Evaluating the Effects of Physiological and Kinematic Factors on Basketball Shooting Accuracy

Abstract

Understanding the factors that influence basketball shooting performance is important for improving player development and competitive strategy. This study examined whether physiological measures or kinematic variables better explain and predict basketball shooting accuracy. Agility and shooting performance metrics were collected from NBA Draft Combine data, and statistical analyses, including ANOVA and regression modeling, were used to evaluate the relationships between these variables. Although significant physiological differences were observed between playing positions, particularly between centers and other players, the correlations between physiological measures and shooting performance were generally weak. 

Beyond physiological measures, kinematic variables also play an important role in determining basketball shooting outcomes. Kinematic data derived from motion capture recordings of repeated free throw attempts were analyzed by calculating joint angles of the shoulders, elbows, and knees and comparing them between made and missed shots. Independent samples t-tests showed no statistically significant differences at the moment of ball release, but significant differences were observed before and after release. Machine learning models, including random forest and logistic regression, were then used to evaluate whether these kinematic variables could predict shot outcomes. 

Overall, kinematic variables demonstrate greater relevance than physiological measures in distinguishing between made and missed shots. Features such as shooting velocity and dominant-side joint angles were identified as particularly influential. These findings suggest that shooting mechanics and coordinated joint movement play a more important role in shot success than general athletic attributes and may provide useful insights for basketball training and player development.