The use of ultrasonograhic measurements of muscle and body fat represent a relatively new data stream that can be used to address questions regarding ungulate condition. We have learned that measurements of body fat and presumably overall body condition among individual animals, even those taken from the same herd at that same time, are highly variable. Relatively little consideration has been given to the sources of variation in body fat and other physiological parameters in wildlife populations. We evaluated the components of variation in late‐winter mule deer (Odocoileus hemionus) body fat estimates: sampling variation (i.e., variation induced by the particular set of individuals that were sampled) and process variation (i.e., variation stemming from biological processes) with a long-term data set (2002–2015) from Colorado, USA. We collected our data from across Colorado as part of historical research, ongoing research, and periodic population monitoring programs. Mean percent ingesta‐free body fat (%IFBF) for sampled mule deer was 7.20±1.20% (SD). Covariates related to individual deer explained approximately 4% of the total variation in %IFBF and annual effects explained an additional 13% of the variation. Substantial residual variation in %IFBF (83%) remained unexplained. The source of the 83% of unexplained variation is partially linked to fine-scale spatial dynamics but also additional individual metrics we were unable to capture, primarily the presence or absence of dependent young. We speculate that the primary factors influencing late-winter mule deer body fat and overall condition are individual in nature. These results present a cautionary check on herd-level inference that can be made from individual late-winter body fat estimates and we postulate that for mule deer, alternative and additional body condition metrics may offer added utility in management scenarios. However, an important next step to better understand wildlife population health is to evaluate the sources and magnitude of variation within other body condition metrics, with the goal of further refining data that can better allow biologists to incorporate herd health into population management recommendations.