Sketch recognition attempts to interpret the hand-sketched markings made by users on an electronic medium. Through recognition, sketches and diagrams can be interpreted and sent to simulators or other meaningful analyzers. Primitives are the basic building block shapes used by high-level visual grammars to describe the symbols of a given sketch domain. However, one limitation of these primitive recognizers is that they often only support basic shapes drawn with a single stroke. Furthermore, recognizers that do support multistroke primitives place additional constraints on users, such as temporal timeouts or modal button presses to signal shape completion. The goal of this research is twofold. First, we wanted to determine the drawing habits of most users. Our studies found multistroke primitives to be more prevalent than multiple primitives drawn in a single stroke. Additionally, our studies confirmed that threading is less frequent when there are more sides to a figure. Next, we developed an algorithm that is capable of recognizing multistroke primitives without requiring special drawing constraints. The algorithm uses a graph-building and search technique that takes advantage of Tarjan's linear search algorithm, along with principles to determine the goodness of a fit. Our novel, constraint-free recognizer achieves accuracy rates of 96% on freely-drawn primitives.