Two aspects of many real-world hiring situations affect hiring success in ways that are not well understood. One is that many applicant pools are relatively small, with perhaps fewer than 20 and sometimes fewer than 10 applicants. The other is that job seekers are likely to apply for more than one job at a time. Despite calls for more research that would be relevant to the small-scale hiring situation, scholars have given little attention to expected new-hire quality in small-pool hiring in general and even less to more specific questions of how that expected quality is affected if applicants apply for multiple jobs simultaneously. Most currently accepted methods linking expected new-hire quality to the selection ratio (or hiring rate) are based on the properties of large pools. The authors argue that those methods are based on the inherent, but dubious, assumption that all job seekers in a given applicant pool are pursuing that particular job and no other jobs. In the small-pool context, these factors have significant, and previously unrealized, negative effects on the expected quality of new hires when job seekers apply for multiple jobs at once. The authors present a conceptual development of a method, based on averages of order statistics, for estimating correct values of expected new-hire quality when pools are small and job seekers tend to apply for multiple jobs simultaneously. A series of simulations support the conclusion that the method yields accurate estimates.