Statistics 4240 - Data Mining

Compared to the actural value of the "missing" data in Homework2, with my result, it turns out that the linear model gives the smallest RMSE (39.97). Ridge and Lasso gives 42.83 and 43.27 respectively( I only run the 10-fold cross validation once to choose the lamda/bound) . Is it reasonable that linear regression is better than ridge and lasso in some case?

Usually ridge and lasso are better than plain linear, but in a real application, anything can happen!