For many species, population size data is difficult to obtain or even unavailable. Therefore, estimations or indirect abundance measures of populations are crucial for ungulate management. Hunting has an important role in wildlife management, and is a partnership between state, landowners, and hunting communities. In ungulate management harvest statistics, as well as ungulate-vehicle collisions (UVCs) and observations, are often used as proxies for population densities and provide detailed information on a spatial and temporal scale. A Bayesian approach was used to model hunters’ response to population densities of fallow deer (Dama dama), roe deer (Capreolus capreolus), and wild boar (Sus scrofa). The results indicate that the variability in number of individuals observed and the non-linearity of both hunters’ harvest and UVCs response varies between roe deer, fallow deer, and wild boar. Both hunters’ harvest and UVC display a sub-linear response to population densities to all three species. Additionally, roe deer show a low variability in the number of individuals observed compared to the other two species. Predictions of population densities by using proxies like harvest statistics and UVC statistics need to be species-specific to be reliable, and by considering a potential sub-linearity and temporal trends for the species of interest more confident and realistic estimates can be developed.