This paper investigates the effectiveness of automatic span retrieval methods for translating SQuAD to German through a comparative analysis across two scenarios. First, we assume no gold-standard target data and find that TAR, a method using an alignment model, results in the highest QA scores. Secondly, we switch to a scenario with a small target data and assess the impact of retrieval methods on fine-tuned models. Our results indicate that while fine-tuning generally enhances model performance, its effectiveness is dependent on the alignment of training and testing datasets.