Machine learning (ML) is integral to the success of games from predicting specific in game actions to identifying and reaching your most valuable users. Since ML is a key element to the success of a game how can we better keep track of all of the ML experiments that are happening behind the scenes? In this session, we will showcase how a new feature in Vertex AI, Vertex Experiments, can help gaming teams better manage, interpret, and extract value from their ML experiments. Tools used: Experiments, Pipelines, Workbench, and ML Metadata.