2022, Vol. 9, Issue 6, Part B

The purpose of the study was to develop a Statistical model to predict the outcome of one of the teams in the NBA i.e. the Golden State Warriors. The last eight seasons' data were taken into consideration for the statistical analysis. These probabilities can assist a team captain or management in considering a certain offensive, defensive, or playing strategy for the next season. The data was collected from the last eight seasons of the NBA i.e. from 2014 to 2022. Data from 656 matches were recorded, and the dependent variable selected for this study was Match Outcome (Win/Loss). Field Goals Made (FGM), Field Goals Attempted (FGA), Three-Point Field Goals Made (3 PM), Three-Point Field Goals Attempted (3PA), Free Throws Made (FTM), (FTA) Free Throws Attempted, and Rebound (REB), these variables were chosen to serve as the predictor variables. For this study, the data was taken from the last eight season matches of the NBA and further, it was interpreted through a statistical technique, binary logistic regression which was used to predict the outcome of a match (Win/Loss). It was found that the developed logistic regression model was significant. According to the statistical significance of the predictor variables, they were numerically weighted and can be used to predict the match outcome. Out of seven predictor variables, only the variable Team score was included in the prediction model with a coefficient of determination (R2) of.750 (Cox & Snell) and .1.000 (Nagelkerke). 95.87% of match results were correctly classified by the model.