Understanding particle motion in snow avalanches is essential for unravelling the driving processes behind transport phenomena and mobility. Our approach to investigating avalanche dynamics at the particle level combines data from a novel inflow sensor system, the AvaNodes, with radar measurements and simulation results from the thickness integrated flow module of AvaFrame, the open avalanche framework. The radar measurements offer a comprehensive view of the avalanche, serving as a reference for the AvaNodes’ trajectories within it. This synthesis provides a holistic overview of the motion of avalanche particles and the front. The utilized com1DFA module in AvaFrame, equipped with a numerical particle grid method, enables a direct implementation of numerical particle tracking functionalities, facilitating a comparison between measurements and simulations. This unique combination prompts questions about the comparability of simulations and measurements on a particle level, yielding new insights into the thickness integrated model’s ability to replicate real-scale snow avalanche particle behaviour assuming a modified Voellmy friction relation. Our work also highlights current limitations of comparing radar measurements and synthetic particle sensor systems with numerical simulation particles. Minimizing the differences between measured and simulated particle velocities and front positions allows to identify optimal parameter settings for an observed avalanche event at the Nordkette test site. Using the best-fit parameter values yields deviations below 5−10% for the maximum velocities and the resulting travel lengths. Beyond the best-fit simulations, the applied optimization method shows a wide range of suitable parameter sets causing equifinality within the investigated parameter space. Additionally, the results show that there is a trade-off between the accuracy of an optimization on single observables or the simultaneous optimization of particle and front behaviour. The particle tracking functionalities further allow to investigate the spatio-temporal flow evolution along flow trajectories in a new way. By displaying maximum velocities in dependence of their initial position we reveal that in contrast to the experimental observation, initial position is the determining factor for the maximum velocity along the particles trajectory in the simulations. In conclusion it is possible to identify suitable parameter sets to reproduce the particle motion with high accuracy. However, this analysis also reveals the limitation of the underlying flow model to replicate varying particle properties or corresponding flow regime changes. Analysing AvaNode sensor data also indicates future potential for investigating the influence of snow and particle properties, such as size, shape, or density, on the avalanche flow.