Reinforcement learning in professional basketball players

Erratum: Reinforcement learning in professional basketball players

Reinforcement learning in professional basketball players

Reinforcement learning in complex natural environments is a challenging task because the agent should generalize from the outcomes of actions taken in one state of the world to future actions in different states of the world. The extent to which human experts find the proper level of generalization is unclear. Here we show, using the sequences of field goal attempts made by professional basketb...

Anthropometric Characteristics of Spanish Professional Basketball Players

The study of elite basketball players' anthropometric characteristics alongside those of body composition contributes significantly to their profiling as professional athletes and plays an important role in the selection process, as these characteristics can have a significant impact on performance. In the current study, 110 professional basketball players from a series of Spanish professional ...

Vitamin D Deficiency Among Professional Basketball Players

BACKGROUND Vitamin D plays an important role in several systems of the human body. Various studies have linked vitamin D deficiency to stress and insufficiency fractures, muscle recovery and function, and athletic performance. The prevalence of vitamin D deficiency in the elite athletic population has not been extensively studied, and very few reports exist among professional athletes. HYPOTH...

Dynamic criteria: a longitudinal analysis of professional basketball players' outcomes.

This paper describes the fluctuations of temporal criteria dynamics in the context of professional sport. Specifically, we try to verify the underlying deterministic patterns in the outcomes of professional basketball players. We use a longitudinal approach based on the analysis of the outcomes of 94 basketball players over ten years, covering practically players' entire career development. Tim...