What Are Stats Metrics To Analyze How Well One Column Predicts Another Column
Other possible evaluation measures are:


Mean Absolute Error (MAE): $\frac{\sum_{i=1}^n{\| y_i - x_i\|}}{n}$
R^2: also known as coefficient of determination, the formula is rather lengthy, but a detailed definition, as well as a motivation, can be found here
Root Mean Squared Logarithmic Error (RMSLE): $\sqrt[]{\frac{1}{n}\sum_{i=1}^n{(\log(y_i + 1) - \log(x_i + 1))^2}}$
Explained Variance Score: $1 - \frac{Var(y - x)}{Var \ y}$ more here and here.
Mean absolute percentage error (MAPE): see the wikipedia for the formula and major drawbacks of this measure.
Median Absolute Error (MAE2): $Median(| y_1 - x_1 | \dots | y_n - x_n |)$


These measures, as well as others, can be found here together with some Python code.