  Computer-aided support and analysis are becoming increasingly important in
the modern world of sports. The scouting of potential prospective players,
performance as well as match analysis, and the monitoring of training programs
rely more and more on data-driven technologies to ensure success. Therefore,
many approaches require large amounts of data, which are, however, not easy to
obtain in general. In this paper, we propose a pipeline for the fully-automated
extraction of positional data from broadcast video recordings of soccer
matches. In contrast to previous work, the system integrates all necessary
sub-tasks like sports field registration, player detection, or team assignment
that are crucial for player position estimation. The quality of the modules and
the entire system is interdependent. A comprehensive experimental evaluation is
presented for the individual modules as well as the entire pipeline to identify
the influence of errors to subsequent modules and the overall result. In this
context, we propose novel evaluation metrics to compare the output with
ground-truth positional data.
