Collecting ground truth-data for real-world applications is a non-trivial but very important task. In order to evaluate new algorithmic approaches or to benchmark system performance, they are inevitable. This is particularly true for robotics applications. In this paper we present our data collection for the biped humanoid robot Nao. Reflective markers were attached to Nao’s body, and the positions and orientation of its body and head were tracked in 6D with an accurate professional vision-based body motion tracking system. While doing so, the data of Nao’s internal state, i.e., the readings of all its servos, the inertial measurement unit, the force receptors plus a camera stream of the robot’s camera were stored for different, typical robotic soccer scenarios in the context of the RoboCup Standard Platform League. These data will be combined in order to compile an accurate ground-truth data set. We describe how the data were recorded, in which format they are stored, and show the usability of the logged data in some first experiments on the recorded data sets. The data sets will be made publicly available for the RoboCup’s Standard Platform League community.