The structure and distribution of entries in the lexicon impose strong constraints on word recognition. A construct of value in operationalizing such constraints is that of uniqueness point Computed by reference to a phonetic dictionary, it is the earliest moment at which a word can be uniquely distinguished from all others in terms of a sequential phoneme by phoneme comparison. There is empirical evidence that the uniqueness point bears a close relationship to the recognition point, the moment at which a word can actually be recognized on the basis of incoming acoustic information. In reality, recognition depends upon noisy and unreliable acoustic information, making categorial phonetic decisions difficult, and the value of a uniqueness point, questionable. Minimal deviation is proposed as a new construct to represent the extent of mismatch between a given word and the closest non-identical word in the lexicon. A computer analysis of a large phonetic dictionary shows that on average minimal deviation increases almost constantly with stimulus input subsequent to the uniqueness point. This simulation suggests that the empirical success of the uniqueness point as an indicator of word recognition performance may be accounted for by this subsequent increase in deviation in addition to the single mismatch at the uniqueness point itself