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Plasticity in solids is dependent on microstructural history, temperature, and loading rate, and sample-dependent knowledge of yield points in structural materials adds reliability to mechanical behavior. Yielding is commonly measured through controlled mechanical testing, in ways that either distinguish elastic (stress) from total deformation measurements or identify plastic slip contributions. In this paper, we show that yielding can be unraveled through statistical analysis of total-strain fluctuations during the evolution sequence of profiles, measured in situ, through digital image correlation. We demonstrate two distinct ways of quantifying yield locations in widely applicable crystal plasticity models for polycrystalline solids, using either principal component analysis or discrete wavelet transforms. We test and compare these approaches for synthetic data of polycrystals and a variety of yielding responses through changes in applied loading rates and strain-rate sensitivity exponents.