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Friday, May 18
Sports and Game Analytics
Fri, May 18, 5:15 PM - 6:15 PM
Lake Fairfax B

Predict Basketball Team Winning Record (304592)

*Mason Chen, Stanford OHS 
Patrick Giuliano, MorrillLearning Center 

Keywords: Basketball Sports, Predictive Modeling, Statistics, Regression

This paper is to build an empirical model to predict the NBA team winning percentage based on their team offensive, defensive, and differential statistics by collecting historical data during 2003-2016. A multiple linear regression model was derived to predict the team winning record with R-Square > 0.95. The multi-linearity concerns were addressed by looking at the Variance Inflation Factor > 10. The regression model has identified 3-point Percentage, Turn Over, and Point per Game most critical to the team offensive efficiency. In defense, how to defend the rebound and opponent’s field goal percentage are most critical. Warriors’ 2015-2016 team record has been identified as an extreme outlier since their winning formula and team statistics are significantly different from the remaining 29 teams. The model built based on 2003-2016 data was further validated by the new season 2016-2017. The model accuracy was proved to be within +/-5% winning percent of the predicted target across all 30 teams. This model can provide NBA coaches and general managers how to draft, recruit, trade, or sign particular players to build a desired Championship team.