Focal points are fascinating effects that emerge from various constellations, for example when light passes through narrow gaps or when objects are seen through lenses or mirrors. These effects can be challenging to render, as paths need to pass through small regions that are not always known beforehand and can occur freely in space. Specialized algorithms exist for some effects, but many of them rely on Markov chain Monte Carlo integration, which is known to suffer from uneven convergence undesirable in practice. Path guiding methods are a promising alternative, but existing techniques only handle a subset of focal effects. We propose a novel form of guiding that is specifically tailored to identify focal points and sample them in accordance to their image contribution. Our technique is the first to unify all focal effects in a single framework and we demonstrate that it can render effects that previous state-of-the-art techniques are unable to handle.