Recent advancements in wearable Global Navigation Satellite Systems (GNSS) devices and optical tracking technologies have significantly expanded the availability of spatiotemporal data in sports analytics. Combined with the common practice of manually recording game event logs, these sources provide unprecedented levels of data that describe in detail what happens during a game. However, the manual collection and tagging of events within a game can be costly and time-consuming, requiring domain experts to repeatedly view and annotate footage to identify discrete events. This study presents a novel method for automatically detecting shooting events using spatiotemporal metrics using GNSS tracking data from a single team to achieve event identification.