  We present iBall, a basketball video-watching system that leverages
gaze-moderated embedded visualizations to facilitate game understanding and
engagement of casual fans. Video broadcasting and online video platforms make
watching basketball games increasingly accessible. Yet, for new or casual fans,
watching basketball videos is often confusing due to their limited basketball
knowledge and the lack of accessible, on-demand information to resolve their
confusion. To assist casual fans in watching basketball videos, we compared the
game-watching behaviors of casual and die-hard fans in a formative study and
developed iBall based on the fndings. iBall embeds visualizations into
basketball videos using a computer vision pipeline, and automatically adapts
the visualizations based on the game context and users' gaze, helping casual
fans appreciate basketball games without being overwhelmed. We confrmed the
usefulness, usability, and engagement of iBall in a study with 16 casual fans,
and further collected feedback from 8 die-hard fans.
