===== OLS Regression Results ======= total_wins R-squared: Dep. Variable: 0.837 Model: OLS Adj. R-squared: 0.837 Method: Least Squares F-statistic: 1580. Date: Tue, 20 Feb 2024 Prob (F-statistic): 4.41e-243 Time: 17:25:17 Log-Likelihood: -1904.6 No. Observations: 618 AIC: 3815. Df Residuals: Df Model: Covariance Type: 615 BIC: 3829. 2 nonrobust ======= coef std err t P>|t| [0.025 0.975] Intercept -152.5736 avg_pts avg_elo_n ======== 0.3497 0.1055 4.500 0.048 0.002 -33.903 0.000 -161.411 -143.736 7.297 0.000 0.256 0.444 47.952 0.000 0.101 =====: 0.110 === Omnibus: Prob (Omnibus): Skew: Kurtosis: 89.087 Durbin-Watson: 0.000 Jarque-Bera (JB): -0.869 Prob(JB): 4.793 Cond. No. 1.203 160.540 1.38e-35 3.19e+04 ==== Warnings: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. [2] The condition number is large, 3.19e+04. This might indicate that there are strong multicollinearity or other numerical problems.