Strong empathic bonding between members of a team can elevate team performance tremendously but it is not clear how such bonding within human-machine teams may impact upon mission success. Prior work using self-reporting surveys and end-of-task metrics do not capture how such bonding may evolve over time and impact upon task fulfillment. Furthermore, sensor-based measures do not scale easily to facilitate the need to collect substantial data for measuring potentially subtle effects. We introduce TEAMMATE, a system designed to provide insights into the emotional dynamics humans may form for machine teammates that could critically impact upon the design of human machine teams.