Research Papers

Farrell, Sean; Laity, Ethan; Laughlin, Dave; Pennebaker, James W.

This paper explores how psychological factors, assessed through natural language analysis, can predict NBA player success alongside traditional metrics such as physical performance statistics. Using language psychology tools, we analyzed transcripts of college athletes' interviews to create psychological profiles which were used as features for machine learning algorithms, finding these could predict NBA roster success with 63% accuracy, increasing to 87% when incorporating playing statistics and physical traits. Survival analysis also demonstrates the ability to forecast career longevity and impact. The research suggests that incorporating psychological insights into recruitment could transform talent identification across elite sports.