MLB-Moneyball-EDAs

Project Descriptions:

Multivariate Linear Regression using 2021 MLB batting data.ipynb

Python jupyter notebook that takes in 2021 MLB batting data (OBP and HITs) and by using a multivariate linear regression model, can predict batting average on test data with an R squared of 0.74

The-Baseball-Labor-Markets-Valuation-of-On-Base-and-Slugging-Percentage ~ Hakes and Sauer Table 3.ipynb

Python Jupyter notebook that reproduces table 3 of Hakes and Sauer (Moneyball analysis) by running linear regressions on Salary ~ OBP and SLG from 2000 to 2004. Utilizing pandas, numpy, seaborn, matplotlib, abn statsmodel libraries.

The Impact of OBP and SLG on Winning for 1999-2003 MLB (Reproducing Hakes and Sauer Table 1).ipynb

Python Jupyter notebook that reproduces table 1 of Hakes and Sauer (Same Analysis used in moneyball). This table compares the impact of OBP and SLG on winning percentage. Utilizing pandas, numpy, matplotlib, and statsmodels libraries.