  RoboCup is an international scientific robot competition in which teams of
multiple robots compete against each other. Its different leagues provide many
sources of robotics data, that can be used for further analysis and application
of machine learning. This paper describes a large dataset from games of some of
the top teams (from 2016 and 2017) in RoboCup Soccer Simulation League (2D),
where teams of 11 robots (agents) compete against each other. Overall, we used
10 different teams to play each other, resulting in 45 unique pairings. For
each pairing, we ran 25 matches (of 10mins), leading to 1125 matches or more
than 180 hours of game play. The generated CSV files are 17GB of data (zipped),
or 229GB (unzipped). The dataset is unique in the sense that it contains both
the ground truth data (global, complete, noise-free information of all objects
on the field), as well as the noisy, local and incomplete percepts of each
robot. These data are made available as CSV files, as well as in the original
soccer simulator formats.
