Sheel Patel

What are the most important factors in predicting an NBA player’s success in the league?

Started Apr. 18, 2024

Abstract or project description

This paper investigates the key predictors of NBA career success by analyzing the early-career performance of first-round draft picks from 2005 to 2017. The study focuses on the first two years of a player's career, using a range of statistical metrics to identify which factors most strongly correlate with career earnings. Key variables analyzed include points per game (PPG), assists/turnover ratio (AST/TO), rebounds per game (RPG), win shares (WS), and other advanced statistics. This was used as the basis for the determination of a second model and what will be the most significant predictors of financial success in the NBA over a long-term period. This analysis uses several multiple linear regression models to find that the most significant predictors of career success statistically were Total PPG and WS, where the scoring and overall contribution to winning had the highest positive effect on earnings. In the second model, the key variables are narrowed down to five, and it was evident that 3P% also plays a crucial role. The models explain about 50% of the variance in career earnings, which strongly underlines the relevance of early performance measures. These findings suggest that while scoring and team contributions are key, other factors such as playing time, team quality, and off-court influences all impact a player's arc. However, the work makes a case for improved draft picks and the assessment of players by showing which early-career statistics best predict long-term success.