Finding Common Characteristics Among NBA Playoff and Championship Teams: A Machine Learning Approach

TL;DR

This study uses machine learning to identify key defensive and offensive factors that distinguish NBA playoff and championship teams over 17 seasons, highlighting the importance of defensive metrics.

Contribution

It introduces a machine learning framework combining classification trees, random forests, and neural networks to analyze NBA team data for playoff and championship prediction.

Findings

Defensive metrics like steals and opponent assists are crucial for playoff qualification.

Made two-point shots and defensive rebounding are vital for winning championships.

Opponent three-point shots negatively impact championship chances.

Abstract

In this paper, we employ machine learning techniques to analyze seventeen seasons (1999-2000 to 2015-2016) of NBA regular season data from every team to determine the common characteristics among NBA playoff teams. Each team was characterized by 26 predictor variables and one binary response variable taking on a value of "TRUE" if a team had made the playoffs, and value of "FALSE" if a team had missed the playoffs. After fitting an initial classification tree to this problem, this tree was then pruned which decreased the test error rate. Further to this, a random forest of classification trees was grown which provided a very accurate model from which a variable importance plot was generated to determine which predictor variables had the greatest influence on the response variable. The result of this work was the conclusion that the most important factors in characterizing a team's playoff eligibility are a team's opponent number of assists per game, a team's opponent number of made two point shots per game, and a team's number of steals per game. This seems to suggest that defensive factors as opposed to offensive factors are the most important characteristics shared among NBA playoff teams. We then use neural networks to classify championship teams based on regular season data. From this, we show that the most important factor in a team not winning a championship is that team's opponent number of made three-point shots per game. This once again implies that defensive characteristics are of great importance in not only determining a team's playoff eligibility, but certainly, one can conclude that a lack of perimeter defense negatively impacts a team's championship chances in a given season. Further, it is shown that made two-point shots and defensive rebounding are by far the most important factor in a team's chances at winning a championship in a given season.