Let me be an Excel sidekick among statistical analysis heroes.

I saw the OKCupid stuff as well, I ran a quick test in Excel to see if the variance in attractiveness contributes to the decision to meet beyond the attractiveness mean. Here's what I got doing regression, with apologies for the hideous formatting:

 ......... Coefficients ..Standard Error ..t Stat ..P-value
Intercept -0.569931558 0.042946471 -13.27074239 4.65749E-35
avg_attr 0.156634411 0.005238302 29.90175402 2.6299E-117
attr_std 0.028596624 0.012485497 2.290387431 0.022377128

The dependent variable is match percent (percent of people who decided they want to date the ratee), avg attr is the mean and attr std the standard deviation of the physical attractiveness ratings. attr std is not the attractiveness to STDs ;-)

As we can see, the coefficient for attractiveness deviation is significantishly positive. It actually has a small negative correlation with match and a larger negative correlation with attractiveness. This means that there is more consensus on the attractiveness of prettier people. Holding attractiveness constant, variance, which is visible for a single rater as an "unusual look", increases the chances that people will want to date you. Put some flowers in your hair!