Visual Analysis of FIFA World Cup Data

Michael Burch, Günter Wallner, Sergiu Lazar Angelescu, Peter Lakatos

Abstract: Soccer is one of the most popular sports in the world, played by thousands of professionals and amateurs every week. Consequently, it is no surprise that it generates an enormous amount of data. In today's data-driven world it is essential to find an optimal, self-explanatory, way to present the data in a way to be able to derive visual patterns that relate to the underlying data patterns. In this paper, we describe an interactive visualization for analyzing soccer data and identifying patterns, correlations, and insights. We illustrate the usefulness of our approach, especially targeted towards non-visualization experts, by applying it to World Cup data and by discussing potential use cases.