IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i23p12616-d691511.html
   My bibliography  Save this article

The Effect of Differential Repeated Sprint Training on Physical Performance in Female Basketball Players: A Pilot Study

Author

Listed:
  • Jorge Arede

    (Department of Sports Sciences, Exercise and Health, University of Trás-os-Montes and Alto Douro, 5001-801 Vila Real, Portugal
    School of Education, Polytechnic Institute of Viseu, 3504-501 Viseu, Portugal
    Department of Sports, Higher Institute of Educational Sciences of the Douro, 4560-708 Penafiel, Portugal)

  • Sogand Poureghbali

    (Institute of Sport Science, Otto-von-Guericke-Universität Magdeburg, 39104 Magdeburg, Germany)

  • Tomás Freitas

    (UCAM Research Center for High Performance Sport, Catholic University of Murcia (UCAM), 30107 Murcia, Spain
    NAR-Nucleus of High Performance in Sport, São Paulo 04753-060, Brazil
    Faculty of Sport Sciences, Catholic University of Murcia (UCAM), 30107 Murcia, Spain)

  • John Fernandes

    (School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff CF23 6XD, UK)

  • Wolfgang I. Schöllhorn

    (Institute of Sport Science, Training and Movement Science, University of Mainz, 55122 Mainz, Germany)

  • Nuno Leite

    (Department of Sports Sciences, Exercise and Health, University of Trás-os-Montes and Alto Douro, 5001-801 Vila Real, Portugal
    Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, University of Trás-os-Montes and Alto Douro, 5001-801 Vila Real, Portugal)

Abstract

This pilot study aimed to determine the effects of differential learning in sprint running with and without changes of direction (COD) on physical performance parameters in female basketball players and to determine the feasibility of the training protocol. Nine female basketball players completed 4 weeks of repeated sprint training (RST) with (COD, n = 4) or without (NCOD, n = 5) changes of direction. A battery of sprints (0–10 and 0–25 m), vertical jumps (counter movement jump (CMJ), drop jump, and single-leg CMJs), and COD tests were conducted before and after intervention. NCOD completed two sets of ten sprints of 20 m, whereas COD performed 20 m sprints with a 180 degree turn at 10 m, returning to the starting line. Before each sprint, participants were instructed to provide different fluctuations (i.e., differential learning) in terms of varying the sprint. Both groups had 30 s of passive recovery between two sprints and 3 min between sets. A significant effect of time for the 0–10 m sprint, CMJ, and single leg-CMJ asymmetries were observed. Adding “erroneous” fluctuation during RST seems to be a suitable and feasible strategy for coaches to enhance physical performance in young female basketball players. However, further studies including larger samples and controlled designs are recommended to strengthen present findings.

Suggested Citation

  • Jorge Arede & Sogand Poureghbali & Tomás Freitas & John Fernandes & Wolfgang I. Schöllhorn & Nuno Leite, 2021. "The Effect of Differential Repeated Sprint Training on Physical Performance in Female Basketball Players: A Pilot Study," IJERPH, MDPI, vol. 18(23), pages 1-16, November.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12616-:d:691511
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/23/12616/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/23/12616/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Regina Nuzzo, 2014. "Scientific method: Statistical errors," Nature, Nature, vol. 506(7487), pages 150-152, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Jorge Arede & John F. T. Fernandes & Wolfgang I. Schöllhorn & Nuno Leite, 2022. "Differential Repeated Sprinting Training in Youth Basketball Players: An Analysis of Effects According to Maturity Status," IJERPH, MDPI, vol. 19(19), pages 1-15, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jyotirmoy Sarkar, 2018. "Will P†Value Triumph over Abuses and Attacks?," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(4), pages 66-71, July.
    2. Gunnarsson, Björn Rafn & vanden Broucke, Seppe & Baesens, Bart & Óskarsdóttir, María & Lemahieu, Wilfried, 2021. "Deep learning for credit scoring: Do or don’t?," European Journal of Operational Research, Elsevier, vol. 295(1), pages 292-305.
    3. Arthur Matsuo Yamashita Rios de Sousa & Hideki Takayasu & Misako Takayasu, 2017. "Detection of statistical asymmetries in non-stationary sign time series: Analysis of foreign exchange data," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.
    4. Maurizio Canavari & Andreas C. Drichoutis & Jayson L. Lusk & Rodolfo M. Nayga, Jr., 2018. "How to run an experimental auction: A review of recent advances," Working Papers 2018-5, Agricultural University of Athens, Department Of Agricultural Economics.
    5. Andrew Gelman & Christian Hennig, 2017. "Beyond subjective and objective in statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 967-1033, October.
    6. Felipe Campelo & Fernanda Takahashi, 2019. "Sample size estimation for power and accuracy in the experimental comparison of algorithms," Journal of Heuristics, Springer, vol. 25(2), pages 305-338, April.
    7. Martin E Héroux & Janet L Taylor & Simon C Gandevia, 2015. "The Use and Abuse of Transcranial Magnetic Stimulation to Modulate Corticospinal Excitability in Humans," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-10, December.
    8. Roger Beecham & Nick Williams & Alexis Comber, 2020. "Regionally-structured explanations behind area-level populism: An update to recent ecological analyses," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
    9. Tagiew, Rustam & Ignatov, Dmitry, 2016. "Gift Ratios in Laboratory Experiments," MPRA Paper 77603, University Library of Munich, Germany.
    10. Megan L Head & Luke Holman & Rob Lanfear & Andrew T Kahn & Michael D Jennions, 2015. "The Extent and Consequences of P-Hacking in Science," PLOS Biology, Public Library of Science, vol. 13(3), pages 1-15, March.
    11. Louis Anthony (Tony) Cox, 2015. "Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks," Risk Analysis, John Wiley & Sons, vol. 35(10), pages 1892-1910, October.
    12. Bettina Budeus & Jörg Timm & Daniel Hoffmann, 2016. "SeqFeatR for the Discovery of Feature-Sequence Associations," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-12, January.
    13. Shuxin Guo & Qiang Liu, 2024. "Data-generating process and time-series asset pricing," Papers 2405.10920, arXiv.org.
    14. Luo, Xing & Zhang, Dongxiao & Zhu, Xu, 2022. "Combining transfer learning and constrained long short-term memory for power generation forecasting of newly-constructed photovoltaic plants," Renewable Energy, Elsevier, vol. 185(C), pages 1062-1077.
    15. Chengwu Yang & Carlo Panlilio & Nicole Verdiglione & Erik B Lehman & Robert M Hamm & Richard Fiene & Sarah Dore & David E Bard & Breanna Grable & Benjamin Levi, 2020. "Generalizing findings from a randomized controlled trial to a real-world study of the iLookOut, an online education program to improve early childhood care and education providers’ knowledge and attit," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-11, January.
    16. Micha³ Zdziarski & Dominika Czerniawska, 2016. "Board Homophily, Board Diversity and Network Centrality (Homofilia, zroznicowanie i centralnosc rady w sieci)," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 14(60), pages 117-133.
    17. Juan Li & Hanzhang Xu & Wei Pan & Bei Wu, 2017. "Association between tooth loss and cognitive decline: A 13-year longitudinal study of Chinese older adults," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-12, February.
    18. Felix Holzmeister & Magnus Johannesson & Robert Böhm & Anna Dreber & Jürgen Huber & Michael Kirchler, 2023. "Heterogeneity in effect size estimates: Empirical evidence and practical implications," Working Papers 2023-17, Faculty of Economics and Statistics, Universität Innsbruck.
    19. Michael E. Mann & Elisabeth A. Lloyd & Naomi Oreskes, 2017. "Assessing climate change impacts on extreme weather events: the case for an alternative (Bayesian) approach," Climatic Change, Springer, vol. 144(2), pages 131-142, September.
    20. Chaskalovic, Joël & Assous, Franck, 2016. "Data mining and probabilistic models for error estimate analysis of finite element method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 129(C), pages 50-68.

    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:gam:jijerp:v:18:y:2021:i:23:p:12616-:d:691511. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.