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A Systematic Review of Collective Tactical Behaviours in Football Using Positional Data

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Abstract

Background

Performance analysis research in association football has recently cusped a paradigmatic shift in the way tactical behaviours are studied. Based on insights from system complexity research, a growing number of studies now analyse tactical behaviours in football based on the collective movements of team players.

Objective

The aim of this systematic review is to provide a summary of empirical research on collective tactical behaviours in football, with a particular focus on organising the methods used and their key findings.

Methods

A systematic search of relevant English-language articles was performed on one database (Web of Science Core Collection) and one search engine (PubMed), based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. The keywords ‘football’ and ‘soccer’ were each paired with all possible combinations of the following keywords: ‘collective movement behaviour’, ‘collective behaviour’, ‘tactical behaviour’, ‘interpersonal coordination’, ‘space’, ‘Voronoi’, ‘synchronisation’, ‘tactical analysis’, ‘constraints’, ‘ecological dynamics’, and ‘dynamic positioning’. Empirical studies that were related to tactical analyses of footballers’ positional data were sought for inclusion and analysis.

Results

Full-text articles of 77 studies were reviewed. A total of 27 tactical variables were identified, which were subsequently organised into 6 categories. In addition to conventional methods of linear analysis, 11 methods of nonlinear analysis were also used, which can be organised into measures of predictability (4 methods) and synchronisation (7 methods). The key findings of the reviewed studies were organised into two themes: levels of analysis, and levels of expertise.

Conclusions

Some trends in key findings revealed the following collective behaviours as possible indicators of better tactical expertise: higher movement regularity; wider dispersion in youth players and shorter readjustment delay between teammates and opponents. Characteristic behaviours were also observed as an effect of playing position, numerical inequality, and task constraints. Future research should focus on contextualising positional data, incorporating the needs of coaching staff, to better bridge the research-practice gap.

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References

  1. Di Salvo V, Collins A, McNeill B, Cardinale M. Validation of Prozone®: a new video-based performance analysis system. Int J Perf Anal Spor. 2006;6:1.

    Google Scholar 

  2. Memmert D, Rein R. Match analysis, Big Data and tactics: current trends in elite soccer. German J Sport Med. 2018;69:65–72.

    Google Scholar 

  3. Castellano J, Alvarez-Pastor D, Bradley PS. Evaluation of research using computerised tracking systems (Amisco® and Prozone®) to analyse physical performance in elite soccer: a systematic review. Sports Med. 2014;44(5):701–12.

    Article  PubMed  Google Scholar 

  4. Barris S, Button C. A review of vision-based motion analysis in sport. Sports Med. 2008;38(12):1025–43.

    Article  PubMed  Google Scholar 

  5. Coutts AJ, Duffield R. Validity and reliability of GPS devices for measuring movement demands of team sports. J Sci Med Sport. 2010;13(1):133–5.

    Article  PubMed  Google Scholar 

  6. Aughey RJ. Applications of GPS technologies to field sports. Int J Sports Physiol Perform. 2011;2011(6):295–310.

    Article  Google Scholar 

  7. Jennings D, Cormack S, Coutts AJ, Boyd LJ, Aughey RJ. Variability of GPS units for measuring distance in team sport movements. Int J Sports Physiol Perform. 2010;5(4):565–9.

    Article  PubMed  Google Scholar 

  8. Castellano J, Casamichana D, Calleja-González J, Román JS, Ostojic SM. Reliability and accuracy of 10 Hz GPS devices for short-distance exercise. J Sports Sci Med. 2011;10(1):233–4.

    PubMed  PubMed Central  Google Scholar 

  9. Frencken WG, Lemmink KA, Delleman NJ. Soccer-specific accuracy and validity of the local position measurement (LPM) system. J Sci Med Sport. 2010;13(6):641–5.

    Article  PubMed  Google Scholar 

  10. Sathyan T, Shuttleworth R, Hedley M, Davids K. Validity and reliability of a radio positioning system for tracking athletes in indoor and outdoor team sports. Behav Res Methods. 2012;44(4):1108–14.

    Article  PubMed  Google Scholar 

  11. 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.

    Article  PubMed  Google Scholar 

  12. Memmert D, Lemmink KAPM, Sampaio J. Current approaches to tactical performance analyses in soccer using position data. Sports Med. 2017;47(1):1–10.

    Article  PubMed  Google Scholar 

  13. Rein R, Memmert D. Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science. Springerplus. 2016;5(1):1410.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Sarmento H, Clemente FM, Araújo D, Davids K, McRobert A, Figueiredo A. What performance analysts need to know about research trends in association football (2012–2016): a systematic review. Sports Med. 2018;48(4):799–836.

    Article  PubMed  Google Scholar 

  15. Rein R, Perl R, Memmert D. Maybe a tad early for a Grand Unified theory: Commentary on “Towards a Grand Unified Theory of sports performance” by Paul S. Glazier. Hum Move Sci. 2017;56:173–5.

    Article  Google Scholar 

  16. Lames M, McGarry T. On the search for reliable performance indicators in game sports. Int J Perform Anal Sport. 2007;7(1):62–79.

    Article  Google Scholar 

  17. Davids K, Araújo D, Shuttleworth R. Applications of dynamical systems theory to football. Sci Footb. 2005;537:550.

    Google Scholar 

  18. McGarry T, Anderson DI, Wallace SA, Hughes MD, Franks IM. Sport competition as a dynamical self-organizing system. J Sports Sci. 2002;20(10):771–81.

    Article  PubMed  Google Scholar 

  19. Glazier PS. Game, set and match? Substantive issues and future directions in performance analysis. Sports Med. 2010;40(8):625–34.

    Article  PubMed  Google Scholar 

  20. Grehaigne JF, Bouthier D, David B. Dynamic-system analysis of opponent relationships in collective actions in soccer. J Sports Sci. 1997;15(2):137–49.

    Article  CAS  PubMed  Google Scholar 

  21. Garganta J. Trends of tactical performance analysis in team sports: bridging the gap between research, training and competition. Revista Portuguesa de Ciências do Desporto. 2009;9:81–9.

    Article  Google Scholar 

  22. Perl J, Memmert D. Soccer: Process and interaction. In: Baca A, Perl J (eds) Modelling and simulation in sport and exercise, 2018; Abingdon: Routledge pp. 73–94.

  23. Gréhaigne J-F, Godbout P. Collective variables for analysing performance in team sports. Routledge handbook of sports performance analysis. Abingdon: Routledge; 2013.

    Google Scholar 

  24. Duarte R, Araújo D, Correia V, Davids K. Sports teams as superorganisms. Sports Med. 2012;42(8):633–42.

    Article  PubMed  Google Scholar 

  25. Newell KM. Constraints on the development of coordination. In: Wade MG, Whiting HTA, editors. Motor development in children: aspects of coordination and control. Dordrecht: Martinus Nijhoff Publishers; 1986. p. 341–60.

    Chapter  Google Scholar 

  26. Travassos B, Davids K, Araújo D, Esteves PT. Performance analysis in team sports: advances from an ecological dynamics approach. Int J Perform Anal Sport. 2013;13(1):83–95.

    Article  Google Scholar 

  27. Davids K, Araujo D, Vilar L, Renshaw I, Pinder R. An ecological dynamics approach to skill acquisition: implications for development of talent in sport. Talent Dev Excell. 2013;5(1):21–34.

    Google Scholar 

  28. Araújo D, Davids K, Hristovski R. The ecological dynamics of decision making in sport. Psychol Sport Exerc. 2006;7(6):653–76.

    Article  Google Scholar 

  29. Vilar L, Araujo D, Davids K, Button C. The role of ecological dynamics in analysing performance in team sports. Sports Med. 2012;42(1):1–10.

    Article  PubMed  Google Scholar 

  30. Gibson J. The ecological approach to visual perception. Dallas: Houghtom Mifflin; 1979.

    Google Scholar 

  31. Fajen BR, Riley MA, Turvey MT. Information, affordances, and the control of action in sport. Int J Sport Psychol. 2009;40(1):79.

    Google Scholar 

  32. Gréhaigne J-F, Godbout P, Bouthier D. The foundations of tactics and strategy in team sports. J Teach Phys Educ. 1999;18(2):159–74.

    Article  Google Scholar 

  33. Gréhaigne J-F, Godbout P. Tactical knowledge in team sports from a constructivist and cognitivist perspective. Quest. 1995;47(4):490–505.

    Article  Google Scholar 

  34. Hibbs A, O’Donoghue P. Strategy and Tactics in sports performance. Routledge handbook of sports performance analysis. Abingdon: Routledge; 2013.

    Google Scholar 

  35. Memmert D, König S. Models of game intelligence and creativity in sport: Implications for skill acquisition. In: Hodges NJ, Williams AM, editors. Skill acquisition in sport: Research, theory and practice. 3 ed. Abingdon: Routledge; 2019. p. 220–36.

  36. Gibson JJ. The senses considered as perceptual systems. Oxford, England: Houghton Mifflin; 1966.

    Google Scholar 

  37. Araujo D, Davids K, Cordovil R, Ribeiro J, Fernandes O. How does knowledge constrain sport performance? An ecological perspective. In: Araújo D, Ripoll H, Raab M, editors. Perspectives on cognition and action in sport. New York: Nova Science Publishers Hauppauge; 2009. p. 119–31.

    Google Scholar 

  38. Balague N, Pol R, Torrents C, Ric A, Hristovski R. On the relatedness and nestedness of constraints. Sports Med Open. 2019;5(1):6.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Gréhaigne J-F, Godbout P, Bouthier D. The teaching and learning of decision making in team sports. Quest. 2001;53(1):59–76.

    Article  Google Scholar 

  40. Silva P, Garganta J, Araujo D, Davids K, Aguiar P. Shared knowledge or shared affordances? Insights from an ecological dynamics approach to team coordination in sports. Sports Med. 2013;43(9):765–72.

    Article  PubMed  Google Scholar 

  41. MacKenzie R, Cushion C. Performance analysis in football: a critical review and implications for future research. J Sports Sci. 2013;31(6):639–76.

    Article  PubMed  Google Scholar 

  42. Sarmento H, Marcelino R, Anguera MT, CampaniCo J, Matos N, LeitAo JC. Match analysis in football: a systematic review. J Sports Sci. 2014;32(20):1831–43.

    Article  PubMed  Google Scholar 

  43. Ometto L, Vasconcellos FV, Cunha FA, Teoldo I, Souza CRB, Dutra MB, et al. How manipulating task constraints in small-sided and conditioned games shapes emergence of individual and collective tactical behaviours in football: A systematic review. Int J Sports Sci Coach. 2018;13(6):1200–14.

    Article  Google Scholar 

  44. Sarmento H, Clemente FM, Harper LD, Costa ITd, Owen A, Figueiredo AJ. Small sided games in soccer – a systematic review. Int J Perf Anal Spor. 2018;18(5):1–57.

    Google Scholar 

  45. Clemente F, Couceiro M, Martins F, Mendes R. An Online Tactical Metrics Applied to Football Game. Res J Appl Sci Eng Technol. 2013;5(5):1700–19.

    Article  Google Scholar 

  46. Yue Z, Broich H, Seifriz F, Mester J. Mathematical analysis of a soccer game. Part I: individual and collective behaviors. Stud Appl Math. 2008;121(3):223–43.

    Article  Google Scholar 

  47. Yue Z, Broich H, Seifriz F, Mester J. Mathematical analysis of a soccer game. Part II: energy, spectral, and correlation analyses. Stud Appl Math. 2008;121(3):245–61.

    Article  Google Scholar 

  48. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6(7):e1000100.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Cohen J. A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960;20(1):37–46.

    Article  Google Scholar 

  51. Travassos B, Vilar L, Araujo D, McGarry T. Tactical performance changes with equal vs unequal numbers of players in small-sided football games. Int J Perform Anal Sport. 2014;14(2):594–605.

    Article  Google Scholar 

  52. Silva P, Chung D, Carvalho T, Cardoso T, Davids K, Araujo D, et al. Practice effects on intra-team synergies in football teams. Hum Mov Sci. 2016;46:39–51.

    Article  PubMed  Google Scholar 

  53. Clemente FM, Santos Couceiro M, Lourenço Martins FM, Dias G, Mendes R. Interpersonal dynamics: 1v1 sub-phase at sub-18 football players. J Hum Kinet. 2013;36:181–91.

    Article  Google Scholar 

  54. Menuchi MRTP, Moro ARP, Ambrósio PE, Pariente CAB, Araújo D. Effects of spatiotemporal constraints and age on the interactions of soccer players when competing for ball possession. J Sports Sci Med. 2018;17(3):379–91.

    PubMed  PubMed Central  Google Scholar 

  55. Laakso T, Travassos B, Liukkonen J, Davids K. Field location and player roles as constraints on emergent 1-vs-1 interpersonal patterns of play in football. Hum Mov Sci. 2017;54:347–53.

    Article  CAS  PubMed  Google Scholar 

  56. Headrick J, Davids K, Renshaw I, Araújo D, Passos P, Fernandes O. Proximity-to-goal as a constraint on patterns of behaviour in attacker–defender dyads in team games. J Sports Sci. 2012;30(3):247–53.

    Article  PubMed  Google Scholar 

  57. Shafizadeh M, Davids K, Correia V, Wheat J, Hizan H. Informational constraints on interceptive actions of elite football goalkeepers in 1v1 dyads during competitive performance. J Sports Sci. 2016;34(17):1596–601.

    Article  PubMed  Google Scholar 

  58. Duarte R, Araujo D, Davids K, Travassos B, Gazimba V, Sampaio J. Interpersonal coordination tendencies shape 1-vs-1 sub-phase performance outcomes in youth soccer. J Sports Sci. 2012;30(9):871–7.

    Article  PubMed  Google Scholar 

  59. Castellano J, Casamichana D. What are the differences between first and second divisions of Spanish football teams? Int J Perform Anal Sport. 2015;2015(15):135–46.

    Article  Google Scholar 

  60. Olthof SBH, Frencken WGP, Lemmink K. Match-derived relative pitch area changes the physical and team tactical performance of elite soccer players in small-sided soccer games. J Sports Sci. 2018;36(14):1557–63.

    Article  PubMed  Google Scholar 

  61. Fradua L, Zubillaga A, Caro O, Ivan Fernandez-Garcia A, Ruiz-Ruiz C, Tenga A. Designing small-sided games for training tactical aspects in soccer: extrapolating pitch sizes from full-size professional matches. J Sports Sci. 2013;31(6):573–81.

    Article  PubMed  Google Scholar 

  62. Zubillaga A, Gabbett TJ, Fradua L, Ruiz-Ruiz C, Caro Ó, Ervilla R. Influence of ball position on playing space in Spanish elite women’s football match-play. Int J Sports Sci Coach. 2013;2013(8):713–22.

    Article  Google Scholar 

  63. Santos P, Lago-Penas C, Garcia-Garcia O. The influence of situational variables on defensive positioning in professional soccer. Int J Perform Anal Sport. 2017;17(3):212–9.

    Article  Google Scholar 

  64. Sampaio J, Maçãs V. Measuring tactical behaviour in football. Int J Sports Med. 2012;33(5):395–401.

    Article  CAS  PubMed  Google Scholar 

  65. Aguiar M, Gonçalves B, Botelho G, Lemmink K, Sampaio J. Footballers’ movement behaviour during 2-, 3-, 4- and 5-a-side small-sided games. J Sports Sci. 2015;33(12):1259–66.

    Article  PubMed  Google Scholar 

  66. Gonçalves BV, Figueira BE, Maças V, Sampaio J. Effect of player position on movement behaviour, physical and physiological performances during an 11-a-side football game. J Sports Sci. 2014;32(2):191–9.

    Article  PubMed  Google Scholar 

  67. Clemente FM, Couceiro MS, Martins FML, Mendes RS, Figueiredo AJ. Using collective metrics to inspect spatio-temporal relationships between football players. S Afr J Res Sport Phys Educ Recreat. 2014;36(2):47–59.

    Google Scholar 

  68. Clemente F, Santos-Couceiro M, Lourenco-Martins F, Sousa R, Figueiredo A. Intelligent systems for analyzing soccer games: the weighted centroid. Ingenieria E Investigacion. 2014;34(3):70–5.

    Article  Google Scholar 

  69. Clemente FM, Couceiro MS, Martins FML, Mendes R, Figueiredo AJ. Measuring tactical behaviour using technological metrics: case study of a football game. Int J Sports Sci Coach. 2013;2013(8):723–40.

    Article  Google Scholar 

  70. Clemente MF, Couceiro SM, Martins FML, Mendes R, Figueiredo AJ. Measuring collective behaviour in football teams: inspecting the impact of each half of the match on ball possession. Int J Perform Anal Sport. 2013;13(3):678–89.

    Article  Google Scholar 

  71. Silva P, Travassos B, Vilar L, Aguiar P, Davids K, Araujo D, et al. Numerical relations and skill level constrain co-adaptive behaviors of agents in sports teams. PLoS One. 2014;9(9):e107112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Silva P, Duarte R, Sampaio J, Aguiar P, Davids K, Araujo D, et al. Field dimension and skill level constrain team tactical behaviours in small-sided and conditioned games in football. J Sports Sci. 2014;32(20):1888–96.

    Article  PubMed  Google Scholar 

  73. Silva P, Esteves P, Correia V, Davids K, Araujo D, Garganta J. Effects of manipulations of player numbers vs. field dimensions on inter-individual coordination during small-sided games in youth football. Int J Perform Anal Sport. 2015;15(2):641–59.

    Article  Google Scholar 

  74. Vilar L, Duarte R, Silva P, Chow JY, Davids K. The influence of pitch dimensions on performance during small-sided and conditioned soccer games. J Sports Sci. 2014;32(19):1751–9.

    Article  PubMed  Google Scholar 

  75. Vilar L, Esteves PT, Travassos B, Passos P, Lago-Peñas C, Davids K. Varying numbers of players in small-sided soccer games modifies action opportunities during training. Int J Sports Sci Coach. 2014;9(5):1007–18.

    Article  Google Scholar 

  76. Gonçalves B, Marcelino R, Torres-Ronda L, Torrents C, Sampaio J. Effects of emphasising opposition and cooperation on collective movement behaviour during football small-sided games. J Sports Sci. 2016;34(14):1346–54.

    Article  PubMed  Google Scholar 

  77. Frencken W, Lemmink K, Delleman N, Visscher C. Oscillations of centroid position and surface area of soccer teams in small-sided games. Eur J Sport Sci. 2011;11(4):215–23.

    Article  Google Scholar 

  78. Bartlett R, Button C, Robins M, Dutt-Mazumder A, Kennedy G. Analysing team coordination patterns from player movement trajectories in soccer: methodological considerations. Int J Perform Anal Sport. 2012;12(2):398–424.

    Article  Google Scholar 

  79. Moura FA, Martins LE, Anido Rde O, de Barros RM, Cunha SA. Quantitative analysis of Brazilian football players’ organisation on the pitch. Sports Biomech. 2012;11(1):85–96.

    Article  PubMed  Google Scholar 

  80. Castellano J, Alvarez D, Figueira B, Coutinho D, Sampaio J. Identifying the effects from the quality of opposition in a football team positioning strategy. Int J Perform Anal Sport. 2013;13(3):822–32.

    Article  Google Scholar 

  81. Folgado H, Lemmink K, Frencken W, Sampaio J. Length, width and centroid distance as measures of teams tactical performance in youth football. Eur J Sport Sci. 2014;14:S487–92.

    Article  PubMed  Google Scholar 

  82. Clemente FM, Martins FML, Couceiro MS, Mendes RS, Figueiredo AJ. Developing a tactical metric to estimate the defensive area of soccer teams: the defensive play area. Proc Inst Mech Eng Part P J Sports Eng Technol. 2016;230(2):124–32.

    Google Scholar 

  83. Olthof SB, Frencken WG, Lemmink KA. The older, the wider: on-field tactical behavior of elite-standard youth soccer players in small-sided games. Hum Mov Sci. 2015;41:92–102.

    Article  PubMed  Google Scholar 

  84. Silva P, Vilar L, Davids K, Araujo D, Garganta J. Sports teams as complex adaptive systems: manipulating player numbers shapes behaviours during football small-sided games. Springerplus. 2016;5:191.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Gonçalves B, Esteves P, Folgado H, Ric A, Torrents C, Sampaio J. Effects of pitch area-restrictions on tactical behavior, physical, and physiological performances in soccer large-sided games. J Strength Cond Res. 2017;31(9):2398–408.

    Article  PubMed  Google Scholar 

  86. Taki T, Hasegawa J. Visualization of dominant region in team games and its application to teamwork analysis. Proc Comput Graph Int. 2000;227–35.

  87. Taki T, Hasegawa J. Dominant region: a basic feature for group motion analysis and its application to teamwork evaluation in soccer games. In: Electronic imaging ‘99; SPIE; 1998. p. 10.

  88. Taki T, Hasegawa J. Quantitative measurement of teamwork in ball games using dominant region. ISPRS J Photogramm. 2000;33:125–31.

    Google Scholar 

  89. Rein R, Raabe D, Memmert D. “Which pass is better?” Novel approaches to assess passing effectiveness in elite soccer. Hum Mov Sci. 2017;55:172–81.

    Article  PubMed  Google Scholar 

  90. Filetti C, Ruscello B, D’Ottavio S, Fanelli V. A study of relationships among technical, tactical, physical parameters and final outcomes in elite soccer matches as analyzed by a semiautomatic video tracking system. Percept Mot Skills. 2017;124(3):601–20.

    Article  PubMed  Google Scholar 

  91. Baptista J, Travassos B, Gonçalves B, Mourão P, Viana JL, Sampaio J. Exploring the effects of playing formations on tactical behaviour and external workload during football small-sided games. J Strength Cond Res. 2018. https://doi.org/10.1519/JSC.0000000000002445.

    Article  PubMed  Google Scholar 

  92. Gonçalves B, Coutinho D, Santos S, Lago-Penas C, Jiménez S, Sampaio J. Exploring team passing networks and player movement dynamics in Youth Association Football. PLoS One. 2017;12(1):e0171156.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Vilar L, Araújo D, Davids K, Bar-Yam Y. Science of winning soccer: emergent pattern-forming dynamics in association football. J Syst Sci Complex. 2013;26(1):73–84.

    Article  Google Scholar 

  94. Clemente FM, Martins FML, Couceiro MS, Mendes RS, Figueiredo AJ. Evaluating the offensive definition zone in football: a case study. S Afr J Res Sport Phys Educ Recreat (SAJR SPER). 2014;36(3):25–37.

    Google Scholar 

  95. Clemente FM, Martins FML, Couceiro MS, Mendes RS, Figueiredo AJ. Inspecting teammates’ coverage during attacking plays in a football game: a case study. Int J Perform Anal Sport. 2014;14(2):384–400.

    Article  Google Scholar 

  96. Ribeiro J, Davids K, Araújo D, Silva P, Ramos J, Lopes R, et al. The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance. Sports Med. 2019;49(9):1337–44.

    Article  Google Scholar 

  97. Ramos J, Lopes RJ, Marques P, Araújo D. Hypernetworks reveal compound variables that capture cooperative and competitive interactions in a soccer match. Front Psychol. 2017;8:1379.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Stergiou N, Buzzi U, Kurz M, Heidel J. Nonlinear tools in human movement. In: Stergiou N, editor. Innovative analyses of human movement: analytical tools for human movement research. 1st ed. Champaign: Human Kinetics; 2004. p. 63–90.

    Google Scholar 

  99. Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;2000(278):H2039–49.

    Article  Google Scholar 

  100. Richman JS, Lake DE, Moorman JR. Sample entropy. Methods enzymol. Cambridge: Academic Press; 2004. p. 172–84.

    Google Scholar 

  101. Yentes JM, Hunt N, Schmid KK, Kaipust JP, McGrath D, Stergiou N. The appropriate use of approximate entropy and sample entropy with short data sets. Ann Biomed Eng. 2013;41(2):349–65.

    Article  PubMed  Google Scholar 

  102. Aguiar M, Gonçalves B, Botelho G, Duarte R, Sampaio J. Regularity of interpersonal positioning discriminates short and long sequences of play in small-sided soccer games. Sci Med Footb. 2017;1(3):258–64.

    Article  Google Scholar 

  103. Barnabe L, Volossovitch A, Duarte R, Ferreira AP, Davids K. Age-related effects of practice experience on collective behaviours of football players in small-sided games. Hum Mov Sci. 2016;48:74–81.

    Article  PubMed  Google Scholar 

  104. Silva P, Aguiar P, Duarte R, Davids K, Araújo D, Garganta J. Effects of pitch size and skill level on tactical behaviours of association football players during small-sided and conditioned games. Int J Sports Sci Coach. 2014;9(5):993–1006.

    Article  Google Scholar 

  105. Leser R, Moser B, Hoch T, Stogerer J, Kellermayr G, Reinsch S, et al. Expert-oriented modelling of a 1vs1-situation in football. Int J Perform Anal Sport. 2015;15(3):949–66.

    Article  Google Scholar 

  106. Siegle M, Lames M. Modeling soccer by means of relative phase. J Syst Sci Complex. 2013;26(1):14–20.

    Article  Google Scholar 

  107. Clemente FM, Sequeiros JB, Correia A, Serra-Olivares J, González-Víllora S, Silva F, et al. How dots behave in two different pitch sizes? Analysis of tactical behavior based on position data in two soccer field sizes ¿Cómo se comportan los puntos en dos campos diferentes? Análisis del comportamiento táctico basado en los datos de posición en dos tamaños de campo de fútbol. RICYDE Revista Internacional de Ciencias del Deporte. 2018;14(51):16–28.

    Article  Google Scholar 

  108. Castellano J, Fernandez E, Echeazarra I, Barreira D, Garganta J. Influence of pitch length on inter- and intra-team behaviors in youth soccer. Anales De Psicologia. 2017;33(3):486–96.

    Article  Google Scholar 

  109. Hill-Haas SV, Dawson B, Impellizzeri FM, Coutts AJ. Physiology of small-sided games training in football: a systematic review. Sports Med. 2011;41(3):199–220.

    Article  PubMed  Google Scholar 

  110. Bujalance-Moreno P, Latorre-Roman PA, Garcia-Pinillos F. A systematic review on small-sided games in football players: acute and chronic adaptations. J Sports Sci. 2018;29:1–29.

    Google Scholar 

  111. Sampaio JE, Lago C, Gonçalves B, Maçãs VM, Leite N. Effects of pacing, status and unbalance in time motion variables, heart rate and tactical behaviour when playing 5-a-side football small-sided games. J Sci Med Sport. 2014;17(2):229–33.

    Article  PubMed  Google Scholar 

  112. Castellano J, Silva P, Usabiaga O, Barreira D. The influence of scoring targets and outer-floaters on attacking and defending team dispersion, shape and creation of space during small-sided soccer games. J Hum Kinet. 2016;51(1):153–63.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Folgado H, Duarte R, Marques P, Gonçalves B, Sampaio J. Exploring how movement synchronization is related to match outcome in elite professional football. Sci Med Footb. 2018;2(2):101–7.

    Article  Google Scholar 

  114. Folgado H, Duarte R, Marques P, Sampaio J. The effects of congested fixtures period on tactical and physical performance in elite football. J Sports Sci. 2015;33(12):1238–47.

    Article  PubMed  Google Scholar 

  115. Travassos B, Gonçalves B, Marcelino R, Monteiro R, Sampaio J. How perceiving additional targets modifies teams’ tactical behavior during football small-sided games. Hum Mov Sci. 2014;38:241–50.

    Article  PubMed  Google Scholar 

  116. Tenga A, Zubillaga A, Caro O, Fradua L. Explorative study on patterns of game structure in male and female matches from elite Spanish soccer. Int J Perform Anal Sport. 2015;15(1):411–23.

    Article  Google Scholar 

  117. Ric A, Torrents C, Gonçalves B, Sampaio J, Hristovski R. Soft-assembled multilevel dynamics of tactical behaviors in soccer. Front Psychol. 2016;7:1513.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Frencken W, Poel H, Visscher C, Lemmink K. Variability of inter-team distances associated with match events in elite-standard soccer. J Sports Sci. 2012;30(12):1207–13.

    Article  PubMed  Google Scholar 

  119. Duarte R, Araújo D, Folgado H, Esteves P, Marques P, Davids K. Capturing complex, non-linear team behaviours during competitive football performance. J Syst Sci Complex. 2013;26(1):62–72.

    Article  Google Scholar 

  120. Duarte R, Araujo D, Correia V, Davids K, Marques P, Richardson MJ. Competing together: assessing the dynamics of team-team and player-team synchrony in professional association football. Hum Mov Sci. 2013;32(4):555–66.

    Article  PubMed  Google Scholar 

  121. Duarte R, Araujo D, Freire L, Folgado H, Fernandes O, Davids K. Intra- and inter-group coordination patterns reveal collective behaviors of football players near the scoring zone. Hum Mov Sci. 2012;31(6):1639–51.

    Article  PubMed  Google Scholar 

  122. Frencken W, Van Der Plaats J, Visscher C, Lemmink K. Size matters: pitch dimensions constrain interactive team behaviour in soccer. J Syst Sci Complex. 2013;26(1):85–93.

    Article  Google Scholar 

  123. Ouellette J. Principles of play for soccer. Strategies. 2004;17(3):26.

    Article  Google Scholar 

  124. Moura FA, van Emmerik REA, Santana JE, Martins LEB, Barros RMLD, Cunha SA. Coordination analysis of players’ distribution in football using cross-correlation and vector coding techniques. J Sports Sci. 2016;34(24):2224–32.

    Article  PubMed  Google Scholar 

  125. Low B, Vilas Boas G, Meyer L, Lizaso E, Hoitz F, Leite N, et al. Exploring the effects of deep-defending vs high-press on footballers tactical behaviour, physical and physiological performance: a pilot study. Motriz: Revista de Educação Física; 2018. p. 24.

    Google Scholar 

  126. Folgado H, Duarte R, Fernandes O, Sampaio J. Competing with lower level opponents decreases intra-team movement synchronization and time-motion demands during pre-season soccer matches. PLoS One. 2014;9(5):e97145.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Palucci Vieira LH, Aquino R, Moura FA, Barros RML, Arpini VM, Oliveira LP, et al. Team Dynamics, Running, and Skill-Related Performances of Brazilian U11 to Professional Soccer Players During Official Matches. J Strength Cond Res. 2018;33(8):2202–16.

    Article  Google Scholar 

  128. Folgado H, Goncalves B, Sampaio J. Positional synchronization affects physical and physiological responses to preseason in professional football (soccer). Res Sports Med. 2018;26(1):51–63.

    Article  PubMed  Google Scholar 

  129. Aquino RLQT, Goncalves LGC, Vieira LHP, Oliveira LP, Alves GF, Santiago PRP, et al. Periodization training focused on technical-tactical ability in young soccer players positively affects biochemical markers and game performance. J Strength Cond Res. 2016;30(10):2723–32.

    Article  Google Scholar 

  130. Coutinho D, Santos S, Goncalves B, Travassos B, Wong DP, Schollhorn W, et al. The effects of an enrichment training program for youth football attackers. PLoS One. 2018;13(6):e0199008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Santos S, Coutinho D, Goncalves B, Schollhorn W, Sampaio J, Leite N. Differential learning as a key training approach to improve creative and tactical behavior in soccer. Res Q Exerc Sport. 2018;89(1):11–24.

    Article  PubMed  Google Scholar 

  132. Santos S, Jiménez S, Sampaio J, Leite N. Effects of the Skills4Genius sports-based training program in creative behavior. PLoS One. 2017;12(2):e0172520.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Coutinho D, Gonçalves B, Wong DP, Travassos B, Coutts AJ, Sampaio J. Exploring the effects of mental and muscular fatigue in soccer players’ performance. Hum Mov Sci. 2018;58:287–96.

    Article  PubMed  Google Scholar 

  134. Figueira B, Gonçalves B, Masiulis N, Sampaio J. Exploring how playing football with different age groups affects tactical behaviour and physical performance. Biol Sport. 2018;35(2):145–53.

    PubMed  Google Scholar 

  135. Gonçalves B, Folgado H, Coutinho D, Marcelino R, Wong D, Leite N, et al. Changes in effective playing space when considering sub-groups of 3–10 players in professional soccer matches. J Hum Kinet. 2018;62(1):145–55.

    Article  PubMed  PubMed Central  Google Scholar 

  136. Coutinho D, Gonçalves B, Travassos B, Wong DP, Coutts AJ, Sampaio JE. Mental fatigue and spatial references impair soccer players’ physical and tactical performances. Front Psychol. 2017;8:1645.

    Article  PubMed  PubMed Central  Google Scholar 

  137. Ric A, Torrents C, Gonçalves B, Torres-Ronda L, Sampaio J, Hristovski R. Dynamics of tactical behaviour in association football when manipulating players’ space of interaction. PLoS One. 2017;12(7):e0180773.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Aquino RL, Goncalves LG, Vieira LH, Oliveira LP, Alves GF, Santiago PR, et al. Biochemical, physical and tactical analysis of a simulated game in young soccer players. J Sports Med Phys Fit. 2016;56(12):1554–61.

    Google Scholar 

  139. Moura FA, Martins LE, Anido RO, Ruffino PR, Barros RM, Cunha SA. A spectral analysis of team dynamics and tactics in Brazilian football. J Sports Sci. 2013;31(14):1568–77.

    Article  PubMed  Google Scholar 

  140. Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci. 1991;88(6):2297–301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Pincus SM, Goldberger AL. Physiological time-series analysis: what does regularity quantify? Am J Physiol Heart Circ Physiol. 1994;266(4):H1643–56.

    Article  CAS  Google Scholar 

  142. Shannon CE. A mathematical theory of communication. Bell Syst Tech J. 1948;27(3):379–423.

    Article  Google Scholar 

  143. Palut Y, Zanone PG. A dynamical analysis of tennis: concepts and data. J Sports Sci. 2005;23(10):1021–32.

    Article  PubMed  Google Scholar 

  144. Derrick T, Thomas J. Time series analysis: the cross-correlation function. In: Stergiou N, editor. Innovative analyses of human movement: analytical tools for human movement research. 1st ed. Champaign: Human Kinetics; 2004. p. 189–205.

    Google Scholar 

  145. Sparrow WA, Donovan E, van Emmerik R, Barry EB. Using relative motion plots to measure changes in intra-limb and inter-limb coordination. J Mot Behav. 1987;19(1):115–29.

    Article  CAS  PubMed  Google Scholar 

  146. Hamill J, Haddad JM, McDermott WJ. Issues in quantifying variability from a dynamical systems perspective. J Appl Biomech. 2000;16(4):407–18.

    Article  Google Scholar 

  147. Cover TM, Thomas JA. Entropy, relative entropy and mutual information. In: Schilling DL, editor. Elements of information theory. 1st ed. New York: Wiley; 1991. p. 12–49.

    Chapter  Google Scholar 

  148. Kuramoto Y, Nishikawa I. Statistical macrodynamics of large dynamical systems. Case of a phase transition in oscillator communities. J Stat Phys. 1987;49(3):569–605.

    Article  Google Scholar 

  149. Frank TD, Richardson MJ. On a test statistic for the Kuramoto order parameter of synchronization: an illustration for group synchronization during rocking chairs. Phys D Nonlinear Phenom. 2010;239(23):2084–92.

    Article  CAS  Google Scholar 

  150. Memmert D, Raabe D, Schwab S, Rein R. A Tactical Comparison of the 4-2-3-1 and 3-5-2 Formation in Soccer: A Theory-Oriented, Experimental Approach Based on Positional Data in an 11 vs. 11 Game Set-Up. PloS ONE 2019;14(1):e0210191. https://doi.org/10.1371/journal.pone.0210191.

  151. Perl J, Memmert D. Key performance indicators. In: Baca A, Perl J (eds) Modelling and Simulation in Sport and Exercise, 2018; Abingdon: Routledge, pp. 146–166.

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Acknowledgements

We would like to thank the reviewers for their constructive feedback and suggestions in the publication of this systematic review, as well as all authors of the reviewed studies who have kindly responded to our queries.

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Benedict Low, Diogo Coutinho, Bruno Gonçalves, Robert Rein, Daniel Memmert and Jaime Sampaio declare no conflicts of interest that are directly relevant to the content of this review.

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Low, B., Coutinho, D., Gonçalves, B. et al. A Systematic Review of Collective Tactical Behaviours in Football Using Positional Data. Sports Med 50, 343–385 (2020). https://doi.org/10.1007/s40279-019-01194-7

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