The 100-m sprint is one of the track events, and the pace of the runner can be measured using a variety of tools, such as a hand stopwatch, timing gate, laser device, radar device, photocell timing, etc. The data measured is the mean travel time. Nonetheless, monitoring an individual sprinter's instantaneous speed tracking is essential for assisting staff trainers in developing an appropriate training schedule for the individual sprinter. The purpose of this study was to construct a computer vision-based system for assessing the sprinting speed of the 100-m subtasks and also to investigate the concurrent validity of video analysis software among athletes. Five athletes participated in the research to determine its validity. Over the course of two trials, the sprinting pace of each participant's subtasks (a 100-m split to 10 m for each subtask) was measured. The application of the computer vision-based system to video analysis software was validated using the Pearson correlation coefficient. The agreement between the two measurement systems was quantified using Bland-Altman plots. The results revealed a significant relationship between the two systems and all 100-m subtask sprinting speeds (r = 0.961-1.000, p 0.0001). The Bland-Altman analyses indicated that the mean differences in 100-m subtask speeds were consistently close to zero, falling within the 95 % limits of agreement. The scatter plot distribution showed symmetry. The computer vision-based system proved to be a valid tool, suggesting its potential value in measuring and monitoring the 100-m subtask sprinting speed of athletes.