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Motion of active particles, such as catalytic micro- and nano-motors, is usually characterized via either dynamic light scattering or optical microscopy. In both cases, speed of particles is obtained from the calculus of the mean square displacement (MSD) and typically, the theoretical formula of the MSD is derived from the motion equations of an active Brownian particle. One of the most commonly reported parameters is the speed of the particle, usually attributed to its propulsion, and is widely used to compare the motion efficiency of catalytic motors. However, it is common to find different methods to compute this parameter, which are not equivalent approximations and do not possess the same physical meaning. Here, we review the standard methods of speed analysis and focus on the errors that arise when analyzing the MSD of self-propelled particles. We analyze the errors from the computation of the instantaneous speed, as well as the propulsive speed and diffusion coefficient through fittings to parabolic equations, and we propose a revised formula for the motion analysis of catalytic particles moving with constant speed that can improve the accuracy and the amount of information obtained from the MSD. Moreover, we emphasize the importance of spotting the presence of different motion dynamics, such as particles with active angular speed or that move under the presence of drift, and how the breaking of ergodicity can completely change the analysis by considering particles with an exponentially decaying speed. In all cases, real data from enzymatically propelled micro-motors and simulations are used to back up the theories. Finally, we propose several analytical approaches and analyze limiting cases that will help to deal with these scenarios while still obtaining accurate results.