Systematic sampling and temporal aggregation are the practices of sampling a time series at regular intervals and of summing or averaging time series observations over a time interval, respectively. Both practices are a source of statistical error and faulty inference. The problems that systematic sampling and temporal aggregation create for the construction of strongly specified and weakly specified models are discussed. The seriousness of these problems then is illustrated with respect to the debate about superpower rivalry. The debate is shown to derive, in part, from the fact that some researchers employ highly temporally aggregated measures of U.S. and Soviet foreign policy behavior. The larger methodological lessons are that we need to devote more time to determining the natural time unit of our theories and to conducting robustness checks across levels of temporal aggregation.