Acta Gymnica e2021.003 | DOI: 10.5507/ag.2021.003

High-intensity activity according to playing position with different team formations in soccer

Javier J. Vilamitjana1, Gabriel Heinze2, Pablo Verde3, Julio Calleja-González4
1 Soccer Research Group, Friends Club - CDA, Buenos Aires, Argentina
2 Sports and Cultural Association of Crespo, Crespo, Argentina
3 Coordination Centre of Clinical Trials, University of Dusseldorf, Dusseldorf, Germany
4 Physical Activity and Sports Sciences, University of the Basque Country - UPV/EHU, Leioa, Spain

Background: A tactical factor such as playing formation seems to be another influencing factor in the physical performance of elite soccer players during the match. Some researchers have suggested that distances covered during high-intensity running in matches are valid measures of physical performance. They concluded that players covered greater distances of high-intensity activities during some team formations in comparison to others.

Objective: The aim of this study was to examine high-intensity patterns of professional soccer players in relation to the positional role with two different playing formations.

Methods: Match data were collected during official games systematically playing in 1-3-4-3 and 1-4-2-1-3 formations. Nineteen professional players (age 24.7 ± 4.8 years, body mass 74.5 ± 6.2 kg, height 176.3 ± 5.3 cm, percentage of body fat 9.7 ± 2.5%) were classified into five positional roles: central defender, wide defender, midfielder, wing and forward. Match performance variables included moderate-intensity running (14.9-19.8 km/h), high-speed running (19.9-25.2 km/h) and sprinting (> 25.2 km/h). The number of runs (#HSR, #SPR) and metabolic rates as HILR ([MIR + HSR + SPR]/min) and HSSL ([HSR + SPR]/min) were determined.

Results: The statistical analysis revealed that #SPR (p = .045), HILR (p = .022) and HSSL (p = .019) were higher in 1-4-2-1-3 than 1-3-4-3 formation. According to the playing position, significant differences were found in HILR (p = .045) and HSSL (p = .028) for forwards during 1-4-2-1-3 and midfielders amounted more HILR than others in that team formation (p = .047). Additionally, wings amounted significantly higher #HSR (p = .011) and #SPR (p = .010) in 1-4-2-1-3, as long as forwards was the other position with more #SPR during that formation (p = .023).

Conclusions: The players performed more high-intensity patterns in 1-4-2-1-3. Attackers and midfielders were the playing positions that held the most statistical differences comparing both team formations. These findings reveal that playing formation seems to be another potential factor of influence with respect to the physical performance of elite players if we consider their high-intensity profile in particular.

Keywords: professional soccer player, tactical formation, positional role, match demands analysis, high-intensity patterns, sprinting performance

Received: August 6, 2020; Revised: January 29, 2021; Accepted: February 9, 2021; Published online: March 29, 2021  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Vilamitjana, J.J., Heinze, G., Verde, P., & Calleja-González, J. (2021). High-intensity activity according to playing position with different team formations in soccer. Acta Gymnica51, Article e2021.003. https://doi.org/10.5507/ag.2021.003
Download citation

References

  1. Alexandre, D., Da Silva, C. D., Hill-Haas, S., Wong, D. P., Natali, A. J., De Lima, J. R. P., Filho, M. G. B. B., Marins, J. J. C. B., García, E. S., & Karim, C. (2012). Heart rate monitoring in soccer: Interest and limits during competitive match play and training, practical application. Journal of Strength and Conditioning Research, 26(10), 2890-2906. https://doi.org/10.1519/JSC.0b013e3182429ac7 Go to original source... Go to PubMed...
  2. Andrzejewski, M., Chmura, J., Pluta, B., & Konarski, J. (2015). Sprinting activities and distance covered by top level Europa League soccer players. International Journal of Sports Science & Coaching, 10(1), 39-50. https://doi.org/10.1260/1747-9541.10.1.39 Go to original source...
  3. Aquino, R., Palucci Vieira, L. H., Carling, C., Martins, G. G. H. M., Alves, I. S., & Puggina, E. F. (2017). Effects of competitive standard, team formation and playing position on match running performance of Brazilian professional soccer players. International Journal of Performance Analysis in Sports, 17(5), 695-705. https://doi.org/10.1080/24748668.2017.1384976 Go to original source...
  4. Bangsbo, J., & Peitersen, B. (2000). Soccer systems and strategies. Human Kinetics.
  5. Bradley, P. S., Carling, C., Archer, D., Roberts, J., Dodds, A., Di Mascio, M., Paul, D., Gomez Diaz, A., Peart, D., & Krustrup, P. (2011). The effect of playing formation on high intensity running and technical profiles in English FA Premier League soccer matches. Journal of Sports Sciences, 29(8), 821-830. https://doi.org/10.1080/02640414.2011.561868 Go to original source... Go to PubMed...
  6. Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., & Krustrup, P. (2009). High-intensity running in English FA Premier League soccer matches. Journal of Sports Sciences, 27(2), 159-168. https://doi.org/10.1080/02640410802512775 Go to original source... Go to PubMed...
  7. Brooks, K. A., Carter, J. G., & Dawes, J. J. (2013). Comparison of VO2 measurement obtained by a physiological monitoring device and the Cosmed Quark CPET. Journal of Novel Physiotherapies, 3, Article 126. https://doi.org/10.4172/2165-7025.1000126 Go to original source... Go to PubMed...
  8. Bush, M., Barnes, C., Archer, D. T., Hogg, B., & Bradley, P. S. (2015) Evolution of match performance parameters for various playing positions in the English Premier League. Human Movement Science, 39, 1-11. https://doi.org/10.1016/j.humov.2014.10.003 Go to original source... Go to PubMed...
  9. Di Salvo, V., Gregson, W., Atkinson, G., Tordoff, P., & Drust, B. (2009). Analysis of high intensity activity in Premier League soccer. International Journal of Sports Medicine, 30(3), 205-212. https://doi.org/10.1055/s-0028-1105950 Go to original source... Go to PubMed...
  10. Di Salvo, V., Pigozzi, F., González-Haro, C., Laughlin, M. S., & De Witt, K. (2013). Match performance comparison in top English soccer leagues. International Journal of Sports Medicine, 34(6), 526-532. https://doi.org/10.1055/s-0032-1327660 Go to original source... Go to PubMed...
  11. Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press. Go to original source...
  12. Jackson, A. S., & Pollock, M. L. (1978). Generalized equations for predicting body density of men. British Journal of Nutrition, 40(3), 497-504. https://doi.org/10.1079/BJN19780152 Go to original source... Go to PubMed...
  13. Jaspers, A., Brink, M. S., Probst, S. G. M., Frencken, W. G. P., & Helsen, W. (2017). Relationships between training load indicators and training outcomes in professional soccer. Sports Medicine, 47, 533-544. https://doi.org/10.1007/s40279-016-0591-0 Go to original source... Go to PubMed...
  14. Kim, J.-H., Roberge, R., Powell, J. B., Shafer, A. B., & Williams, W. J. (2013). Measurement accuracy of heart rate and respiratory rate during graded exercise and sustained exercise in the heat using the Zephyr BioHarness. International Journal of Sports Medicine, 34(6), 497-501. https://doi.org/10.1055/s-0032-1327661 Go to original source... Go to PubMed...
  15. Krustrup, P., Mohr, M., Amstrup, T., Rysgaard, T., Johansen, J., Steensberg, J., Pedersen, P. K., & Bangsbo, J. (2003). The Yo-Yo intermittent recovery test: Physiological response, reliability, and validity. Medicine & Science in Sports & Exercise, 35(4), 697-705. https://doi.org/10.1249/01.MSS.0000058441.94520.32 Go to original source... Go to PubMed...
  16. Krustrup, P., Mohr, M., Ellingsgaard, H., & Bangsbo, J. (2005) Physical demands of elite female soccer games: Importance of training status. Medicine & Science in Sports & Exercise, 37(7), 1242-1248. https://doi.org/10.1249/01.mss.0000170062.73981.94 Go to original source... Go to PubMed...
  17. McGilchrist, C. A., & Yau, K. K. W. (2007). The derivation of BLUP, ML, REML estimation methods for generalized linear mixed models. Communications in Statistics - Theory and Methods, 24(12), 2963-2980. https://doi.org/10.1080/03610929508831663 Go to original source...
  18. Mohr, M., Krustrup, P., & Bangsbo, J. (2003). Match performance of high-standard soccer players with special reference to development of fatigue. Journal of Sports Sciences, 21(7), 519-528. https://doi.org/10.1080/0264041031000071182 Go to original source... Go to PubMed...
  19. Tierney, P. J., Young, A., Clarke, N. D., & Duncan, M. J. (2016). Match play demands of 11 versus 11 professional football using Global Positioning System tracking: Variations across common playing formations. Human Movement Science, 49, 1-8. https://doi.org/10.1016/j.humov.2016.05.007 Go to original source... Go to PubMed...
  20. Vilamitjana, J., Heinze, G., Verde, P., & Calleja-González, J. (2020). Comparison of physical performance between possession games and matches in professional football. Apunts. Educación Física y Deportes, 141, 75-86. https://doi.org/10.5672/apunts.2014-0983.es.(2020/3).141.09 Go to original source...

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.