Objectives: This article introduces a nonlinear dynamical systems model to quantify synchronization among group members with regard to physiological activity or overt behaviors. Method: The driver-empath model accommodates asymmetries in influence among group members, separates autocorrelation effects from synchronization with other group members in time series analysis, accommodates dynamics that could be more complex than simple oscillators, and produces metrics at the individual, dyadic, and group levels of analysis. Results: An illustrative example of a team of seven undergraduates in a group decision-making task is presented with commentary for data preparation and determining lag length of time series data. The supporting literature summarizes connections between the group-level synchronization coefficient and group-level workload, cooperation versus competition dynamics, leadership emergence, and team performance. Conclusions: The driver-empath model has accumulated substantial external validity for answering research questions in group dynamics. Suggested new applications include studying synchrony across different network configurations and possible social fault lines.