Predict Baskerball Team Winning Record
Predict Basketball Team Winning Record
Charles Chen
Applied Materials
Mason Chen
Stanford University OHS
Build an empirical model to predict the NBA team winning percentage based on team offensive, defensive, and differential statistics by collecting historical data during 2003-2016. The raw data have been standardized through Z transformation to remove mean and large variance bias effect. A multiple linear and step regression model was derived to predict the team winning record. After trimmed the insignificant regression terms, the derived model can predict team winning percent with R-Square > 0.95. The multi-linearity concerns were addressed by looking at the Variance Inflation Factor > 10. The redundant terms were removed to avoid over-fit risk. The regression model has identified 3-point Percentage, Turn Over, and Point per Game most critical to the team offensive efficiency. Warriors' 2015-2016 team record has been identified as an extreme outlier. The 2nd-order and Interaction Terms were added to enhance the prediction accuracy. The nonlinearity terms have indicated the complexity of the basketball team behaviors. The model was further validated by the new season 2016-2017. The model accuracy was proved to be within +/-5% of the predicted target across all 30 teams.