Video synchronization is an essential processing step in many multimedia applications, and various methods have been proposed in the literature each of which addresses the problem from a different point of vantage. In this article, we present an information theoretic approach to video synchronization, based on the state-of-the-art in hybrid video coding. Time series derived from the videos' instantaneous bitrate demand are correlated in a robust manner employing the recently published ConCor algorithm. We enhance ConCor with integrated normalization capabilities in order to improve its shape-oriented matching performance. Furthermore, we present a mathematical framework to derive the most suitable ConCor parameters given a specific class of input videos. In an extensive experimental analysis, we give an insight into the representation of synchronization-relevant scene changes with bitrate data, and examine the influence of encoding parameters on the synchronization performance. Experiments on diverse video input substantiate the reliable performance of our easy to implement, yet effective video synchronization algorithm which distinguishes itself in that it operates largely without manual intervention.