To better understand patterns of prekindergarten applications and lottery outcomes, ideal analyses would draw on a rich set of background data on children and families and explore variation in participation and match rates across demographic and socioeconomic groups. But the DC prekindergarten lottery collects minimal background data because of its primary mission to support a streamlined and accessible application system. Instead, we use families' listed addresses, geocoded and linked to American Community Survey five-year microdata on community characteristics at the Public Use Microdata Area (PUMA) level, to proxy for the individual characteristics of prekindergarten applicants and matched and wait-listed applicants. Although this approach has limitations, it provides the best opportunity to learn about applicants and their families before school enrollment. Additional details on methods and limitations can be found in our report, Who Wins the Preschool Lottery? (Greenberg et al. 2020). (author abstract)