The tracking of product maturity is a major challenge in today’s Vehicle Software Development. A new approach is focusing on the rating of product maturity based on measurement data. This highly depends on the available measurement data. To extract more information from different data sources from free driving, cycle driving, testbenches or Simulation a new methodology is proposed in this paper. The proposed method uses a combination of information reduction by averaging, density-based Clustering and exact comparison of time series data. The outcome are clusters of similar operation points, which can be used for further investigation. An example application is showcasing the potential of the identification. The new method is used to investigate reproducibility of powertrain behavior. For this, measurement data are searched for comparable time periods or driving situations. These are then rated for reproducibility: A high reproducibility is a sign of high product maturity. Therefore, this is integrated into an existing approach for product maturity rating based on measurement data.