ABSTRACT
The combination of information delivery, mathematical support and essential consulting discussed here under the generalized umbrella of 'analytics' is quite new and ambiguous, especially in terms of sport theories and practices. Analytics is sometimes combined with categories of 'big data', visualization and data mining. Active employment of data that is collected is the second general attribute of analytics. The analytics is divided into types according to their aims and means. Based on the main aim and/or method, types include predictive analytics, learning analytics, web analytics, behavioural analytics, and competitive analytics. Sport analytics itself is characterized by a complex of directions, applicative aims, methods and tools. Whereas the mainstream interpretation of sport analytics has already been drawn, issues of forecasting, scheduling and sport performance metrics using the tools of analytics and operational research (OR) still require clarification. The chapter systematizes the research and main theoretical issues in the general field of analytics and specifically in sport analytics.
