  Most sports visualizations rely on a combination of spatial, highly temporal,
and user-centric data, making sports a challenging target for visualization.
Emerging technologies, such as augmented and mixed reality (AR/XR), have
brought exciting opportunities along with new challenges for sports
visualization. We share our experience working with sports domain experts and
present lessons learned from conducting visualization research in SportsXR. In
our previous work, we have targeted different types of users in sports,
including athletes, game analysts, and fans. Each user group has unique design
constraints and requirements, such as obtaining real-time visual feedback in
training, automating the low-level video analysis workflow, or personalizing
embedded visualizations for live game data analysis. In this paper, we
synthesize our best practices and pitfalls we identified while working on
SportsXR. We highlight lessons learned in working with sports domain experts in
designing and evaluating sports visualizations and in working with emerging
AR/XR technologies. We envision that sports visualization research will benefit
the larger visualization community through its unique challenges and
opportunities for immersive and situated analytics.

Human-Computer Interaction