Regression yields much smaller standard deviation and the mean is off, what could be wrong?
The difference in standard deviation is nothing suspicious.  It is only to be expected, if you have a weak correlation.

Suppose the regression is y ~ x, i.e., y = ax + b.  Suppose that x only explains a small fraction of the variability in y, i.e., y is scattered all over the place and the least regression line only weakly fits the data.  Suppose also that the line is nearly horizontal (i.e., a is small).  Then the standard deviation of the predicted y-values will be small (since the line is nearly horizontal) but the standard deviation of the actual y-values might be large.

But really, the way to figure out what is going on is to visualize the data.  You should always start by visualizing the data.  Plot a scatterplot, and superimpose the least squares fit line on top of it.  I bet you'll immediately have a better sense of what might be going on.