Magnetic Resonance Fingerprinting (MRF) maps various tissue properties and system parameters simultaneously. MRF time series, which are matched to a precalculated dictionary, are often obtained with fast acquisition of low resolution images with undersampled spiral trajectories using a regular sampling pattern. In this work, we propose to order a set of spiral trajectories based on dictionary variance instead of the standard sequential or golden-angle ordering. Phantom and in vivo results show that the variance based optimized order converges faster to expected true values. The optimized order does not limit other MRF optimization approaches and can be applied to any MRF sequence.