Sport analyticsSport analytics development is highly dependent on managing the quality of data in a few applications, such as athlete performanceAthlete performance. This chapter will review several facets of sport analytics, beginning with data preparation and collection, as well as various procedures in sport management. It discusses the various methods of data acquisition for sport analytics applications, including computer visionComputer Vision (CV) and wearable sensorsWearable sensors. It will examine the involvement of sports organizations and discuss the future challenges within sport analyticsSport analytics. Specific data acquisition approaches, such as data cleaningData cleaning, standardization, and feature engineeringFeature engineering, will also be discussed to ensure the usability, safety, accuracy, and reliability of the collected data. Some key aspects of athlete managementAthlete management will also be discussed to highlight the impact of foresight, injury preventionInjury prevention, and workload managementLoad management. Ethical principles will also be examined regarding respect for persons and data privacy. In reviewing these relationships, the chapter presents a first-generation understanding of data management and how data and analytical approaches can contribute to over-dependency, unethical, and/or unsafe practices in working with athletes.