Leveraging Artificial Intelligence for Automated Qualifier Determination in NCAA Division II Diving: A Technical Case Study

Abstract

The integration of artificial intelligence (AI) in sporting event administration has expanded in recent years, offering increased accuracy, efficiency, and standardization in decision-making processes. This case study investigates the use of ChatGPT, a large language model (LLM), to automate and validate the selection of championship qualifiers in the NCAA Division II Diving Championships - an administrative process known for its complexity and susceptibility to human error. Through structured prompt engineering, iterative testing, and verification using official qualifying procedures, the study demonstrates the feasibility of employing AI to support operational reliability. The findings highlight opportunities and limitations for AI adoption in sport management settings and provide recommendations for future implementation.