THE EFFECTIVENESS OF DIFFERENT MACHINE LEARNING ALGORITHMS ON BASKETBALL PLAYERS’ SHOOTING PERFORMANCE

Abstract

Bu çalışmanın temel amacı, National Basketball Association (NBA) oyuncularının atış isabeti üzerinde hangi faktörlerin önemli bir rolü olduğunu belirlemektir. Bu amaca ulaşmak için, çalışmada 2014-2015 NBA sezonunda oynanan her bir maç için oyuncu bazlı ham veri seti kullanılmıştır. Yedi farklı makine öğrenme algoritması uygulanmış ve aynı zamanda aşırı uyum problemini önlemek için 10 kat çapraz geçerlilik prosedürü 10 defa tekrar edilmiştir. Analizde dokuz adet bağımsız değişken ve bir ikili bağımlı değişken kullanılmıştır. Bir basketbol oyuncusunun başarılı bir atış yapıp yapamayacağını tahmin etmek için kullanılan algoritmalar arasında en başarılı makine öğrenme algoritması k-en yakın komşu algoritmasıdır. Atış Mesafesi, en yakın savunma oyuncusunun mesafesi ve temas süresi oyuncunun başarılı bir atış yapmasını etkileyen en önemli faktörler olarak tanımlanır. Oyuncuların atış performansı oyunu kazanmada çok etkili olduğu için, bu çalışmanın sonuçları basketbol oyuncularına ve takım koçlarına antrenman programları için bir rehber olarak kullanılabilir.

Keywords

• Basketbol oyunu,makine öğrenmesi,performans analizi,sınıflama teknikleri

THE EFFECTIVENESS OF DIFFERENT MACHINE LEARNING ALGORITHMS ON BASKETBALL PLAYERS’ SHOOTING PERFORMANCE

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. 

Keywords

• Basketball games,classification techniques,machine learning algorithms,performance analysis

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