||The goal of this research was to evaluate fractal statistics as an alternative method of quantifying eye movement when viewing pictures of different affective valence. Eye movement researchers have traditionally used measures of fixations and saccade variability to differentiate viewing patterns across affective picture groups and individual differences that relate to these fixation statistics. Research examining fixation statistics when viewing pleasant and unpleasant pictures has both found and failed to find differences between metrics. Inconsistent findings appear to be driven by the sensitivity of fixation metrics, as well as differing methodologies. Eye tracking with contemporary tracking devices produces voluminous time series data ideal for analytical approaches that quantify patterns occurring on a temporal scale; fractal dimension and lacunarity are two types of fractal statistics that characterize temporal and spatial patterns. Variogram, Madogram, and Hall-Wood estimates of fractal dimensionality, lacunarity slopes, and fixation indices were calculated for time series data generated by individuals viewing sequences of pictures with unpleasant, pleasant, or neutral valence. Nature target pictures were embedded within each picture group to evaluate carry over effects from viewing affective pictures. Fractal statistics were compared to fixation statistics and their ability to differentiate eye movement across picture groups using a series of linear mixed models where fractal statistics and fixation statistics were treated as outcome variables. Fractal dimensions were unable to differentiate eye movement in pleasant and unpleasant picture groups, displaying a similar pattern to fixation statistics, except for number of fixations, which differed across pleasant and unpleasant picture groups. Fractal dimensions were, however, able to differentiate pleasant/unpleasant pictures when compared to neutral picture groups, also consistent with the pattern observed with fixation statistics. Emotional reactivity, trait anxiety, depression, and state affect were included as random effects to examine the ability of individual differences to predict the outcome and control for factors that have the potential to influence eye movement. Fixation statistics were not predicted by individual differences whereas fractal dimensions were predicted by emotional reactivity, but only for y-axis eye movement. Target pictures were viewed differentially depending on which affective picture group they were presented in; however, differences between unpleasant and pleasant picture groups remained elusive. Eye movement was largely similar across pleasant and unpleasant picture groups whether using fractal or fixation statistics. Lacunarity proved most effective in differentiating eye movement across pictures groups where less negative slopes were associated with the unpleasant picture group. Fractal statistics appear to be equally as useful as fixation statistics for the purpose of differentiating eye movement across affective picture groups. Fractal statistics also appear to be a sensitive measure of individual differences in emotional reactivity. Overall these results support the inclusion and consideration of fractal statistics in the analysis of eye movement.