Points are dimensionless geometric elements often employed by geographic information systems to model a range of real-world objects such as people and vehicles. Many analytical tools have been developed for finding and validating certain patterns of static points such as clustering. In this paper, we present our preliminary efforts to develop statistical methods for analyzing patterns of moving points whose locations are tracked at equal intervals of time. Focus is placed on simple descriptive statistics—rather than more sophisticated inferential statistics—useful for detecting a tendency of two or more points to move in some coordinated fashion. A major implication of this paper is that statistical analysis complements spatial data query and modeling with respect to dynamics of sets of point-like objects in a way that potentially interrelated subsets are screened.