Temporal mismatches between heat provided by a drain water heat recovery system, and heat consumption are, although often disregarded in literature, a crucial factor in assessing the feasibility of the former. Generally, the only available information for residences is the average monthly consumption. The probabilistic method described in this paper uses observations from 113 residences to predict daily and monthly consumption profiles, using monthly consumption as a starting point. These profiles were then used to study the operation of a drain water heat recovery system, but can also be used to assess the operation of other heating methods where the supply is not controlled, such as solar thermal. The operation of the drain water heat recovery systems was predicted based on a monitoring campaign at 3 residences, measuring wastewater temperature and flow at 5-minute intervals, for over a 1-year period. The performance of this system was assessed using the performance data of 26 commercially available heat pumps, with rated power below 7 kW. The method was applied to a theoretical average Irish residence, obtained through a Monte Carlo analysis on just under 700 000 Irish residences. The method highlighted the potential for a reduction in heating related greenhouse gas emissions by 7.6% to 22%. However, this increased heating costs by 120% to 130%. At current traditional heating prices, the DWHR system for a single residence is not financially competitive with traditional systems, due to its significant capital investment. Further research should examine combining waste water streams from different residences to provide a larger flow, and potentially a high recoverable energy volume, thus improving financial viability. Policy makers should also consider incentivizing DWHR to improve its financial competitiveness and help achieve the above GHG emissions savings. (C) 2018 Elsevier B.V. All rights reserved.