IDEAS home Printed from https://ideas.repec.org/a/taf/rpanxx/v20y2020i1p118-132.html
   My bibliography  Save this article

Conditional analysis of elite beach handball according to specific playing position through assessment with GPS

Author

Listed:
  • Juan Carlos Zapardiel
  • Iván Asín-Izquierdo

Abstract

Beach handball needs to continue to develop. For this reason, observational studies that analyse competitive demands are necessary. Therefore, our objective in this work was to carry out performance assessment of the beach handball players regarding specific playing positions during competition, without modifying the specific structure of the game. The study included 57 elite beach handball players. The results showed that significant differences were found in most of the variables studied when the specific playing positions were compared. Our work has led us to conclude that the assessment of the conditional demands of beach handball players in competition must be done considering the specific playing positions.

Suggested Citation

  • Juan Carlos Zapardiel & Iván Asín-Izquierdo, 2020. "Conditional analysis of elite beach handball according to specific playing position through assessment with GPS," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 20(1), pages 118-132, January.
    • Handle: RePEc:taf:rpanxx:v:20:y:2020:i:1:p:118-132
    DOI: 10.1080/24748668.2020.1718458
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24748668.2020.1718458
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/24748668.2020.1718458?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Alice Iannaccone & Daniele Conte & Cristina Cortis & Andrea Fusco, 2021. "Usefulness of Linear Mixed-Effects Models to Assess the Relationship between Objective and Subjective Internal Load in Team Sports," IJERPH, MDPI, vol. 18(2), pages 1-11, January.
    2. Basilio Pueo & Jose Julio Espina-Agullo & Sergio Selles-Perez & Alfonso Penichet-Tomas, 2020. "Optimal Body Composition and Anthropometric Profile of World-Class Beach Handball Players by Playing Positions," Sustainability, MDPI, vol. 12(17), pages 1-13, August.

    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:taf:rpanxx:v:20:y:2020:i:1:p:118-132. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RPAN20 .

    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.