We introduce a notion of halfspace for Hadamard manifolds that is natural in the context of convex optimization. For this notion of halfspace, we generalize a classic result of Grünbaum, which itself is a corollary of Helly's theorem. Namely, given a probability distribution on the manifold, there is a point for which all halfspaces based at this point have at least $\frac{1}{n+1}$ of the mass. As an application, the gradient oracle complexity of convex optimization is polynomial in the parameters defining the problem.