Current Developments in Handball Game Analysis

Main Article Content

Nilgün Vurgun
Murat Bilge
Serdar Eler
Nebahat Eler
Aydın Şentürk

Keywords

Game analysis, tournament analysis, finalist analysis, longitudinal analysis

Abstract

The most important expectation of the trainers was the correct evaluation of the game analysis and the reflection of its effects on the trainings. Because of handball’s complex nature, interpreting numerical data with objective field facts requires expertise. The aim of this study was to evaluate the numerical results under three different titles (longitudinal-success–tournament analysis) and with different research problems. As a longitudinal analysis, match parameters of the same generation (WU17-WU19 European Championships) in underage categories held two years apart were compared. As a success analysis, all the matches played by the 2020 MECh (Mens’ European Championship) champion (Spain) and finalist (Croatia) in the tournament were analyzed. It has been set up which parameters determine success. As a tournament analysis, the leadership of European teams in handball was analyzed after the evaluations between the European teams and others in the 2019 WWCh (Womens’ World Championship) tournament. According to the property of the research problem, t-test, Kruskall Wallis H-test, Pearson correlation and the eta square statistics were used. Research results based on numerical data has tried to be done current contributions to game analysis in handball. As a result, this study has been designed to show that the results of match analysis in handball are not just numbers. It is aimed to evaluate the results under four different titles and with different research problems and to transfer them on the practice. With these three topics; longitudinal analysis, success analysis and tournament analysis, it would also be appropriate to complement the notational analysis with different variables that are predominantly characterized by actions such as different parameters’ efficiency. In order to model the game process effectively, it is necessary to obtain more data about the actions of the teams during the match and the strategies used in different competitions.

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