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Preanalysis plans (PAPs) have become an important tool for limiting false discoveries in field experiments. We evaluate the properties of an alternate approach which splits the data into two samples: An exploratory sample and a confirmation sample. When hypotheses are homogeneous, we describe an improved split-sample approach that achieves 90% of the rejections of the optimal PAP without requiring preregistration or constraints on specification search in the exploratory sample. When hypotheses are heterogeneous in priors or intrinsic interest, we find that a hybrid approach which prespecifies hypotheses with high weights and priors and uses a split-sample approach to test additional hypotheses can have power gains over any pure PAP. We assess this approach using the community-driven development (CDD) application from Casey et al.(2012) and find that the use of a hybrid split-sample approach would have generated qualitatively different conclusions.