During reach planning, we integrate multiple senses to estimate the location of the hand and the target, which is used to generate a movement. Visual and proprioceptive information are combined to determine the location of the hand. The goal of this study was to investigate whether multi-sensory integration is affected by extraretinal signals, such as head roll. It is believed that a coordinate matching transformation is required before vision and proprioception can be combined because proprioceptive and visual sensory reference frames do not generally align. This transformation utilizes extraretinal signals about current head roll position, i.e., to rotate proprioceptive signals into visual coordinates. Since head roll is an estimated sensory signal with noise, this head roll dependency of the reference frame transformation should introduce additional noise to the transformed signal, reducing its reliability and thus its weight in the multi-sensory integration. To investigate the role of noisy reference frame transformations on multi-sensory weighting, we developed a novel probabilistic (Bayesian) multi-sensory integration model (based on Sober and Sabes, 2003) that included explicit (noisy) reference frame transformations. We then performed a reaching experiment to test the model's predictions. To test for head roll dependent multi-sensory integration, we introduced conflicts between viewed and actual hand position and measured reach errors. Reach analysis revealed that eccentric head roll orientations led to an increase of movement variability, consistent with our model. We further found that the weighting of vision and proprioception depended on head roll, which we interpret as being a result of signal dependant noise. Thus, the brain has online knowledge of the statistics of its internal sensory representations. In summary, we show that sensory reliability is used in a context-dependent way to adjust multi-sensory integration weights for reaching.