Predict the Winning Ratio of Major League Baseball Teams: Generalized Pythagorean Formula Approach

This study investigates the winning ratio of Major League Baseball (MLB) season games by using a generalized Pythagorean formula. Based on the method of regression analysis, this study verifies the ability of the generalized Pythagorean formula to predict MLB team winning rates. Empirical results show that the multivariate regression model has a highest adjusted R2 (0.9126) than other regression models. In addition, either MSE or MAE of in-sample and out-of-sample, the generalized Pythagorean formula derived from Cobb-Douglas production function has the lowest values than other versions of Pythagorean formula. Based on this generalized Pythagorean formula, team’s managers can acquire potential rookies through drafts or player trades to recruit the players they need to achieve the team’s goals.