IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0166534.html
   My bibliography  Save this article

The Challenge of Evaluating the Intensity of Short Actions in Soccer: A New Methodological Approach Using Percentage Acceleration

Author

Listed:
  • Karin Sonderegger
  • Markus Tschopp
  • Wolfgang Taube

Abstract

Purpose: There are several approaches to quantifying physical load in team sports using positional data. Distances in different speed zones are most commonly used. Recent studies have used acceleration data in addition in order to take short intense actions into account. However, the fact that acceleration decreases with increasing initial running speed is ignored and therefore introduces a bias. The aim of our study was to develop a new methodological approach that removes this bias. For this purpose, percentage acceleration was calculated as the ratio of the maximal acceleration of the action (amax,action) and the maximal voluntary acceleration (amax) that can be achieved for a particular initial running speed (percentage acceleration [%] = amax,action / amax * 100). Methods: To define amax, seventy-two highly trained junior male soccer players (17.1 ± 0.6 years) completed maximal sprints from standing and three different constant initial running speeds (vinit; trotting: ~6.0 km·h–1; jogging: ~10.8 km·h–1; running: ~15.0 km·h–1). Results: The amax was 6.01 ± 0.55 from a standing start, 4.33 ± 0.40 from trotting, 3.20 ± 0.49 from jogging and 2.29 ± 0.34 m·s–2 from running. The amax correlated significantly with vinit (r = –0.98) and the linear regression equation of highly-trained junior soccer players was: amax = –0.23 * vinit + 5.99. Conclusion: Using linear regression analysis, we propose to classify high-intensity actions as accelerations >75% of the amax, corresponding to acceleration values for our population of >4.51 initiated from standing, >3.25 from trotting, >2.40 from jogging, and >1.72 m·s–2 from running. The use of percentage acceleration avoids the bias of underestimating actions with high and overestimating actions with low initial running speed. Furthermore, percentage acceleration allows determining individual intensity thresholds that are specific for one population or one single player.

Suggested Citation

  • Karin Sonderegger & Markus Tschopp & Wolfgang Taube, 2016. "The Challenge of Evaluating the Intensity of Short Actions in Soccer: A New Methodological Approach Using Percentage Acceleration," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-10, November.
    • Handle: RePEc:plo:pone00:0166534
    DOI: 10.1371/journal.pone.0166534
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0166534
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0166534&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0166534?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hadi Nobari & Rafael Oliveira & Filipe Manuel Clemente & Jose Carmelo Adsuar & Jorge Pérez-Gómez & Jorge Carlos-Vivas & João Paulo Brito, 2020. "Comparisons of Accelerometer Variables Training Monotony and Strain of Starters and Non-Starters: A Full-Season Study in Professional Soccer Players," IJERPH, MDPI, vol. 17(18), pages 1-14, September.
    2. Cristian Savoia & Johnny Padulo & Roberto Colli & Emanuele Marra & Allistair McRobert & Neil Chester & Vito Azzone & Samuel A. Pullinger & Dominic A. Doran, 2020. "The Validity of an Updated Metabolic Power Algorithm Based upon di Prampero’s Theoretical Model in Elite Soccer Players," IJERPH, MDPI, vol. 17(24), pages 1-20, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0166534. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.