Abstract:

The main purpose of this study is to determine which factors have an important role in National Basketball Association (NBA) players’ shooting accuracy. To achieve this purpose, player-based raw-dataset for each match on the 2014-2015 NBA season is used in this study. Seven different machine learning algorithms are applied and also 10-fold cross-validation with 10-repeat process is performed to avoid the overfitting problem. Nine independent variables and one binary dependent variable are included in the analysis. According to the results of the analysis, k-nearest neighbor algorithm is the best machine learning algorithm among other algorithms that are used in the analysis in order to predict whether basketball player can make a shot or not. Shot Distance, distance of closest defense player and touch time are identified as the most important factors affecting player’s successful field goal accuracy. Since the successful field goal performance is very influential in winning the game, the results of this study can be used as a guide for training programs to basketball players and team coaches. 

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