Within this work, we present a method for fast characterization and statistical analysis of structural and electrical crystal properties. By this, we investigate the impact of grain size and grain shape distribution in the lower part of the brick on the defect development in the upper part of the brick. Our method is based on fast measurements on as-cut wafers, namely photoluminescence imaging and reflection or infrared transmission images. We combine the extracted information and isolate dislocation structures from recombination active grain boundaries via image-processing. Two large data sets (more than 40 bricks) of different materials allow us to quantify the assumed correlation between grain structure and dislocation development. The results confirm that the relative length of dark lines as a part of dislocation clusters in the upper brick part shows a locally linear correlation with the square root of a meaningful grain area measure in the lower brick part (Pearson coefficient R between 0.80 and 0.88). It also correlates with the inhomogeneity measures for grain area and shape (Pearson coefficient R about 0.88). As a result, changes in the crystallization process may be targeted according to the grain structure in the lower part of the brick. In the future, this method may serve to improve the prediction of solar cell results based on wafer-data.