The proliferation of consumer recording devices and video sharing websites makes the possibility of having access to multiple recordings of the same occurrence increasingly likely. These co-synchronous recordings can be identified via their audio tracks, despite local noise and channel variations. We explore a robust fingerprinting strategy to do this. Matching pursuit is used to obtain a sparse set of the most prominent elements in a video soundtrack. Pairs of these elements are hashed and stored, to be efficiently compared with one another. This fingerprinting is tested on a corpus of over 700 YouTube videos related to the 2009 U.S. presidential inauguration. Reliable matching of identical events in different recordings is demonstrated, even under difficult conditions.