=============== Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Type: ========: total_wins Least Squares Tue, 20 Feb 2024 OLS Regression Results ======================== R-squared: OLS Adj. R-squared: F-statistic: Prob (F-statistic): 17:15:06 Log-Likelihood: 618 AIC: 616 BIC: 1 nonrobust ===== ======== 0.823 0.823 2865. 8.06e-234 -1930.3 3865. 3873. ===== coef std err Intercept -128.2475 3.149 -40.731 avg_elo_n 0.1121 0.002 53.523 =========== ======== ======= ======= ==================: Omnibus: 152.822 Durbin-Watson: t P>|t| [0.025 ===== 0.975] 0.000 0.000 -134.431 0.108 -122.064 0.116 =====: ======== 1.098 Prob (Omnibus): 0.000 Skew: Kurtosis: -1.247 Jarque-Bera (JB): Prob(JB): 393.223 6.009 Cond. No. ======= 4.10e-86 2.14e+04 == Warnings: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. [2] The condition number is large, 2.14e+04. This might indicate that there are strong multicollinearity or other numerical problems.