The effect of using time-averaged wave statistics in a simple empirical model for shoreline change is investigated. The model was first calibrated with a six-year time series of hourly wave conditions and weekly shoreline position at the Gold Coast, Australia. The model was then recalibrated with the hourly waves averaged over intervals up to 1 year. With wave averaging up to 2 days, model performance was approximately constant (squared correlation r 2 ~0.61-0.62), with only small changes in the values of empirical model parameters (e.g. the beach response coefficient c varied by less than 4%). With between 2 and 40 day averaging, individual storms are not resolved; model skill decreased only modestly (r 2 ~0.55), but c varied erratically by up to 40% of the original value. That is, optimal model coefficients depend on wave averaging, an undesirable result. With increased averaging (N40 days) seasonal variability in the wave field is not resolved well and model skill declined markedly. Thus, temporal averaging of wave conditions increases numerical efficiency, but over-averaging degrades model performance and distorts best-fit values of model free parameters.