Author:
Bowman James K., ,Boone R. Thomas,Zaichkowsky Leonard,Goldman Scott,Auerbach Alex, , , ,
Abstract
Introduction In the realm of competitive athletics, numerous variables have been examined for predictive utility with respect to player selection/development and outcomes on the field. Notwithstanding important advances, the current predictors only account for a modest amount of variance in outcomes of relevance in the National Football League (NFL). Objective The primary objective of this study was to investigate the predictive validity of a new measure of athletic intelligence, the Athletic Intelligence Quotient (AIQ), which is based on the empirically supported Cattell-Horn-Carroll (CHC) Theory of Intelligence. The predictive validity of the AIQ was determined in relation to performance metrics from 146 NFL players across several seasons. Results Hierarchical regression analyses indicate that specific AIQ factors accounted for a statistically significant increase in the explanation of variance beyond the current level of evaluation for several performance metrics (e.g., career approximate value; sacks, tackles, rushing yards). Further, specific factors of the AIQ are related to position specific statistics, offering the possibility that performance prediction can be focused in for the specific skills required by a given position. Discussion Given the recent impact of analytics in professional sports, and the significant findings noted in the current investigation, the authors discuss the potential importance of the AIQ in the selection and coaching processes.
Cited by
6 articles.
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