Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a unidimensional IRT model for unfolding polytomous responses. It yields single-peaked, non-monotonic item characteristic curves that predict a higher item score to the extent that an individual is located close to an item on the underlying latent continuum. A simulation was performed to examine the characteristics of these new item fit indices under the GGUM, as well as a traditional likelihood ratio x[superscript 2] test (G[superscript 2]). All variants of S-X[superscript 2] exhibited reasonable Type I error rates, but that for G[superscript 2] was more erratic. The new indices exhibited variable power to detect misfit. Two new item fit tests are recommended for use based on simulation results. (Contains 1 figure and 4 tables.)