This study covers the analysis of occupancy and energy use data collected from a live housing project in Nottingham, UK. Post occupancy evaluation/monitoring in buildings has been established to be of great importance, but implementation levels are generally low. Broader uptake of monitoring systems will increase understanding of buildings in use, allowing improved responsive building controls and future design feedback. The analysis covered assesses: how closely domestic energy uses currently relate to inferred occupancy, whether wasteful energy behaviours can be identified between occupants in similar buildings, how these wastes might be addressed and how effectively occupancy/behaviour can be quantified using a simple and non-intrusive sensor system. Data was gathered from an existing energy platform recording space heating, water use and circuit-level electrical use in 8 high-environmental-performance houses. Occupancy was detected via two motion sensors present in each house, one per major floor. Two houses were equipped with CO2 sensors, allowing for more detailed analysis on a limited subset of the data. Data fidelity issues caused by backup at the data logger necessitated processing of the data prior to further analysis. The results of the study show high variation in sensor response to occupancy despite the similarity between tested buildings. True occupancy levels and behaviours thus cannot be reliably inferred from simple sensor data alone, highlighting the need for a greater depth of information gathering in order to fully sense building context for the purpose of control or detailed analysis. While the relationship between domestic electrical energy use and occupancy rates is confirmed, it is difficult to prove from the data gathered whether all energy used provides utility to the occupant. Heating behaviours across unoccupied houses show approx. 14kWh per day difference, suggesting the significant impact of occupant control and behaviour in the home.