• Different languages concentrate information in different areas of the word. • We hypothesize that readers target words optimally to maximize information uptake. • We test this hypothesis with artificially constructed lexicons and eye tracking. • We support our analyses with a Bayesian cognitive model of visual word recognition. • Our findings suggest lexicon-level information might play a role in natural reading. Skilled readers use multiple heuristics to guide their eye movements during reading. One possible cue that readers may rely on is the way in which information about word identity is typically spread across words. In many (but not all) languages, words are, on average, more informative on the left, predicting that readers should have a preference for left-of-center fixation when targeting words. Any such effect will, however, be modulated by important perceptual constraints and may be masked by various confounding factors. In three experiments with artificially constructed lexicons, we provide causal evidence that the way in which a language distributes information affects how readers land on words. We further support our analyses with a Bayesian cognitive model of visual word recognition that predicts where readers ought to fixate in order to minimize uncertainty about word identity. Taken together, our findings suggest that global properties of the lexicon may play a role in isolated word targeting, and may therefore make a contribution to eye movement behavior in more natural reading settings. [ABSTRACT FROM AUTHOR]