Even relatively closely related languages can differ greatly in word order. Take English and German for instance.
English is pretty boringly subject-verb-object whereas in German the finite verb must come second, all other verbs go to the end, and separable prefixes also all go to the end.
According to machine translation lore, the systems work better in inverse proportion to the number of linguists in the project.
So given a complete lack of understanding of the source language how do machine translation systems manage these different word orders?
Do they actually have to know some linguistics after all and hence are not so pure as touted? Or do they actually do worse that touted under these conditions. Or are there statistical methods that somehow take into account even word ordering differences without recourse to linguistic knowledge?