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Data Mining im Fußball
(2014)
The term Data Mining is used to describe applications that can be applied to extract useful information from large datasets. Since the 2011/2012 season of the german soccer league, extensive data from the first and second Bundesliga have been recorded and stored. Up to 2000 events are recorded for each game.
The question arises, whether it is possible to use Data Mining to extract patterns from this extensive data which could be useful to soccer clubs.
In this thesis, Data Mining is applied to the data of the first Bundesliga to measure the value of individual soccer players for their club. For this purpose, the state of the art and the available data are described. Furthermore, classification, regression analysis and clustering are applied to the available data. This thesis focuses on qualitative characteristics of soccer players like the nomination for the national squad or the marks players get for their playing performance. Additionally this thesis considers the playing style of the available players and examines if it is possible to make predictions for upcoming seasons. The value of individual players is determined by using regression analysis and a combination of cluster analysis and regression analysis.
Even though not all applications can achieve sufficient results, this thesis shows that Data Mining has the potential to be applied to soccer data. The value of a player can be measured with the help of the two approaches, allowing simple visualization of the importance of a player for his club.
In den systematischen Neurowissenschaften werden oft Experimente durchgeführt, welche die Kommunikation von Hirnarealen bei der Bewältigung einer bestimmten Aufgabe untersuchen. Dabei wird angenommen, dass Neuronenverbände, die ihre Aktivität synchronisiert haben, an dieser Aufgabe beteiligt sind. In den aufgezeichneten EEG-Daten kann diese Zusammenarbeit anhand von interregionaler Kohärenz als Phasensynchronizität der Hirnstromfrequenz nachgewiesen bzw. quantifiziert werden. Ziel der Arbeit ist die Implementierung einer Software, welche die notwendigen Schritte der Kohärenzanalyse durchführt und die Ergebnisse statistisch aufbereitet und darstellt. Da die Verfahren und der Ablauf weitgehend durch die Anforderungsspezifikation vorgegeben sind, liegt ein Schwerpunkt der Arbeit auf dem Entwurf und der Programmierung einer intuitiv zu bedienenden Benutzeroberfläche, die den automatisierten Ablauf der Analyse ermöglicht. Ein Statistik-Toolkit soll die Überprüfung von Arbeitshypothesen ermöglichen (Signifikanz). Weiterhin soll die Darstellung den Transport und die Diskussion der Ergebnisse erleichtern.
Computers fundamentally changed the methods used by social scientists during the past decades. It is no exaggeration to state that the wide use and growing user-friendliness of computers and statistical analysis systems helped empirical social research as a subdiscipline to become mainstream. This made a new subdiscipline necessary which is mainly working on adapting and applying computer science methods for social research: social science informatics. This book originated from lecture courses given by the authors from the mid-1980s and developed for computer science students with a minor in social science. Unlike many other introductions to univariate and multivariate data analysis, this book is addressed to advanced scholars and students who apply "classical" statistical methods and who want to get an overview of the mathematical foundations of the methods they apply and who want to avoid the pitfalls of cookbook-like introduction when they interpret their results. The electronic document is a slightly revised version of the printed version of 1994 which has been out of stock for many years.