ORIGINAL PAPER
Players’ participation in team possessions of the 2014 FIFA® World Cup semi-finalists
1
América Futebol Clube, Belo Horizonte, Brazil
2
Universidade Federal de Viçosa, Viçosa, Brazil
3
Centre of Research and Studies in Soccer, Department of Physical Education, Universidade Federal de Viçosa, Viçosa, Brazil
Submission date: 2020-06-18
Acceptance date: 2020-10-04
Publication date: 2021-07-25
Hum Mov. 2022;23(1):44-49
KEYWORDS
TOPICS
ABSTRACT
Purpose:
In soccer, teammates are required to behave in a synchronized fashion to generate an effective unity. The study aim was to compare the number of players participating in team possessions of the 4 semi-finalists of the 2014 FIFA® World Cup.
Methods:
The sample of this observational study comprised 2372 team possessions of the 2014 FIFA® World Cup semifinalists (Germany, Argentina, the Netherlands, and Brazil). Descriptive analysis was performed, and the Kolmogorov-Smirnov normality test was applied. The Kruskal-Wallis and Mann-Whitney tests served to verify the overall and specific effects of the number of players participating in team possessions. Effect sizes were reported as Pearson’s r. The significance level was set at p < 0.05. The SPSS software version 22 was used for statistical procedures.
Results:
The tournament winners (Germany) displayed significantly higher means of the number of players per possession than the Netherlands and Brazil (U = 144.797; p < 0.001; small effect; and U = 158.501; p < 0.001; small effect, respectively), as did the runners-up, Argentina (U = 140.253; p = 0.012; negligible effect; and U = 154.226; p < 0.001; small effect, respectively). The Netherlands had a significantly higher mean number of players participating in team possessions than Brazil (U = 160.467; p = 0.014; negligible effect).
Conclusions:
The teams who reached the tournament final circulated the ball by using more players than those eliminated in the semi-finals. Future studies should verify the potential utilization of the number of players as an indicator of competitive success.
In soccer, teammates are required to behave in a synchronized fashion to generate an effective unity. The study aim was to compare the number of players participating in team possessions of the 4 semi-finalists of the 2014 FIFA® World Cup.
Methods:
The sample of this observational study comprised 2372 team possessions of the 2014 FIFA® World Cup semifinalists (Germany, Argentina, the Netherlands, and Brazil). Descriptive analysis was performed, and the Kolmogorov-Smirnov normality test was applied. The Kruskal-Wallis and Mann-Whitney tests served to verify the overall and specific effects of the number of players participating in team possessions. Effect sizes were reported as Pearson’s r. The significance level was set at p < 0.05. The SPSS software version 22 was used for statistical procedures.
Results:
The tournament winners (Germany) displayed significantly higher means of the number of players per possession than the Netherlands and Brazil (U = 144.797; p < 0.001; small effect; and U = 158.501; p < 0.001; small effect, respectively), as did the runners-up, Argentina (U = 140.253; p = 0.012; negligible effect; and U = 154.226; p < 0.001; small effect, respectively). The Netherlands had a significantly higher mean number of players participating in team possessions than Brazil (U = 160.467; p = 0.014; negligible effect).
Conclusions:
The teams who reached the tournament final circulated the ball by using more players than those eliminated in the semi-finals. Future studies should verify the potential utilization of the number of players as an indicator of competitive success.
REFERENCES (32)
1.
Gréhaigne J-F, Bouthier D, David B. Dynamic-system analysis of opponent relationships in collective actions in soccer. J Sports Sci. 1997;15(2):137–149; doi: 10.1080/026404197367416.
2.
McGarry T. Soccer as a dynamical system: some theoretical considerations. In: Reilly T, Cabri J, Araújo D (eds.), Science and football V: the proceedings of the Fifth World Congress on Science and Football. London: Routledge; 2005; 570–579.
3.
Silva P, Chung D, Carvalho T, Cardoso T, Davids K, Araújo D, et al. Practice effects on intra-team synergies in football teams. Hum Mov Sci. 2016;46:39–51; doi: 10.1016/j.humov.2015.11.017.
4.
Teoldo I, Guilherme J, Garganta J. Training football for smart playing: on tactical performance of teams and players. Curitiba: Appris; 2017.
5.
McGarry T. Applied and theoretical perspectives of performance analysis in sport: scientific issues and challenges. Int J Perform Anal Sport. 2009;9(1):128–140; doi: 10.1080/24748668.2009.11868469.
6.
Lemoine A, Jullien H. Study of the production of information in the context of the instantaneous transmission of the ball in football [in French]. J Rech Interv Educ Phys Sport. 2004;6:47–55.
7.
Dugrand M. Football, from transparency to complexity [in French]. Paris: Presses Universitaires de France; 1989.
8.
Lemoine A, Jullien H, Ahmaidi S. Technical and tactical analysis of one-touch playing in soccer – study of the production of information. Int J Perform Anal Sport. 2005;5(1):83–103; doi: 10.1080/24748668.2005.11868318.
9.
Lemoine A, Jullien H. Defensive play and patterns of play in football [in French]. J Rech Interv Educ Phys Sport. 2008;15:5–19; doi: 10.4000/ejrieps.5776.
10.
Praça GM, Folgado H, Pereira de Andrade AG, Greco PJ. Influence of additional players on collective tactical behavior in small-sided soccer games. Rev Bras Cineantropom Desempenho Hum. 2016;18(1):62–71; doi: 10.5007/1980-0037.2015v17n5p62.
11.
Padilha MB, Guilherme J, Serra-Olivares J, Roca A, Teoldo I. The influence of floaters on players’ tactical behaviour in small-sided and conditioned soccer games. Int J Perform Anal Sport. 2017;17(5):721–736; doi: 10.1080/24748668.2017.1390723.
12.
Moniz F, Scaglia A, Sarmento H, García-Calvo T, Teoldo I. Effect of an inside floater on soccer players tactical behaviour in small sided and conditioned games. J Hum Kinet. 2020;71(1):167–177; doi: 10.2478/hukin-2019-0080.
13.
Santos R, Duarte R, Davids K, Teoldo I. Interpersonal coordination in soccer: interpreting literature to enhance the representativeness of task design, from dyads to teams. Front Psychol. 2018;9:2550; doi: 10.3389/ fpsyg.2018.02550.
14.
McLean S, Salmon PM, Gorman AD, Naughton M, Solomon C. Do inter-continental playing styles exist? Using social network analysis to compare goals from the 2016 EURO and COPA football tournaments knockout stages. Theor Issues Ergon Sci. 2017;18(4):370–383; doi: 10.1080/1463922X.2017.1290158.
15.
Yi Q, Gómez MA, Wang L, Huang G, Zhang H, Liu H. Technical and physical match performance of teams in the 2018 FIFA World Cup: effects of two different playing styles. J Sports Sci. 2019;37(22):2569–2577; doi: 10.1080/02640414.2019.1648120.
16.
Preciado M, Anguera MT, Olarte M, Lapresa D. Observational studies in male elite football: a systematic mixed study review. Front Psychol. 2019;10:2077; doi: 10.3389/fpsyg.2019.02077.
17.
Garganta JM. Tactical modelling of a football game: a study of the organization of the offensive phase in high performance teams [in Portuguese]. Porto: Universidade do Porto; 1997.
18.
Cureton EE. Rank-biserial correlation. Psychometrika. 1956;21(3):287–290; doi: 10.1007/BF02289138.
19.
Cohen J. Statistical power analysis for the behavioral sciences, 2nd ed. New York: Lawrence Erlbaum Associates; 1988.
20.
Robinson G, O’Donoghue P. A weighted kappa statistic for reliability testing in performance analysis of sport. Int J Perform Anal Sport. 2007;7(1):12–19; doi: 10.1080/24748668.2007.11868383.
21.
Tabachnick BG, Fidell LS. Using multivariate statistics: international edition, 6th ed. London: Pearson Education; 2012.
22.
Clemente FM, Sarmento H, Praça GM, Nikolaidis PT, Rosemann T, Knechtle B. Variations of network centralities between playing positions in favorable and unfavorable close and unbalanced scores during the 2018 FIFA World Cup. Front Psychol. 2019;10:1802; doi: 10.3389/fpsyg.2019.01802.
23.
Sarmento H, Clemente FM, Gonçalves E, Harper LD, Dias D, Figueiredo A. Analysis of the offensive process of AS Monaco professional soccer team: a mixed-method approach. Chaos Soliton Fract. 2020;133:109676; doi: 10.1016/j.chaos.2020.109676.
24.
Reep C, Benjamin B. Skill and chance in association football. J R Stat Soc Ser A. 1968;131(4):581–585; doi: 10.2307/2343726.
25.
Hughes M, Franks I. Analysis of passing sequences, shots and goals in soccer. J Sports Sci. 2005;23(5):509–514; doi: 10.1080/02640410410001716779.
26.
Wallace JL, Norton KI. Evolution of World Cup soccer final games 1966–2010: game structure, speed and play patterns. J Sci Med Sport. 2014;17(2):223–228; doi: 10.1016/j.jsams.2013.03.016.
27.
Lago-Ballesteros J, Lago-Peñas C, Rey E. The effect of playing tactics and situational variables on achieving score-box possessions in a professional soccer team. J Sports Sci. 2012;30(14):1455–1461; doi: 10.1080/02640414.2012.712715.
28.
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–174; doi: 10.2307/2529310.
29.
Yi Q, Liu H, Nassis GP, Gómez M-Á. Evolutionary trends of players’ technical characteristics in the UEFA Champions League. Front Psychol. 2020;11:1032; doi: 10.3389/fpsyg.2020.01032.
30.
Aquino R, Garganta J, Manechini JPV, Bedo BLS, Puggina EF. Effects of match situational variables on possession: the case of England Premier League season 2015/16. Mot Rev Educ Fis. 2017;23(3):e101794; doi: 10.1590/S1980-6574201700030015.
31.
Alves DL, Osiecki R, Palumbo DP, Moiano-Junior JVM, Oneda G, Cruz R. What variables can differentiate winning and losing teams in the group and final stages of the 2018 FIFA World Cup? Int J Perform Anal Sport. 2019;19(2):248–257; doi: 10.1080/24748668.2019.1593096.
32.
Lord F, Pyne DB, Welvaert M, Mara JK. Methods of performance analysis in team invasion sports: a systematic review. J Sports Sci. 2020;38(20):2338–2349; doi: 10.1080/02640414.2020.1785185.
Share
RELATED ARTICLE
| eISSN: | 1899-1955 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
