
As a hockey enthusiast, I’m thrilled about the ICE-Q 2.0, a revolutionary AI system that learns from actual NHL matches, thanks to the NHL Edge data. This learning process empowers the AI to become smarter, enabling it to make more informed decisions.
The NHL Edge data utilized by ICE-Q 2.0 encompasses a wide range of aspects such as skaters’ acceleration and top speed, shot locations and velocities, save percentages by zones, heat maps depicting player movements, puck possession times and zone usages, and reaction times and body orientations. These details are captured using 14 infrared cameras, puck sensors, and jersey tags.
In essence, all this data is woven into the game’s player attributes, Tendencies, and visual elements, making it a more immersive and realistic experience for us fans.