Applied Data Science: An Approach to Explain a Complex Team Ball Game

Friedemann Schwenkreis, Eckard Nothdurft

Abstract

Team handball is a fast and complex game with a very traditional background and so far, almost no collection of digital information. Only a few attempts have been made to come up with models to explain the mechanisms of the game based on measured indicators. CoCoAnDa is a project located at the Baden-Wuerttemberg Cooperative State University that addresses this gap. While having started with the aim to introduce data mining technology into an almost non-digitalized team sport, the project has extended its scope by introducing mechanisms to collect digital information as well as by developing field specific models to interpret the collected data. The work presented will show the design of specialized apps that have been implemented to manually collect a maximum of data during team handball matches by a single observer. This paper will also describe the analysis of available data collected as part of the match organization of 1,190 matches of the first and 1,559 matches of the second German team handball league, HBL. Furthermore, the data of more than 150 games of national teams, the first league, and the third league have been manually collected using the apps developed as part of the project.

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