Dose–Response Relationship Between External Load and Wellness in Elite Women’s Soccer Matches: Do Customized Velocity Thresholds Add Value?

in International Journal of Sports Physiology and Performance
View More View Less
Restricted access

Purchase article

USD  $24.95

Student 1 year online subscription

USD  $112.00

1 year online subscription

USD  $149.00

Student 2 year online subscription

USD  $213.00

2 year online subscription

USD  $284.00

Purpose: To examine the dose–response relationship between match-play high-speed running (HSR), very high-speed running (VHSR), and sprint (SPR) distances versus subsequent ratings of fatigue and soreness. Methods: Thirty-six outfield players competing in the professional National Women’s Soccer League (NWSL, United States) with a minimum of five 90-minute match observations were monitored during the 2016 and 2017 seasons (408 match observations, 11 [6]/player). HSR (≥3.47 m·s−1), VHSR (≥5.28 m·s−1), and SPR (≥6.25 m·s−1) were determined generically (GEN) in players using a 10-Hz global positioning system. HSR, VHSR, and SPR speed thresholds were also reconfigured according to player peak speed per se and in combination with the final velocity achieved in the 30:15 Intermittent Fitness Test (locomotor approach to establishing individual speed zones). On the morning following matches (match day [MD + 1]), players recorded subjective wellness ratings of fatigue and soreness using 7-point Likert scales. Results: Fatigue (−2.32; 95% CI, −2.60 to −2.03 au; P < .0001) and soreness (−2.05; 95% CI, −2.29 to −1.81; P < .0001) ratings worsened on MD + 1. Standardized unit changes in HSRGEN (fatigue: −0.05; 95% CI, −0.11 to 0.02 and soreness: −0.02, 95% CI, −0.07 to 0.04) and VHSRGEN (fatigue: −0.06; 95% CI, −0.12 to 0.00 and soreness: −0.04; 95% CI, −0.10 to 0.02) had no influence on wellness ratings at MD + 1. Individualized speed thresholds did not improve the model fit. Conclusions: Subjective ratings of fatigue and wellness are not sensitive to substantial within-player changes in match physical performance. HSR, VHSR, and SPR thresholds customized for individual players’ athletic qualities did not improve the dose–response relationship between external load and wellness ratings.

Scott was with the US Soccer Federation, Chicago, IL, USA, at the time of the study. Norris and Lovell are with Western Sydney University, Penrith, NSW, Australia.

Lovell (R.Lovell@westernsydney.edu.au) is corresponding author.
  • 1.

    Buchheit M, Racinais S, Bilsborough JC, et al. Monitoring fitness, fatigue and running performance during a pre-season training camp in elite football players. J Sci Med Sport. 2013;16(6):550555. PubMed ID: 23332540 doi:10.1016/j.jsams.2012.12.003

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

    Thorpe RT, Strudwick AJ, Buchheit M, Atkinson G, Drust B, Gregson W. Tracking morning fatigue status across in-season training weeks in elite soccer players. Int J Sports Physiol Perform. 2016;11(7):947952. doi:10.1123/ijspp.2015-0490

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

    Gallo TF, Cormack SJ, Gabbett TJ, Lorenzen CH. Pre-training perceived wellness impacts training output in Australian football players. J Sports Sci. 2016;34(15):14451451. PubMed ID: 26637525 doi:10.1080/02640414.2015.1119295

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

    Govus AD, Coutts A, Duffield R, Murray A, Fullagar H. Relationship between pretraining subjective wellness measures, player load, and rating-of-perceived-exertion training load in American College Football. Int J Sports Physiol Perform. 2018;13(1):95101. doi:10.1123/ijspp.2016-0714

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

    Thorpe RT, Strudwick AJ, Buchheit M, Atkinson G, Drust B, Gregson W. Monitoring fatigue during the in-season competitive phase in elite soccer players. Int J Sports Physiol Perform. 2015;10(8):958964. doi:10.1123/ijspp.2015-0004

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

    Wellman AD, Coad SC, Flynn PJ, Climstein M, McLellan CP. Movement demands and perceived wellness associated with preseason training camp in NCAA division I college football players. J Strength Cond Res. 2017;31(10):27042718. PubMed ID: 28817504 doi:10.1519/JSC.0000000000002106

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

    Carling C, Bradley P, McCall A, Dupont G. Match-to-match variability in high-speed running activity in a professional soccer team. J Sports Sci. 2016;34(24):22152223. PubMed ID: 27144879 doi:10.1080/02640414.2016.1176228

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

    Fessi MS, Moalla W. Postmatch perceived exertion, feeling, and wellness in professional soccer players. Int J Sports Physiol Perform. 2018;13(5):631637. doi:10.1123/ijspp.2017-0725

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

    Brito J, Hertzog M, Nassis GP. Do match-related contextual variables influence training load in highly trained soccer players? J Strength Cond Res. 2016;30(2):393399. PubMed ID: 26244827 doi:10.1519/JSC.0000000000001113

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

    Hoppe MW, Slomka M, Baumgart C, Weber H, Freiwald J. Match running performance and success across a season in German Bundesliga soccer teams. Int J Sports Med. 2015;36(7):563566. PubMed ID: 25760152 doi:10.1055/s-0034-1398578

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

    Johnston RD, Gabbett TJ, Jenkins DG, Hulin BT. Influence of physical qualities on post-match fatigue in rugby league players. J Sci Med Sport. 2015;18(2):209213. PubMed ID: 24594214 doi:10.1016/j.jsams.2014.01.009

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

    Hunter F, Bray J, Towlson C, et al. Individualisation of time-motion analysis: a method comparison and case report series. Int J Sports Med. 2015;36(1):4148. PubMed ID: 25259591

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

    Lovell R, Abt G. Individualization of time-motion analysis: a case-cohort example. Int J Sports Physiol Perform. 2013;8(4):456458. doi:10.1123/ijspp.8.4.456

  • 14.

    Gabbett TJ. Use of relative speed zones increases the high-speed running performed in team sport match play. J Strength Cond Res. 2015;29(12):33533359. PubMed ID: 26020710 doi:10.1519/JSC.0000000000001016

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

    Scott D, Lovell R. Individualisation of speed thresholds does not enhance the dose-response determination in football training. J Sports Sci. 2018;36(13):15231532. PubMed ID: 29099673 doi:10.1080/02640414.2017.1398894

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

    Fitzpatrick JF, Hicks KM, Hayes PR. Dose–response relationship between training load and changes in aerobic fitness in professional youth soccer players. Int J Sports Physiol Perform. 2018;13(10):16.

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

    Rago V, Brito J, Figueiredo P, Krustrup P, Rebelo A. Relationship between external load and perceptual responses to training in professional football: effects of quantification method. Sports (Basel). 2019;7(3):68. doi:10.3390/sports7030068

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

    Mendez-Villanueva A, Buchheit M, Simpson B, Bourdon PC. Match play intensity distribution in youth soccer. Int J Sports Med. 2013;34(2):101110. PubMed ID: 22960988

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Buchheit M. The 30–15 intermittent fitness test: accuracy for individualizing interval training of young intermittent sport players. J Strength Cond Res. 2008;22(2):365374. PubMed ID: 18550949 doi:10.1519/JSC.0b013e3181635b2e

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Akenhead R, Nassis GP. Training load and player monitoring in high-level football: current practice and perceptions. Int J Sports Physiol Perform. 2016;11(5):587593. doi:10.1123/ijspp.2015-0331

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

    Park LAF, Scott D, Lovell R. Velocity zone classification in elite women’s football: where do we draw the lines? Sci Med Football. 2019;3(1):2128. doi:10.1080/24733938.2018.1517947

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

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

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

    Wagenmakers E-J, Farrell S. AIC model selection using Akaike weights. Psychon Bull Rev. 2004;11(1):192196. PubMed ID: 15117008 doi:10.3758/BF03206482

  • 24.

    Nakagawa S, Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol. 2012;4(2):133142. doi:10.1111/j.2041-210x.2012.00261.x

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

    Johnson PCD. Extension of Nakagawa & Schielzeth’s R2 GLMM to random slopes models. Methods Ecol Evol. 2014;5(9):944946. PubMed ID: 25810896 doi:10.1111/2041-210X.12225

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Fanchini M, Ferraresi I, Modena R, Schena F, Coutts AJ, Impellizzeri FM. Use of CR100 scale for session rating of perceived exertion in soccer and its interchangeability with the CR10. Int J Sports Physiol Perform. 2016;11(3):388392. doi:10.1123/ijspp.2015-0273

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

    Weston M, Siegler J, Bahnert A, McBrien J, Lovell R. The application of differential ratings of perceived exertion to Australian Football League matches. J Sci Med Sport. 2015;18(6):704708. PubMed ID: 25241705 doi:10.1016/j.jsams.2014.09.001

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

    O’Connor F, Thornton HR, Ritchie D, et al. Greater association of relative thresholds than absolute thresholds with noncontact lower-body injury in professional Australian rules footballers: implications for sprint monitoring. Int J Sports Physiol Perform. 2020;15(2):204212. PubMed ID: 31094252 doi:10.1123/ijspp.2019-0015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Oosthuyse T, Bosch AN. The effect of gender and menstrual phase on serum creatine kinase activity and muscle soreness following downhill running. Antioxidants (Basel). 2017;6(1):16. doi:10.3390/antiox6010016

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 271 271 123
Full Text Views 30 30 5
PDF Downloads 17 17 5