![]() Infrastructure Block Volumes for data extraction. ReSpo.Vision runs its sports analytics platform on OCI, using a variety of compute options, including AMD flex virtual machines, bare metal high performance computing options, and highly performant GPU shapes. Respo.Vision’s metaverse-ready visualization engine also provides fans with an immersive, in-game experience to see any action from multiple perspectives. By turning raw data into digestible features such as particular match events and in-game behaviors of player performance, ReSpo.Vision's platform provides game predictions, play suggestions, tactics, player purchases, and more. The ReSpo.Vision platform then uses this data to create player and game analytics, calculate game event probabilities, customize visual game trackers, and provide detailed statistics for bookmakers. With the data collected from the game, ReSpo.Vision is able to automate event detection, visualization, performance assessment, insights, and recommendations for teams, sponsors, and fans.įounded in 2019, Warsaw-based ReSpo.Vision has developed a unique 3D tracking and data capture system, which can screen any TV broadcast or single camera output and capture a continuous stream of 3D coordinates of body sections of each player and of the ball. Each game generates some 150 million data points. This data is then recorded through a single TV camera or from a previous recording. Using computer vision and machine learning algorithms, the ReSpo.Vision platform captures detailed tracking data for more than 40 player body parts at a rate of 60 times per second. To improve player performance, identify competitor weaknesses, and to calculate winning odds, ReSpo.Vision runs its AI-enabled, cloud-native sports analytics platform on Oracle CloudĬapturing real-time 3D tracking data of players and balls, ReSpo.Vision ingests broadcast TV feeds without requiring additional preinstalled cameras or human intervention.
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