Basketball writers and journalists report on the sport that millions of fans follow and love. However, the recent emergence of pervasive data about the sport and the growth of new forms of sports analytics is changing writers' jobs. While these writers seek to leverage the data and analytics to create engaging, data-driven stories, they typically lack the technical background to perform analytics or efficiently explore data. We investigated and analyzed the work and context of basketball writers, interviewed nine stakeholders to understand the challenges from a holistic view. Based on what we learned, we designed and constructed two interactive visualization systems that support rapid and in-depth sports data exploration and sense-making to enhance their articles and reporting. We deployed the systems during the recent NBA playoffs to gather initial feedback. This article describes the visualization design study we conducted, the resulting visualization systems, and what we learned to potentially help basketball writers in the future.
https://dl.acm.org/doi/abs/10.1145/3491102.3502078
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)