Space creation dynamics in basketball offence: validation and evaluation of elite teams

The game of basketball involves several interactions of the offensive and defensive teams (i.e., dynamics). The dynamics for defensive disruption can be organized in classes of equivalence defined herein as space creation dynamics (SCDs). The aims of this study were: a) to validate a set of SCDs classes for offensive actions and b) identify the recurrence of these classes on elite teams’ games. SCDs definition and validation followed Fonseca’s et al. (2008) criteria: 1a. proposition of a preliminary model of SCDs classes based on researchers experience and game analysis; 1b. expert improvement of the pre-defined proposal of SCDs; 1c. intra-observer and inter-observers reliability; 1d. application of the SCDs: analysis on elite basketball games. Resultant classes of SCDs (steps 1a-b): Space creation with ball dribbled (BD); Space creation with ball not dribbled (BND); Post Isolation (PostI); Perimeter Isolation (PerI); Space creation without the ball (WB); On ball screen (OnBS); Out-of-ball screen (OutBS). Reliability (1c): Kappa test intra-observer and inter-observer reliability range from (0.76 -0.85) to (0.73-0.86), respectively. Inter-judges reliability indicates the usefulness of these classes for game analyses. (1d): “OnBS” presented the highest frequency of occurrence among elite teams (34.8%) indicating the relevance of pick and roll for teams’ strategy.

[1]  Martin Lames,et al.  On the search for reliable performance indicators in game sports , 2007 .

[2]  T. McGarry Applied and theoretical perspectives of performance analysis in sport: Scientific issues and challenges , 2009 .

[3]  Tsamourtzis Evangelos,et al.  Defensive systems in basketball ball possessions. , 2006 .

[4]  Nic James,et al.  Reliability procedures for categorical data in Performance Analysis , 2007 .

[5]  Dean Oliver,et al.  Basketball on Paper: Rules and Tools for Performance Analysis , 2003 .

[6]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[7]  Athanasiou Nikolaos,et al.  Analysis of fast breaks in basketball , 2005 .

[8]  Ian M Franks,et al.  Sport competition as a dynamical self-organizing system , 2002, Journal of sports sciences.

[9]  Martin Lames,et al.  Designing observational systems to support top-level teams in game sports , 2001 .

[10]  Tim McGarry,et al.  Space–time coordination dynamics in basketball: Part 2. The interaction between the two teams , 2010, Journal of sports sciences.

[11]  R. Fonseca,et al.  Development and content validity of the Brazilian Brief Neuropsychological Assessment Battery Neupsilin , 2008 .

[12]  Peter O’Donoghue,et al.  Reliability Issues in Performance Analysis , 2007 .

[13]  J. Gréhaigne,et al.  Tactical Knowledge in Team Sports From a Constructivist and Cognitivist Perspective , 1995 .

[14]  Mike D Hughes,et al.  The use of performance indicators in performance analysis , 2002, Journal of sports sciences.

[15]  Hubert Remmert Analysis of group-tactical offensive behavior in elite basketball on the basis of a process orientated model , 2003 .

[16]  D. Kyriakou,et al.  Comparison of effectiveness of organized offences between two different championships in high level basketball , 2005 .