The Dose–Response Relationship Between Training-Load Measures and Changes in Force–Time Components During a Countermovement Jump in Male Academy Soccer Players

in International Journal of Sports Physiology and Performance

Click name to view affiliation

Matthew EllisNewman University, Birmingham, United Kingdom

Search for other papers by Matthew Ellis in
Current site
Google Scholar
PubMed
Close
*
,
Tony MyersNewman University, Birmingham, United Kingdom

Search for other papers by Tony Myers in
Current site
Google Scholar
PubMed
Close
,
Richard TaylorCoventry University, Coventry, United Kingdom

Search for other papers by Richard Taylor in
Current site
Google Scholar
PubMed
Close
,
Rhys MorrisCoventry University, Coventry, United Kingdom

Search for other papers by Rhys Morris in
Current site
Google Scholar
PubMed
Close
, and
Ibrahim AkubatNewman University, Birmingham, United Kingdom

Search for other papers by Ibrahim Akubat in
Current site
Google Scholar
PubMed
Close
Restricted access

Purpose: To manage physical performance in soccer, practitioners monitor the training load (TL) and the resulting fatigue. A method frequently used to assess performance is the countermovement jump (CMJ). However, the efficacy of CMJ to detect fatigue from soccer matches and training remains uncertain, as does the relationship between TL and change in CMJ performance. The aims of the present study were 2-fold. One was to observe the changes of CMJ force–time components and jump height (JH). The second was to examine dose–response relationships between TL measures and CMJ over a 6-week preseason. Methods: Twelve male academy soccer players (17 [1] y, 71.2 [5.6] kg, and 178 [5.8] cm) were recruited. Daily changes in CMJ were assessed against baseline scores established before preseason training, along with internal and external TL measures. A series of Bayesian random intercept models were fitted to determine probability of change above/below zero and greater than the coefficient of variation established at baseline. Jumps were categorized into match day minus (MD−) categories where the higher number indicated more time from a competitive match. Results: JH was lowest on MD − 3 (28 cm) and highest on MD − 4 (34.6 cm), with the probability of change from baseline coefficient of variation highly uncertain (41% and 61%, respectively). Changes to force–time components were more likely on MD − 3 (21%–99%), which provided less uncertainty than JH. Bayes R2 ranged from .22 to .57 between TL measures and all CMJ parameters. Conclusions: Force–time components were more likely to change than JH. Practitioners should also be cautious when manipulating TL measures to influence CMJ performance.

Myers https://orcid.org/0000-0003-4516-4829

Ellis (m.ellis@newman.ac.uk) is corresponding author.

Supplementary Materials

    • Supplementary Tables S1 (PDF 344 KB)
    • Supplementary Tables S2 (PDF 348 KB)
  • Collapse
  • Expand
  • 1.

    Banister EW. Modeling elite athletic performance. In: MacDougall D, Wenger HA, Green HJ, eds. Physiological Testing of Elite Athletes. 2nd ed. Human Kinetics; 1991.

    • Search Google Scholar
    • Export Citation
  • 2.

    Enoka RM, Duchateau J. Translating fatigue to human performance. Med Sci Sports Exerc. 2016;48(11):22282238. doi:10.1249/MSS.0000000000000929

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

    Silva JR, Rumpf MC, Hertzog M, et al. Acute and residual soccer match-related fatigue: a systematic review and meta-analysis. Sports Med. 2018;48(3):539583. doi:10.1007/s40279-017-0798-8

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

    Rago V, Brito J, Figueiredo P, et al. Countermovement jump analysis using different portable devices: implications for field testing. Sports. 2018;6(3):91. doi:10.3390/sports6030091

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

    Hatze H. Validity and reliability of methods for testing vertical jumping performance. J Appl Biomech. 1998;14(2):127140. doi:10.1123/jab.14.2.127

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Vanrenterghem J, De Clercq D, Cleven PV. Necessary precautions in measuring correct vertical jumping height by means of force plate measurements. Ergonomics. 2001;44(8):814818. doi:10.1080/00140130118100

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

    McMahon JJ, Suchomel TJ, Lake JP, Comfort P. Understanding the key phases of the countermovement jump force-time curve. Strength Cond J. 2018;40(4):96106. doi:10.1519/SSC.0000000000000375

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

    Gathercole R, Sporer B, Stellingwerff T, Sleivert G. Alternative countermovement-jump analysis to quantify acute neuromuscular fatigue. Int J Sports Physiol Perform. 2015;10(1):8492. doi:10.1123/ijspp.2013-0413

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    Buckthorpe M, Morris J, Folland JP. Validity of vertical jump measurement devices. J Sports Sci. 2012;30(1):6369. doi:10.1080/02640414.2011.624539

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

    Ekblom B. Applied physiology of soccer. Sports Med. 1986;3(1):5060. doi:10.2165/00007256-198603010-00005

  • 11.

    Ispirlidis I, Fatouros IG, Jamurtas AZ, et al. Time-course of changes in inflammatory and performance responses following a soccer game. Clin J Sport Med. 2008;18(5):423431. doi:10.1097/JSM.0b013e3181818e0b

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Nedelec M, McCall A, Carling C, Legall F, Berthoin S, Dupont G. The influence of soccer playing actions on the recovery kinetics after a soccer match. J Strength Cond Res. 2014;28(6):15171523. doi:10.1519/JSC.0000000000000293

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

    Malone JJ, Murtagh CF, Morgans R, Burgess DJ, Morton JP, Drust B. Countermovement jump performance is not affected during an in-season training microcycle in elite youth soccer players. J Strength Cond Res. 2015;29(3):752757. doi:10.1519/JSC.0000000000000701

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Thorpe RT, Strudwick AJ, Buchheit M, Atkinson G, Drust B, Gregson W. The influence of changes in acute training load on daily sensitivity of morning-measured fatigue variables in elite soccer players. Int J Sports Physiol Perform. 2017;12(suppl 2):S2107S2113. doi:10.1123/ijspp.2016-0433

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

    Nicol C, Avela J, Komi PV. The stretch-shortening cycle. Sports Med. 2006;36(11):977999. doi:10.2165/00007256-200636110-00004

  • 16.

    Avela J, Komi PV. Reduced stretch reflex sensitivity and muscle stiffness after long-lasting stretch-shortening cycle exercise in humans. Eur J Appl Physiol Occup Physiol. 1998;78(5):403410. doi:10.1007/s004210050438

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

    Pasquet B, Carpentier A, Duchateau J, Hainaut K. Muscle fatigue during concentric and eccentric contractions. Muscle Nerve. 2000;23(11):17271735. doi:10.1002/1097-4598(200011)23:11<1727::AID-MUS9>3.0.CO;2-Y

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Los Arcos A, Martínez-Santos R, Yanci J, Mendiguchia J, Méndez-Villanueva A. Negative associations between perceived training load, volume and changes in physical fitness in professional soccer players. J Sports Sci Med. 2015;14(2):394401.

    • Search Google Scholar
    • Export Citation
  • 19.

    Papadakis L, Tymvios C, Patras K. Association of internal training load with changes in aerobic endurance and strength/power variables in professional soccer players during the preseason. Biol Exerc. 2019;15(1):19. doi:10.4127/jbe.2019.0153

    • Search Google Scholar
    • Export Citation
  • 20.

    Enes A, Oneda G, Alves DL, et al. Determinant factors of the match-based internal load in elite soccer players. Res Q Exerc Sport. 2021;92(1):6370. doi:10.1080/02701367.2019.1710445

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Alba-Jiménez C, Moreno-Doutres D, Peña J. Trends assessing neuromuscular fatigue in team sports: a narrative review. Sports. 2022;10(3):33. doi:10.3390/sports10030033

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Al Haddad H, Simpson BM, Buchheit M. Monitoring changes in jump and sprint performance: best or average values? Int J Sports Physiol Perform. 2015;10(7):931934. doi:10.1123/ijspp.2014-0540

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Owen NJ, Watkins J, Kilduff LP, Bevan HR, Bennett MA. Development of a criterion method to determine peak mechanical power output in a countermovement jump. J Strength Cond Res. 2014;28(6):15521558. doi:10.1519/JSC.0000000000000311

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Mundy PD, Lake JP, Carden PJ, Smith NA, Lauder MA. Agreement between the force platform method and the combined method measurements of power output during the loaded countermovement jump. Sports Biomech. 2016;15(1):2335. doi:10.1080/14763141.2015.1123761

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Edwards S. The Heart Rate Monitor Book. Polar Electro Oy; 1993.

  • 26.

    Lucia A, Hoyos J, Santalla A, Earnest C, Chicharro JL. Tour de France versus Vuelta a Espana: which is harder? Med Sci Sports Exerc. 2003;35(5):872878. doi:10.1249/01.MSS.0000064999.82036.B4

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Ellis M, Penny R, Wright B, Noon M, Myers T, Akubat I. The dose–response relationship between training-load measures and aerobic fitness in elite academy soccer players. Sci Med Footb. 2021;5(2):128136. doi:10.1080/24733938.2020.1817536

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109115.

  • 29.

    Manzi V, Bovenzi A, Impellizzeri MF, Carminati I, Castagna C. Individual training-load and aerobic-fitness variables in premiership soccer players during the precompetitive season. J Strength Cond Res. 2013;27(3):631636. doi:10.1519/JSC.0b013e31825dbd81

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    Akubat I, Patel E, Barrett S, Abt G. Methods of monitoring the training and match load and their relationship to changes in fitness in professional youth soccer players. J Sports Sci. 2012;30(14):14731480. doi:10.1080/02640414.2012.712711

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Newell J, Higgins D, Madden N, et al. Software for calculating blood lactate endurance markers. J Sports Sci. 2007;25(12):14031409. doi:10.1080/02640410601128922

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    Rampinini E, Alberti G, Fiorenza M, et al. Accuracy of GPS devices for measuring high-intensity running in field-based team sports. Int J Sports Med. 2015;36(1):4953.

    • Search Google Scholar
    • Export Citation
  • 33.

    Varley MC, Fairweather IH, Aughey RJ. Validity and reliability of GPS for measuring instantaneous velocity during acceleration, deceleration, and constant motion. J Sports Sci. 2012;30(2):121127. doi:10.1080/02640414.2011.627941

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    McElreath R. Statistical Rethinking: A Bayesian Course With Examples in R and Stan. Chapman and Hall/CRC; 2020.

  • 35.

    Lenth RV. emmeans: estimated marginal means, aka least-squares means. 2021 R package version 1.6.0. https://CRAN.R-project.org/package=emmeans

    • Search Google Scholar
    • Export Citation
  • 36.

    Lemoine NP. Moving beyond noninformative priors: why and how to choose weakly informative priors in Bayesian analyses. Oikos. 2019;128(7):912928. doi:10.1111/oik.05985

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 37.

    Bürkner P-C. brms: An R package for Bayesian multilevel models using Stan. J Stat Softw. 2017;80(1):128. doi:10.18637/jss.v080.i01

  • 38.

    Thorlund JB, Aagaard P, Madsen K. Rapid muscle force capacity changes after soccer match play. Int J Sports Med. 2009;30(4):273278. doi:10.1055/s-0028-1104587

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 39.

    Romagnoli M, Sanchis-Gomar F, Alis R, et al. Changes in muscle damage, inflammation, and fatigue-related parameters in young elite soccer players after a match. J Sports Med Phys Fitness. 2016;56(10):11981205.

    • Search Google Scholar
    • Export Citation
  • 40.

    Calvert TW, Banister EW, Savage MV, Bach T. A Systems Model of the Effects of Training on Physical Performance. IEEE; 1976.

All Time Past Year Past 30 Days
Abstract Views 1543 1543 33
Full Text Views 75 75 4
PDF Downloads 121 121 6