Tactical interaction of offensive and defensive teams in team handball analysed by artificial neural networks

Norbert Schrapf, Shaimaa Alsaied and Markus Tilp

Mathematical and Computer Modelling of Dynamical Systems, 2017, vol. 23, issue 4, 363-371

Abstract: The interaction between teams behaviour is from high relevance for success in sports games. Since the analysis of this interaction is not well established, the present study attempts to model the interaction between opposing teams in team handball. Offensive and defensive playing patterns were determined by means of artificial neural networks from position data of 723 offensive action sequences and the corresponding defensive players, respectively. The most common combinations of these patterns were then analysed statistically. Pattern efficiency was assessed by scoring rate, distance between shooting position and nearest defensive player and distance to goal. No statistically significant relation between pattern combinations and efficiency was found. However, results revealed tendencies to higher efficiency of some tactical patterns. Furthermore, odds ratio analysis revealed advantageous defensive tactics against specific offensive behaviour. Summarizing, results indicate that artificial neural networks are appropriate to model the interaction between teams based on players’ positions.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/13873954.2017.1336733 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:23:y:2017:i:4:p:363-371

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20

DOI: 10.1080/13873954.2017.1336733

Access Statistics for this article

Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch

More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().