Download PDF
Int J Sports Med 2020; 41(04): 219-226
DOI: 10.1055/a-1065-2100
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Comparing Maximal Mean and Critical Speed and Metabolic Powers in Elite and Sub-elite Soccer

Cameron Lord 
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
,
Anthony John Blazevich
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
,
Chris Richard Abbiss
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
,
Eric James Drinkwater
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
2   Centre for Sport Research, Deakin University, Burwood, Australia
,
Fadi Ma’ayah
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
3   School of Education, Curtin University, Bentley, Australia
› Author Affiliations
Further Information

Publication History



accepted 07 November 2019

Publication Date:
22 January 2020 (online)

Also available at
    Permissions and Reprints

Abstract

The quantification of maximal mean speed (MMS), maximal mean metabolic power (MMPmet), critical speed (CS) and critical metabolic power (CPmet) was conducted over full A-League (elite) and National Premier League (NPL; sub-elite) seasons. Comparisons were made between levels of soccer competition and playing positions (i. e. centre backs, full backs, central midfielders, wide midfielders and strikers). A symmetric moving average algorithm was applied to the GPS raw data using specific time windows (i. e. 1, 5, 10, 60, 300 and 600 s) and maximal values were obtained. Additionally, these maximal values were used to derive estimates of CS and CPmet. Maximal mean values, particularly during smaller time windows (i. e. 1 and 5 s), were greater in A-League match play. Only MMPmet1 was identified as being consistently different between competitions (P=<0.001–0.049) in all playing positions. Significance was only observed in CS (P=0.005) and CPmet (P=0.005) of centre backs between competitions. Centre backs were identified as the least energy demanding playing position. The present findings suggests that both maximal mean and critical analyses are suitable alternatives to common absolute distance and speed assessments of match running performance during competitive matches.

Key words

global positioning systems - external work load - football - competition load
 

  • References

  • 1 Martin-Garcia A, Gomez Diaz A, Bradley PS. et al. Quantification of a professional football team's external load using a microcycle structure. J Strength Cond Res. 2018; DOI: 10.1519/JSC.0000000000002816.
    PubMedGoogle Scholar
  • 2 Ade J, Fitzpatrick J, Bradley PS. High-intensity efforts in elite soccer matches and associated movement patterns, technical skills and tactical actions. Information for position-specific training drills. J Sports Sci. 2016; 34: 2205-2214 doi:10.1080/02640414.2016.1217343
    PubMedGoogle Scholar
  • 3 Polglaze T, Dawson B, Buttfield A. et al. Metabolic power and energy expenditure in an international men’s hockey tournament. J Sports Sci. 2018; 36: 140-148 doi:10.1080/02640414.2017.1287933
    PubMedGoogle Scholar
  • 4 Bradley PS, Noakes TD. Match running performance fluctuations in elite soccer: Indicative of fatigue, pacing or situational influences?. J Sports Sci. 2013; 31: 1627-1638 doi:10.1080/02640414.2013.796062
    PubMedGoogle Scholar
  • 5 Abt G, Lovell R. The use of individualized speed and intensity thresholds for determining the distance run at high intensity in professional soccer. J Sports Sci. 2009; 27: 893-898 doi:10.1080/02640410902998239
    PubMedGoogle Scholar
  • 6 Dwyer DB, Gabbett TJ. Global positioning system data analysis: Velocity ranges and a new definition of sprinting for field sport athletes. J Strength Cond Res. 2012; 26: 818-824 doi:10.1519/JSC.0b013e3182276555
    PubMedGoogle Scholar
  • 7 Polglaze T, Hogan C, Dawson B. et al. Classification of intensity in team sport activity. Med Sci Sports Exerc. 2018; 50: 1487-1494 doi:10.1249/MSS.0000000000001575
    PubMedGoogle Scholar
  • 8 Lovell R, Abt G. Individualization of time-motion analysis: A case-cohort example. Int J Sports Physiol Perform 2013; 8: 456-458
    CrossrefPubMedGoogle Scholar
  • 9 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: 41-48 doi:10.1055/s-0034-1384547
    PubMedGoogle Scholar
  • 10 Carling C, Bradley P, McCall A. et al. Match-to-match variability in high-speed running activity in a professional soccer team. J Sports Sci. 2016; 34: 2215-2223 doi:10.1080/02640414.2016.1176228
    PubMedGoogle Scholar
  • 11 Bowen L, Gross AS, Gimpel M. et al. Accumulated workloads and the acute: Chronic workload ratio relate to injury risk in elite youth football players. Br J Sports Med. 2017; 51: 452-459 doi:10.1136/bjsports-2015-095820
    PubMedGoogle Scholar
  • 12 di Prampero PE, Fusi S, Sepulcri L. et al. Sprint running: A new energetic approach. J Exp Biol. 2005; 208: 2809-2816 doi:10.1242/jeb.01700
    PubMedGoogle Scholar
  • 13 Polglaze T, Dawson B, Peeling P. Gold standard or fool’s gold? The efficacy of displacement variables as indicators of energy expenditure in team sports. Sports Med. 2016; 46: 657-670 doi:10.1007/s40279-015-0449-x
    PubMedGoogle Scholar
  • 14 Vanhatalo A, Jones AM, Burnley M. Application of critical power in sport. Int J Sports Physiol Perform 2011; 6: 128-136
    CrossrefPubMedGoogle Scholar
  • 15 Clarke AC, Presland J, Rattray B. et al. Critical velocity as a measure of aerobic fitness in women's rugby sevens. J Sci Med Sport. 2014; 17: 144-148 doi:10.1016/j.jsams.2013.03.008
    PubMedGoogle Scholar
  • 16 Clark IE, West BM, Reynolds SK. et al. Applying the critical velocity model for an off-season interval training program. J Strength Cond Res. 2013; 27: 3335-3341 doi:10.1519/JSC.0b013e31828f9d87
    PubMedGoogle Scholar
  • 17 Galbraith A, Hopker J, Lelliott S. et al. A single-visit field test of critical speed. Int J Sports Physiol Perform. 2014; 9: 931-935 doi:10.1123/ijspp.2013-0507
    PubMedGoogle Scholar
  • 18 Jones AM, Vanhatalo A. The 'critical power' concept: Applications to sports performance with a focus on intermittent high-intensity exercise. Sports Med. 2017; 47: 65-78 doi:10.1007/s40279-017-0688-0
    PubMedGoogle Scholar
  • 19 Lord C, Blazevich AJ, Abbiss CR. et al. Reliability and validity of maximal mean and critical speed and metabolic power in Australian youth soccer players J Hum Kinet. 2019; DOI: 10.2478/hukin-2019-0135.
    PubMedGoogle Scholar
  • 20 Roecker K, Mahler H, Heyde C. et al. The relationship between movement speed and duration during soccer matches. PloS One 2017; 12: e0181781
    CrossrefPubMedGoogle Scholar
  • 21 Delaney JA, Thornton HR, Burgess DJ. et al. Duration-specific running intensities of Australian Football match-play. J Sci Med Sport. 2017; 20: 689-694 doi:10.1016/j.jsams.2016.11.009
    PubMedGoogle Scholar
  • 22 Malone S, Solan B, Hughes B. et al. Duration-specific running performance in elite Gaelic football. J Strength Cond Res. 2017; DOI: 10.1519/JSC.0000000000001972.
    PubMedGoogle Scholar
  • 23 Harriss DJ, Macsween A, Atkinson G. Standards for ethics in sport and exercise science research: 2020 update. Int J Sports Med. 2019; 40: 813-817
    PubMedGoogle Scholar
  • 24 Barr M, Beaver T, Turczyn D. et al. The validity and reliability of 15 Hz global positioning system units for assessing the activity profiles of university football players. J Strength Cond Res. 2019; 33: 1371-1379 doi:10.1519/JSC.0000000000002076
    PubMedGoogle Scholar
  • 25 Kempton T, Sirotic AC, Cameron M. et al. Match-related fatigue reduces physical and technical performance during elite rugby league match-play: A case study. J Sports Sci. 2013; 31: 1770-1780 doi:10.1080/02640414.2013.803583
    PubMedGoogle Scholar
  • 26 Hopkins WG. A scale of magnitudes for effect statistics. A new view of statistics. 2002
    PubMed
  • 27 Mallo J, Mena E, Nevado F. et al. Physical demands of top-class soccer friendly matches in relation to a playing position using global positioning system technology. J Hum Kinet. 2015; 47: 179-188 doi:10.1515/hukin-2015-0073
    PubMedGoogle Scholar
  • 28 Gaudino P, Iaia FM, Alberti G. et al. Monitoring training in elite soccer players: Systematic bias between running speed and metabolic power data. Int J Sports Med. 2013; 34: 963-968 doi:10.1055/s-0033-1337943
    PubMedGoogle Scholar
  • 29 Osgnach C, Poser S, Bernardini R. et al. Energy cost and metabolic power in elite soccer: A new match analysis approach. Med Sci Sports Exerc. 2010; 42: 170-178 doi:10.1249/MSS.0b013e3181ae5cfd
    PubMedGoogle Scholar