Thesis

The Importance of NBA Box Score Statistics and the Value of Statistical Outbursts

The Nation Basketball Association (NBA) has embraced the 21st Century by increasing its use of advanced analytics. New and evolving statistics can be used to determine how efficient a player is while he is on the court. However, even though a player is being efficient, his performance may not lead to victories. This paper creates a Decision Tree Classifier model that helps to determine, through game by game statistics, an NBA player’s value to a team’s chance to win. Players tested in the model demonstrate that having a high PER does not always lead to being a great asset for their team. The models created also distinguish what statistics are important for All-Star and Starter level players. The All-Star model favors individually focused, offensive statistics; whereas the Starter model places a higher level of importance on team statistics.

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