In randomized controlled trials (RCTs) where the outcome is a student-level, study-collected test score, a particularly valuable piece of information is a study-collected baseline score from the same or similar test (a pre-test). Pre-test scores can be used to increase the precision of impact estimates, conduct subgroup analysis, and reduce bias from missing data at follow up. Although administering baseline tests provides analytic benefits, there may be less expensive ways to achieve some of the same benefits, such as using publically available school-level proficiency data. This paper compares the precision gains from adjusting impact estimates for student-level pre-test scores (which can be costly to collect) with the gains associated with using publically available school-level proficiency data (available at low cost), using data from five large-scale RCTs conducted for the Institute of Education Sciences. The study finds that, on average, adjusting for school-level proficiency does not increase statistical precision as well as student-level baseline test scores. Across the cases we examined, the number of schools included in studies would have to nearly double in order to compensate for the loss in precision of using school-level proficiency data instead of student-level baseline test data.