The statistical distribution of waves in short-crested seas is critical for the design of coastal structures, not least because large, breaking waves are known to induce significant wave loads. Despite recent advancements, discrepancies remain in the statistical description of crest heights in finite waters. These are particularly highlighted in cases where strong nonlinear effects/wave breaking are prevalent. The present work utilises a large experimental dataset of random simulations of short-crested seas to provide further insights into those mechanisms. Specifically, a novel method to identify waves that undergo nonlinear amplifications and wave breaking is developed. This is used to calculate the associated energy gain/dissipation per wave. A modelling suite is proposed to describe the probability of wave breaking and associated dissipation, which is then converted into a mixture model to recover crest height statistics. The success of the proposed approach is demonstrated through comparisons between model predictions and measurements.
