This research aims to find patterns in the live position data of trains within shunting yards. These patterns can be converted to heuristics and applied in algorithms developed by railway operators in the Netherlands to tackle the Train Unit Shunting Problem. The usage patterns were extracted from real-world location data of train units. Specifically, this research focuses on finding patterns in the paths taken in both temporal and spatial metrics. These investigations identified the busiest times in the shunting yards according to various metrics, such as the total number of trains and the number of serviced trains. These metrics are extracted from the type of train movement at a given moment, which was provided with the dataset. The accuracy of the provided train movement category has been analyzed and shown to be inaccurate for uses within shunting yards compared to a proposed approach. Finally, an algorithm for classifying train units that belong to the same train has been shown to have initial success.