Multiple Regression: Predicting the Total Number of Wins using Average Points Scored, Average Relative Skill, Average Points Differential and Average Relative Skill Differential

The coach also wants you to consider the average points differential and average relative skill differential as predictor variables in the multiple regression model. This multiple regression model has the total number of wins as the response variable, and average points scored, average relative skill, average points differential and average relative skill differential as predictor variables. This regression model will help your coach predict how many games your team might win in a regular season based on metrics like the average score, average relative skill, average points differential and average relative skill differential between the team and their opponents.

OLS Regression Results Dep. Variable: total wins R-squared: 0 . 878 Model : OLS Adj . R-squared: 0. 877 Method : Least Squares F-statistic: 1102. Date : Sat, 13 Aug 2022 Prob (F-statistic) : 3. 07e-278 Time : 03 : 15 : 48 Log-Likelihood : -1815 .5 No. Observations : 618 AIC : 3641. Df Residuals: 613 BIC : 3663. Df Model: 4 Covariance Type: nonrobust coef std err t P> t [0 . 025 0 . 975] Intercept 34.5753 25. 867 1. 337 0. 182 -16 .223 85.373 avg_pts 0. 2597 0 . 043 6. 070 0 . 000 0. 176 0 . 344 avg_elo_n -0 . 0134 0 . 017 -0. 769 0 . 442 -0 . 048 0 . 021 avg_pts_differential 1 . 6206 0. 135 12 . 024 0. 000 1 . 356 1. 885 avg_elo_differential 0 . 0525 0 . 018 2. 915 0 . 004 0 . 017 0 . 088 Omnibus : 193 . 608 Durbin-Watson : 0. 979 Prob (Omnibus ) : 0 . 000 Jarque-Bera (JB) : 598 . 416 Skew: -1.503 Prob ( JB) : 1. 14e-130 Kurtosis : 6. 769 Cond. No. 2. 11e+05 Warnings : [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. [2] The condition number is large, 2.1le+05. This might indicate that there are strong multicollinearity or other numerical problems