Sample size can be chosen to achieve a specified width in a confidence interval. The probability of obtaining a narrow width given that the confidence interval includes the population parameter is defined as the power of the confidence interval, a concept unfamiliar to many practitioners. This article shows how to utilize the Statistical Analysis System (SAS) proc power procedure to determine an appropriate sample size and achieve sufficient power for a specified confidence interval. Two examples in sport and exercise science are used to illustrate sample size determination for confidence intervals in the dependent and independent "t" tests. The relevant SAS code and output are provided with detailed annotations. As the use of confidence intervals becomes a more integral part of studies in sport and exercise science, the reporting and analysis of their power should be considered much like that of hypothesis tests.