This paper considers two procedures for estimating the center of a symmetric distribution, which use the observations themselves to choose the form of the estimator. Both procedures begin with a family of possible estimators. We use the observations to estimate the asymptotic variance of each member of the family of estimators. We then choose the estimator in the family with smallest estimated asymptotic variance and use the value given by that estimator as the location estimate. These procedures are shown to be asymptotically as good as knowing beforehand which estimator in the family is best for the given distribution, and using that estimator.