Sports Analytics has evolved from traditional descriptive statistics into a multidisciplinary domain powered by Data Science, Machine Learning, and Artificial Intelligence. This presentation, Sports Analytics 2.0: From Descriptive Analysis to Artificial Intelligence, examines how state of the art analytical methodologies are transforming athlete assessment, team strategy, injury prevention, performance forecasting, and decision-making across a wide range of Sports Industry.
Drawing on examples from diverse sports, the session highlights applications in player performance evaluation, tactical analysis, wearable and biomechanical data interpretation, injury and recovery modeling, and the economic implications of athlete availability.
Emerging trends shaping the next generation of sports analytics are also discussed, including multimodal AI combining video, sensor, and textual data; real-time and streaming analytics; graph-based and LLM-driven methodologies such as GraphRAG; and the integration of ethical, transparent, and responsible AI practices within sports organizations.
By bridging descriptive, predictive, prescriptive, and AI-driven approaches, this talk provides a holistic and future-oriented perspective on how Sports Analytics 2.0 is redefining performance science and strategic decision-making across the global sports ecosystem.
Zoom link: https://uoc-gr.zoom.us/j/88659969718?pwd=g6bjYPDCuUQo1bzVxjjbgQL4xFN1f3.1
