The concept of big data and the definition of data science within the framework of structured, semi-structured, and unstructured data facilitate more effective strategic and operational decisions for the complex processes of sport events.

Machine learning can be used in sports events, especially in the prediction of participant numbers, optimization of operational processes, and enhancement of participant experiences. By analysing large data sets using data mining methods, it is effectively supported in sport event management processes, performance analyses, marketing strategies, and sustainability practices.

Effective solutions in areas such as task assignment, personnel evaluation, and process optimization in sports events are provided by artificial intelligence-based decision systems. systems. In addition, the integration of these technologies increases transparency by promoting a more collaborative environment among stakeholders. By instantly analysing the real-time data collected during the event, unforeseen situations are quickly adapted. This increases participant satisfaction and optimizes resource utilization.

Data-driven management in sport events transforms into a dynamic ecosystem that facilitates organizational learning processes and the effective implementation of strategic planning.