Many applications for robots require them to work alongside people as capable members of human-robot teams and to collaborate in order to perform tasks and achieve common goals. These tasks can induce strain on the human due to time constraints. Additionally, humans can become highly stressed due to fatigue, resulting in decreased efficiency. The contribution of this paper is in the introduction of a human fatigue model and the application of this model to a mixed team coordination framework in order to predict team performance given the constraints of human fatigue. The human fatigue model - namely a FAtigue Prediction (FAP) model - is used to conduct numerical simulations that predict mixed team performances. Specifically, extensive simulations are performed to determine how human fatigue influences the choice of the number of agents for a given number of tasks. The novel mixed team coordination framework is a Stochastic Clustering Auction (SCA), which is based on a modification of the Swendsen-Wang method, called SW2SCA. It enables complex and efficient movement between clusters by connecting tasks that appear to be synergistic and then stochastically reassigning these connected tasks. In SW2SCA, the auctioneer makes stochastic movements with homogeneous or heterogeneous agents. The final discussion outlines a systematic procedure to predict the performance of human-robot systems with the FAP model in SCA.