This example evaluates potential predictors of baseball player salaries by computing r-squared values through linear regression. It uses pandas for data management, adding derived features like age, experience, and experience/age, and scipy’s `stats.linregress` to test each variable. The data comes from a baseball CSV file, and for physical attributes it renders scatter plots with the fitted regression line using matplotlib. The code prints r-squared results for both physical and skill-based variables, highlighting experience/age as the strongest predictor.