The integration of visual, lexical, and oculomotor information is a critical part of reading. Mr. Chips is an ideal-observer model that combines these sources of information optimally to read simple texts in the minimum number of saccades. This model provides a computational framework for interpreting human reading saccades in both normal and low vision. The purpose of this paper is to report performance of the model for conditions emulating reading with normal vision--a visual span of nine characters, multiplicative saccade noise with a standard deviation of 30%, and texts based on three full-length children's books. Comparison of fixation locations by humans and Mr. Chips revealed: (1) that both exhibit very similar word-skipping behavior; (2) both show initial fixations near the center of words, but with a systematic difference suggestive of an asymmetry in the human visual span; and (3) differences in the pattern of refixations within words that may uncover non-optimal lexical inference by human readers. A human context effect--30% difference in mean saccade size between continuous text and random sequences of words--was very similar to the 25% effect for the model associated with a corresponding difference in the predictability of text words. Overall, our findings show that many of the complicated aspects of human reading saccades can be explained concisely by early information-processing constraints.