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Original Article

Defining Velocity and Acceleration Ranges for Time–Motion Analysis from a 7-Sided Game in U11 Soccer Players Using Global Positioning System Devices: A Case Study

Abd-Elbasset Abaïdia1 (), Grégory Dupont2, Georges Baquet1
Université de Lille, EA 7369-URePSSS-Unité de Recherche Pluridisciplinaires Sport Santé Société, 59000 Lille, France
Research Institute for Sport and Exercise Sciences Liverpool John Moores University, Liverpool, UK
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Abstract

The aims of this study were (1) to define speed and acceleration thresholds from youth match activity of soccer players and (2) to analyze the activity performed by young soccer players during a match using GPS devices and according to these thresholds. Ten U11 soccer players from a professional club participated in a 7-sided match being equipped with global positioning system (GPS) devices (sampling frequency 5 Hz) to measure the speed of each player. The Kernel Density Estimate (KDE) was used to observe the occurrences of velocities. The range of velocities was described by a distribution curve, from which the speed and acceleration thresholds for each category of movement were defined and time–motion analysis of the match was made. The model with 4 Gaussian laws was the best when using the Akaike Information Criterion (AIC). In this study, the thresholds defined for each category of movement were: standing (< 0.1 km/h), walking (0.1–5.6 km/h), slow running (5.7–7.7 km/h), fast running (7.8–12.7 km/h) and sprint (≥ 12.8 km/h). Acceleration thresholds were calculated to define movement considered as a sprint for each category of movement: standing (0.3 m/s2), walking (0.66 m/s2), slow running (1.01 m/s2) or fast running (0.97 m/s2). All the acceleration thresholds were significantly different from each other (P < 0.001) with large effect sizes, excepting the comparison between slow and fast running (P = 0.41) with a small effect size. In U-11 soccer players, time–motion analysis may be performed according to five categories of movement. This study has also defined sprint and acceleration thresholds for this category of age.

Keywords

FootballSprintAccelerationsMovementYouth

References

1

Abbott W, Brickley G, Smeeton NJ, Mills S. Individualizing acceleration in english premier league academy soccer players. J Strength Cond Res. 2018;32(12):3503–10.

Crossref Google Scholar
2

Ade JD, Harley JA, Bradley PS. Physiological response, time-motion characteristics, and reproducibility of various speed-endurance drills in elite youth soccer players: small-sided games versus generic running. Int J Sports Physiol Perform. 2014;9(3):471–9.

Crossref Google Scholar
3

Akenhead R, Hayes PR, Thompson KG, French D. Diminutions of acceleration and deceleration output during professional football match play. J Sci Med Sport. 2013;16(6):556–61.

Crossref Google Scholar
4

Andrzejewski M, Chmura Y, Pluta B, Kasprzak A. Analysis of motor activities of professional soccer players. J Strength Cond Res. 2012;26(6):1481–8.

Crossref Google Scholar
5

Barros RML, Misuta MS, Menezes RP, Figueroa PJ, Moura FA, Cunha SA, Anido R, Leite NJ. Analysis of the distances covered by first division Brazilian soccer players obtained with an automatic tracking method. J Sports Sci Med. 2007;6:233–42.

Google Scholar
6

Bradley PS, Sheldon W, Wooster B, Olsen P, Boanas P, Krustrup P. High-intensity running in English FA Premier League soccer matches. J Sports Sci. 2009;27(2):159–68.

Crossref Google Scholar
7

Buchheit M, Mendez-Villanueva A, Simpson BM, Bourdon PC. Match running performance and fitness in youth soccer. Int J Sports Med. 2010;31(11):818–25.

Crossref Google Scholar
8

Burgess DJ, Naughton G, Norton KI. Profile of movement demands of national football players in Australia. J Sci Med Sport. 2006;9:334–434.

Crossref Google Scholar
9

Carling C. Interpreting physical performance in professional soccer match-play: should we be more pragmatic in our approach? Sports Med. 2013;43(8):655–63.

Crossref Google Scholar
10

Carling C, Bloomfield J, Nelsen L, Reilly T. The role of motion analysis in elite soccer: contemporary performance measurement techniques and work rate data. Sports Med. 2008;38(10):839–62.

Crossref Google Scholar
11

Carling C, Le Gall F, Dupont G. Analysis of repeated high-intensity running performance in professional soccer. J Sports Sci. 2012;30(4):325–36.

Crossref Google Scholar
12

Castellano J, Blanco-Villaseñor A, Alvarez D. Contextual variables and time-motion analysis in soccer. Int J Sports Med. 2011;32:415–21.

Crossref Google Scholar
13

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(3):818–24.

Crossref Google Scholar
14

Gabett TJ, Muvley MJ. Time-motion analysis of small-sided training games and competition in elite women soccer players. J Strength Cond Res. 2008;22(2):543–52.

Crossref Google Scholar
15

Goto H, Morris JG, Nevill ME. Motion analysis of U11 to U16 elite English Premier League Academy players. J Sports Sci. 2015;33(12):1248–58.

Crossref Google Scholar
16

Harley JA, Barnes CA, Portas M, Lovell R, Barrett S, Paul D, Weston M. Motion analysis of match-play in elite U12 to U16 age-group soccer players. J Sports Sci. 2010;28(13):1391–7.

Crossref Google Scholar
17

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):3–13.

Crossref Google Scholar
18

Krustrup P, Mohr M, Steensberg A, Bencke J, Kjaer M, Bangsbo J. Muscle and blood metabolites during a soccer game: implications for sprint performance. Med Sci Sports Exerc. 2006;38(6):1165–74.

Crossref Google Scholar
19

Martínez-Cabrera FI, Núñez-Sánchez FJ, Losada J, Otero-Esquina C, Sánchez H, De Hoyo M. Use of individual relative thresholds to assess acceleration in young soccer players according to initial speed. J Strength Cond Res. 2021;35(4):1110–8.

Crossref Google Scholar
20

Mohr M, Krustrup P, Bangsbo J. Match performance of high-standard soccer players with special reference to development of fatigue. J Sports Sci. 2003;21(7):519–28.

Crossref Google Scholar
21

Mujika I, Spencer M, Santisteban J, Goiriena JJ, Bishop D. Age-related differences in repeated-sprint ability in highly trained youth football players. J Sports Sci. 2009;27(14):1581–90.

Crossref Google Scholar
22

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):1517–23.

Crossref Google Scholar
23

Osgnach C, Poser S, Bernardini R, Rinaldo R, di Prampero PE. Energy cost and metabolic power in elite soccer: a new match analysis approach. Med Sci Sports Exerc. 2010;42(1):170–8.

Crossref Google Scholar
24

Page P. Beyond statistical significance: clinical interpretation of rehabilitation research literature. Int J Sports Phys Ther. 2014;9(5):726–36.

Google Scholar
25

Palucci Vieira LH, Carling C, Barbieri FA, Aquino R, Santiago PRP. Match running performance in young soccer players: a systematic review. Sports Med. 2019;49(2):289–318.

Crossref Google Scholar
26

Rampinini E, Coutts AJ, Castagna C, Sassi R, Impellizzeri FM. Variation in top level soccer match performance. Int J Sports Med. 2007;28(12):1018–24.

Crossref Google Scholar
27

Randers MB, Mujika I, Hewitt A, Santisteban J, Bischoff R, Solano R, Zubillaga A, Peltola E, Krustrup P, Mohr M. Application of four different football match analysis systems: a comparative study. J Sports Sci. 2010;28(2):171–82.

Crossref Google Scholar
28

Di Salvo V, Baron R, Tschan H, Calderon Montero FJ, Bachl N, Pigozzi F. Performance characteristics according to playing position in elite soccer. Int J Sports Med. 2007;28(3):222–7.

Crossref Google Scholar
29

Scott MT, Scott TJ, Kelly VG. The validity and reliability of global positioning systems in team sport: a brief review. J Strength Cond Res. 2016;30(5):1470–90.

Crossref Google Scholar
30

Stølen T, Chamari K, Castagna C, Wisløff U. Physiology of soccer: an update. Sports Med. 2005;35(6):501–36.

Crossref Google Scholar
31

Teixeira JE, Forte P, Ferraz R, Leal M, Ribeiro J, Silva AJ, Barbosa TM, Monteiro AM. Monitoring accumulated training and match load in football: a systematic review. Int J Environ Res Public Health. 2021;18(8):3906.

Crossref Google Scholar
32

Teixeira JE, Forte P, Ferraz R, Leal M, Ribeiro J, Silva AJ, Barbosa TM, Monteiro AM. Quantifying sub-elite youth football weekly training load and recovery variation. Appl Sci. 2021;11(11):4871.

Crossref Google Scholar
33

Teixeira JE, Leal M, Ferraz R, Ribeiro J, Cachada JM, Barbosa TM, Monteiro AM, Forte P. Effects of match location, quality of opposition and match outcome on match running performance in a Portuguese professional football team. Entropy. 2021;23(8):973.

Crossref Google Scholar
34

Waldron M, Twist C, Highton J, Worsfold P, Daniels M. Movement and physiological match demands of elite rugby league using portable global positioning systems. J Sports Sci. 2011;29(11):1223–30.

Crossref Google Scholar
Journal of Science in Sport and Exercise
Volume 5 Issue 2,
May 2023
Pages 167-173
DOI: 10.1007/s42978-022-00174-0
Cite this article:
Abaïdia A-E, Dupont G, Baquet G. Defining Velocity and Acceleration Ranges for Time–Motion Analysis from a 7-Sided Game in U11 Soccer Players Using Global Positioning System Devices: A Case Study. Journal of Science in Sport and Exercise, 2023, 5(2): 167-173. https://doi.org/10.1007/s42978-022-00174-0
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