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Several studies have shown that children's performance with input devices in pointing tasks increases with age. However, none of these studies analyzes the sub-movements children make during pointing tasks. This paper analyzes mouse event data from a previous study to compare, at a sub-movement level, the way preschool children and young adults conduct pointing tasks. Results of the analysis show that the children made significantly more sub-movements than the adults. This was caused by children's inaccuracy in the length and direction of their sub-movements. The results also show that most sub-movements were started near the target, and that there was a balance between overshoots and undershoots in these sub-movements. Based on sub-movement data, this paper proposes an algorithm to identify when participants have difficulty pointing. The algorithm provides several advantages such as triggering a precision mode only when users experience difficulty, not requiring information on the location of visual targets, and not requiring information on the direction of mouse motion.