  A wide variety of transition-based algorithms are currently used for
dependency parsers. Empirical studies have shown that performance varies across
different treebanks in such a way that one algorithm outperforms another on one
treebank and the reverse is true for a different treebank. There is often no
discernible reason for what causes one algorithm to be more suitable for a
certain treebank and less so for another. In this paper we shed some light on
this by introducing the concept of an algorithm's inherent dependency
displacement distribution. This characterises the bias of the algorithm in
terms of dependency displacement, which quantify both distance and direction of
syntactic relations. We show that the similarity of an algorithm's inherent
distribution to a treebank's displacement distribution is clearly correlated to
the algorithm's parsing performance on that treebank, specifically with highly
significant and substantial correlations for the predominant sentence lengths
in Universal Dependency treebanks. We also obtain results which show a more
discrete analysis of dependency displacement does not result in any meaningful
correlations.

Computation and Language