The sea-ice modelling community progresses towards Pan-Arctic simulations that explicitly resolve leads in the simulated ice cover. This creates new challenges of proper model evaluation. We introduce a feature-based evaluation of simulated deformation fields and compare the results to a scaling analysis of sea ice deformation. Leads and pressure ridges - combined to Linear Kinematic Features (LKF) - are detected and tracked by an algorithm that uses deformation and drift data. LKFs in two Pan-Arctic sea-ice simulations with a horizontal grid spacing of 2km are compared with an LKF data-set derived from the RADARSAT Geophysical Processor System (RGPS). One simulation uses a 5-class Ice Thickness Distribution (ITD). The simulated sea-ice deformation is described by multi-fractal spatial and temporal scaling as observed from RGPS for both simulations. Interannual and seasonal variations of the number of LKFs, LKF densities and LKF orientations in the ITD simulation are found to be in line with RGPS observations. The heavy-tailed distribution of LKF lengths and the scale invariance of LKF curvature is reproduced by the model and points towards the self-similar nature of sea-ice deformation fields. The model overestimates the intersection angle of LKFs which is attributed to the use of the elliptical yield curve. In addition, the lifetime and growth rates of LKFs are found to be described by an exponential tail. In conclusion, our analysis of LKF statistics is a useful tool for a comprehensive description of deformation features and as such complements the previously used scaling analysis. The ITD simulation is shown to reproduce LKFs sufficiently well to be used for studying the effect of directly resolved leads in climate simulation.