Fit plays an important role in the function and wearability of functional clothing. Smart gloves, or functional gloves with integrated technologies (such as sensors or actuators), rely on fit to create an interaction with the body surface that is needed to afford functionality. For example, glove fit must produce contact between a haptic actuator and the body to enable a haptic sensation. Failure of coupling between body and glove can also cause sensor malfunction, reduced mobility, and user discomfort. High-resolution fit analysis is needed to assess the geometric relationship between gloves and the complicated anatomical structure of the hand. This study developed a high-resolution fit assessment method that provides quantitative information on smart glove fit. The study defined key fit measures, proximity and alignment, to measure smart glove fit, focusing on quantifying the relationship between integrated technologies and the body surface. A quantitative pipeline was developed that included three stages: hand model development, 3D scan analysis, and result translation. The methods provided high-resolution (< 1 mm accuracy) and objective data that can be used to inform smart glove fit improvements and, consequently, improvements to on-body functionality. The results of the fit analysis demonstrate that these methods can effectively quantify glove fit. Adding proximity and alignment measurements to the analysis allows the relationship between the body and integrated technologies to be quantified, providing information to improve smart glove fit. Virtual fitting was explored for expanding the pipeline to reduce prototyping time and costs by simulating gloves virtually.