  Sports analytics -- broadly defined as the pursuit of improvement in athletic
performance through the analysis of data -- has expanded its footprint both in
the professional sports industry and in academia over the past 30 years. In
this paper, we connect four big ideas that are common across multiple sports:
the expected value of a game state, win probability, measures of team strength,
and the use of sports betting market data. For each, we explore both the shared
similarities and individual idiosyncrasies of analytical approaches in each
sport. While our focus is on the concepts underlying each type of analysis, any
implementation necessarily involves statistical methodologies, computational
tools, and data sources. Where appropriate, we outline how data, models, tools,
and knowledge of the sport combine to generate actionable insights. We also
describe opportunities to share analytical work, but omit an in-depth
discussion of individual player evaluation as beyond our scope. This paper
should serve as a useful overview for anyone becoming interested in the study
of sports analytics.
