Schloss and Palmer (VSS-2009) reported that 80% of the variance in average color preferences for 32 chromatic colors by American participants was explained by an ecological measure of how much people like the objects that are characteristically those colors. The weighted affective valence estimate (WAVE), computed from the results of a multi-task procedure, outperformed three other models containing more free parameters. One group of participants described all objects that came to mind for each color, which were compiled into 222 categories of object descriptions. A second group rated how similar each presented color was to the color of each object described for that color. A third group rated their affective valences (positive-to-negative) for each object from its verbal description. The WAVE for each color is the average valence for each object, weighted by the rated similarity of the given color to the described object. The WAVEs were strongly correlated with average color preference ratings (r=.89). We now show that when WAVEs are calculated at the level of individual participants, they account for significantly more variance in the same individual's color preference ratings than do average WAVEs computed from the entire group. A new group of participants rated their preferences for all 32 colors, after which they provided their own idiosyncratic object descriptions for each color and rated their affective responses to them. They also rated their affective response to each of the 222 object descriptions provided by the original group. The correlation between the individual's color preferences and his/her individual WAVEs, computed from their personal ratings of the 222 object valences, proved to be reliably better than the fit of the group WAVEs, computed from the average affective ratings. Together, the cone-contrast model (Hurlbert & Ling, 2007) and the WAVE predictor explain 58% of the variance in individual participants.