The Satellite Laser Ranging Station Data and Operational Anomaly Detection Model (SLR SAM) is a Jupyter notebook which serves as a tool that may be used to track anomalies within satellite laser ranging (SLR) station performance. SLR SAM uses isolation forest, a machine learning algorithm, with publicly available satellite data from NASA's Crustal Dynamics Data Information System (CDDIS). This tool was designed to help SLR stations and analysts detect anomalies which may be linked to hardware or software changes at the stations.