 1 (PDF 905 kb)
40279_2017_830_MOESM2_ESM.pdf (602 kb)
Supplementary material 2 (PDF 602 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Psychology, Sport and Exercise, School of Social Sciences, Humanities and LawTeesside UniversityMiddlesbroughUK
  2. 2.Sport Science and Medical DepartmentHartlepool United Football ClubHartlepoolUK
  3. 3.Sport and Exercise Discipline Group, Faculty of HealthUniversity of Technology Sydney (UTS)SydneyAustralia
  4. 4.Pro-Football SupportHuddersfieldUK
  5. 5.School of Applied Social SciencesDurham UniversityDurhamUK

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