Numerical wear predictions are gaining increasing interest in many engineering applications, as they allow to simulate complex operative conditions not easily replicable in the laboratory. As far as hip prostheses are concerned, most of the wear models in the literature are based on the simulation of gait (recommended also in experimental wear tests), since gait is considered the most frequent and important motor task to recover after arthroplasty. However, since joint prostheses have been increasingly implanted in younger people, high loads and potentially severe conditions, e.g. due to sporting activities, should also be considered for a more reliable wear assessment of these implants. In this study, we propose a profitable combination of musculoskeletal and analytical wear modelling for the prediction of wear caused by common daily activities in metal-on-plastic hip arthroplasties. Several motion analysis data available in the literature (walking, fast walking, lunge, squat, stair negotiation) were selected and the effects of such motor tasks on prosthesis wear were investigated, both separately and in combination. Additionally, for comparative purposes, wear prediction for simplified gait conditions prescribed by the ISO 14242 standard, were also considered. Results suggest that this latter case produces lower wear depth and volume with respect to a relatively demanding combination of the selected daily activities. The preliminary results of the present study represent a first step towards the auspicious goal of validating the proposed procedure for in silico trials of hip arthroplasties.