Fundamental matrix estimation is difficult since it is often based on correspondences that are spoilt by noise and outliers. Outliers must be thrown out via robust statistics, and noise gives uncertainty. In this article we provide a closed-form formula for the uncertainty of the so-called 8 point algorithm, which is a basic tool for fundamental matrix estimation via robust methods. As an application, we modify a well established robust algorithm accordingly, leading to a new criterion to recover point correspondences under epipolar constraint, balanced by the uncertainty of the estimation.