Rainfall-runoff models are commonly evaluated against statistical evaluation metrics. However, these metrics do not provide much insight into what is hydrologically wrong if a model fails to simulate observed streamflow well and they are also not applicable for ungauged catchments. Here, we propose a signature-based hydrologic efficiency (SHE) metric consisting of hydrologic signatures that can be regionalized for model evaluation in ungauged catchments. We test our new efficiency metric across 633 catchments from Great Britain. Strong correlations with Spearman rank and Pearson correlation values around 0.8 are found between our proposed metric and commonly used statistical evaluation metrics (NSE, KGE, NP…) demonstrating that the proposed SHE metric is related to existing metrics as much as these metrics are related to each other. For ungauged catchments, we regionalise the three signatures included in SHE and find that 78% of catchments have an absolute difference of SHE values between gauged and ungauged cases of less than 0.2. This difference increases where the regionalized bias and variance signature values are different to the observed ones. It means that SHE metric is applicable for model evaluation in ungauged catchments if its signatures can be regionalized well.