Sports analytics are applications of data science to decision-making in all aspects of sports. As important as player/team performance evaluations are, there are also a wide range of sports analytics problems beyond this category. Here we present a partial review of such topics. These topics include competitive balance and game design (e.g., tournament structures, scheduling, rule changes, referee bias, inter-rater reliability, etc.), sports gambling (e.g., traditional sportsbooks, daily fantasy sports, etc.), business aspects of the sports (e.g., attendance, finance, sports sentiment analysis for customer satisfaction, fan engagement, etc.), and injury analytics. Challenges brought by new data collection technologies will also be summarized to call for contributions from data scientists.