The growth of the wave energy sector is contingent on the ability for stakeholders, particularly electrical utilities, to rapidly predict the production from wave energy converters (WECs). Current methodologies require extensive knowledge of metocean conditions, a priori determination of WEC architecture, and highly-specific physical and numerical tools. Additionally, the lack of a consistent robust method to up-sample the hourly temporal resolution of traditional wave buoys and/or numerical wave propagation models limits the implementation of wave energy technologies in Integrated Resource Planning (IRP) by utilities. These two knowledge gaps create a significant barrier for broad adoption of wave energy. This novel research provides an overview of a waves-to-wire method to quantify WEC performance, across a wide variety of technology architectures, to develop an empirically driven and easily applicable generic model of WEC performance. The generic WEC performance model ultimately shows an average co-efficient of determination (R2) of 0.93 and less than 9% variation in annual energy production when compared against five significantly different WEC architectures. The temporal up-sampling methodology is shown to generate wave resource and WEC performance data at a resolution suitable for an IRP process, creates a realistic representation of wave condition variability on short-time frames, and does not artificially perturb the available energy on an annual basis.