Basketball ranks among the world’s most popular team invasion sports, captivating millions with its dynamic play and intense competition. In recent decades, the advent of Artificial Intelligence has opened new pathways for enhancing the performance of basketball players, indicating a transformative era in basketball analytics and athlete development. Artificial Intelligence encompasses a variety of cutting-edge technologies, each contributing uniquely to the data-driven evolution of basketball. This chapter delves into two of the pivotal Artificial Intelligence technologies, including Machine Learning and Deep Learning, which have found extensive and successful applications within the realm of basketball. Consequently, this chapter aims to equip stakeholders in basketball, from players to coaches, with a deeper comprehension of how Artificial Intelligence technologies can enhance athletic performance and strategic decision-making, thereby translating complex data into actionable insights.

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Machine Learning in Basketball

  • Kehang Chen,
  • Marc Garnica Caparrós

摘要

Basketball ranks among the world’s most popular team invasion sports, captivating millions with its dynamic play and intense competition. In recent decades, the advent of Artificial Intelligence has opened new pathways for enhancing the performance of basketball players, indicating a transformative era in basketball analytics and athlete development. Artificial Intelligence encompasses a variety of cutting-edge technologies, each contributing uniquely to the data-driven evolution of basketball. This chapter delves into two of the pivotal Artificial Intelligence technologies, including Machine Learning and Deep Learning, which have found extensive and successful applications within the realm of basketball. Consequently, this chapter aims to equip stakeholders in basketball, from players to coaches, with a deeper comprehension of how Artificial Intelligence technologies can enhance athletic performance and strategic decision-making, thereby translating complex data into actionable insights.