Data analytics are an increasingly popular method for talent identification, and are used for a variety of decision making purposes, such as rotations and playing time. However, coaches often rely on their percep-tions and experiences to identify talent and player attributes that are important to success. Therefore, the purposes of this study were to evaluate differences between coach perceptions of player ability against actual performances as well as to determine whether these perceptions differed as a head or assistant coach. Participants were six (two head; four assistant) college coaches who were asked to collectively identify the five most important attributes when evaluating a basketball player. Then, before the season began, all coaches were asked to independently score each of their athletes on these attributes using a 100mm Visual Analog Scale. These scores were compared to player performances during the season. Results were mixed, and while there were correlations between some player performance variables and coach perceptions, they varied wildly, and coaches` perceptions of their athletes had little consistent correlation to their performances. Furthermore, there were few agreements between head coaches and their assistants or between assistants. Findings suggest that while coach perceptions and talent identification have their place, the use of data analytics in sports may provide additional support when making coaching decisions such as playing time. Therefore, coaches should recognize their own limitations of player talent and balance these "feelings" with statistical evidence.
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