  This article revisits an analysis on inaccuracies of time series averaging
under dynamic time warping conducted by \cite{Niennattrakul2007}. The authors
presented a correctness-criterion and introduced drift-outs of averages from
clusters. They claimed that averages are inaccurate if they are incorrect or
drift-outs. Furthermore, they conjectured that such inaccuracies are caused by
the lack of triangle inequality. We show that a rectified version of the
correctness-criterion is unsatisfiable and that the concept of drift-out is
geometrically and operationally inconclusive. Satisfying the triangle
inequality is insufficient to achieve correctness and unnecessary to overcome
the drift-out phenomenon. We place the concept of drift-out on a principled
basis and show that sample means as global minimizers of a Fr\'echet function
never drift out. The adjusted drift-out is a way to test to which extent an
approximation is coherent. Empirical results show that solutions obtained by
the state-of-the-art methods SSG and DBA are incoherent approximations of a
sample mean in over a third of all trials.
