We present an analysis of velocity-based saccade detection in data recorded from a new mobile eye-tracking system (SMI-ETG 2W) with sampling rate of 120 Hz. We applied an algorithm developed for the detection of microsaccades from noisy data. Parameters of the algorithm were selected based on statistical analyses using surrogate data and velocity-amplitude correlations of the main sequence for saccades. Results on saccade amplitudes and fixation durations are compared to published benchmark dataset obtained from a desktop eye-tracking system with a sampling rate of 1000 Hz. We conclude that velocity-based saccade detection can be applied to the new system reliably.