Object tracking is one of the main challenges in soccer-playing robots. Due to its fast movement, detecting and tracking the soccer ball is challenging for goalkeepers in both humanoid and wheeled robots. To speed up object tracking, we propose the use of Event-based Cameras (ECs). ECs are bio-inspired sensors that asynchronously report changes in brightness for each pixel. Because of their high dynamic range, pixel bandwidth, temporal resolution, low power consumption, and computational simplicity, they are beneficial for vision-based projects in challenging lighting conditions and can detect fast movements with their microsecond response time. We created a dataset using two different event-based cameras from iniVation and Prophesee that recorded events in the lab and during Middle Size League matches at RoboCup 2023. Additionally, we created a Graphical User Interface (GUI) working with the Robot Operating System (ROS) to simplify camera and camera-projector setup calibration for RoboCup participants. The proposed ROS GUI is able to control the camera bias parameters online and publish a stream of events in addition to event “frames” on ROS topics. These advancements will help all RoboCup teams shift from frame-based to event-based technologies, enhancing ball detection regardless of color or lighting. The dataset is available publicly: github.com/MISTLab/event_based_data .