•  
  •  
 

Author ORCID Identifier

https://orcid.org/0000-0002-8729-3031

DOI

https://doi.org/10.7290/jasm17i4UV

Abstract

Advanced analytics and artificial intelligence (AI) occupy an increasing position and function within the institutional setting of collegiate athletics. At both the departmental and programmatic levels, collegiate athletic stakeholders have consistently increased their reliance on AI and data within decision-making processes and strategic development. Given its importance to competitive success, AI interfaces such as machine-based learning, predictive analysis, and natural language processing has been increasingly integrated within the recruiting process of prospective and transfer athletes. However, while such reliance on data-driven strategies and predictive analytics hold competitive value within the talent identification and evaluation process, the relational role of the recruitment of prospective athletes remains foundational to successful recruiting in collegiate athletics. This manuscript operationalizes the formation of recruiting within this setting and discusses the limited performative value of AI within the traditional college athlete recruiting process.

Share

COinS