Training Load, Neuromuscular Readiness, and Perceptual Fatigue Profile in Youth Elite Long-Jump Athletes

in International Journal of Sports Physiology and Performance
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Purpose: To describe and identify individual trends and changes in training load, neuromuscular readiness, and perceptual fatigue measures in 2 youth elite long jumpers, finalists at the European Athletics U18 (Under 18) Championships (athlete A, female, age 16.5 y, long-jump record 6.25 m; athlete B, male, age 16.0 y, long-jump record 7.28 m). Methods: Data were collected from both training sessions and athletics competitions during a 16-week period, divided into a preparation (weeks 1–8) and a competitive phase (weeks 9–16). Training load was computed through training diaries (training time, sprint, jumping, and weights volume). The countermovement jump and the 10-to-5 repeated-jump test were executed on a weekly basis to assess neuromuscular readiness, and perceptual fatigue measures were collected through a wellness questionnaire. Statistical analysis was conducted using a magnitude-based decisions approach. Results: The results highlighted a decrease in training load during the competitive period with moderate to large differences for training time, sprint, and jump volume. Moreover, data showed an upward trend and very likely higher scores in vertical-jump performance across the competitive phase together with a very likely lower perceptual fatigue. Conclusions: This scenario seemed to be favorable to achieve competition performance very close to the personal record during the competitive season. This study provided an example of application of a comprehensive monitoring system with young athletes involved in track-and-field jumping events.

Franceschi and Sampaio are with the Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), University of Trás-os-Montes and Alto Douro, Vila Real, Portugal. Franceschi and Airale are with Eracle Academy, Turin, Italy. Conte is with the Inst of Sport Science and Innovations, Lithuanian Sports University, Kaunas, Lithuania.

Franceschi (alb.franceschi@gmail.com) is corresponding author.
  • 1.

    Haugen TA, Solberg PA, Foster C, Moran-Navarro R, Breitschadel F, Hopkins WG. Peak age and performance progression in world-class track-and-field athletes. Int J Sports Physiol Perform. 2018;13(9):11221129. PubMed ID: 29543080 doi:10.1123/ijspp.2017-0682

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Boccia G, Moisè P, Franceschi A, et al. Career performance trajectories in track and field jumping events from youth to senior success: the importance of learning and development. PLoS One. 2017;12(1):e0170744. PubMed ID: 28129370 doi:10.1371/journal.pone.0170744

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Tonnessen E, Svendsen IS, Olsen IC, Guttormsen A, Haugen T. Performance development in adolescent track and field athletes according to age, sex and sport discipline. PLoS One. 2015;10(6):e0129014. PubMed ID: 26043192 doi:10.1371/journal.pone.0129014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Huxley DJ, O’Connor D, Healey PA. An examination of the training profiles and injuries in elite youth track and field athletes. Eur J Sport Sci. 2014;14(2):185192. PubMed ID: 23777449 doi:10.1080/17461391.2013.809153

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Murray A. Managing the training load in adolescent athletes. Int J Sports Physiol Perform. 2017;12(suppl 2):S242S249. doi:10.1123/ijspp.2016-0334

  • 6.

    Sands W, Cardinale M, McNeal J, et al. Recommendations for measurement and management of an elite athlete. Sports. 2019;7(5):105. doi:10.3390/sports7050105

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Jiménez-Reyes P, González-Badillo JJ. Monitoring training load through the CMJ in sprints and jump events for optimizing performance in athletics. Cultura, Ciencia y Deporte. 2011;7(18):207217.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Harper D, Hobbs SJ. The ten to five repeated jump test. A new test for evaluation of reactive strength. Paper presented at: BASES Student Conference; April 12–13, 2011; Chester, United Kingdom. http://ray.yorksj.ac.uk/id/eprint/2664

    • Export Citation
  • 9.

    Hooper SL, Mackinnon LT, Howard A, Gordon RD, Bachmann AW. Markers for monitoring overtraining and recovery. Med Sci Sports Exerc. 1995;27(1):106112. PubMed ID: 7898325 doi:10.1249/00005768-199501000-00019

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Impellizzeri FM, Maffiuletti NA. Convergent evidence for construct validity of a 7-point Likert scale of lower limb muscle soreness. Clin J Sport Med. 2007;17(6):494496. PubMed ID: 17993794 doi:10.1097/JSM.0b013e31815aed57

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Hopkins WG. Magnitude-based decisions. Sportscience. 2019;23:iiii.

  • 12.

    Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):313. PubMed ID: 19092709 doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Hopkins WG. A spreadsheet for monitoring an individual’s changes and trend. Sportscience. 2017;21:59.

  • 14.

    DeWeese BH, Hornsby G, Stone M, Stone MH. The training process: planning for strength-power training in track and field. Part 1: theoretical aspects. J Sport Health Sci. 2015;4(4):308317. doi:10.1016/j.jshs.2015.07.003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Mujika I, Halson S, Burke LM, Balagué G, Farrow D. An integrated, multifactorial approach to periodization for optimal performance in individual and team sports. Int J Sports Physiol Perform. 2018;13(5):538561. PubMed ID: 29848161 doi:10.1123/ijspp.2018-0093

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Loturco I, Winckler C, Kobal R, et al. Performance changes and relationship between vertical jump measures and actual sprint performance in elite sprinters with visual impairment throughout a Parapan American games training season. Front Physiol. 2015;6:323. PubMed ID: 26594181 doi:10.3389/fphys.2015.00323

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Saw AE, Main LC, Gastin PB. Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. Br J Sports Med. 2016;50(5):281291. PubMed ID: 26423706 doi:10.1136/bjsports-2015-094758

    • Crossref
    • Search Google Scholar
    • Export Citation
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