The Work Sampling (WS) technique, used worldwide to understand how workers spend their time, represents a time-consuming and costly activity. Therefore, several researchers work on different approaches to automate the data collection using sensor-based and vision-based technologies. The challenge of all the sensor-based approaches is that they do not provide the share of time in different work categories. The lack of knowledge on a possible correlation between Direct Work and, e.g., presence, location, or worker movement represents a gap in the current body of knowledge. Thus, this research aims to understand the correlation between Direct Work as the independent predictor variable; and Movement as the dependent response variable. The authors used the data gathered through the application of WS in five case studies on building renovation projects in Denmark. To explain this correlation. The authors selected a combination of four quantitative techniques: (1) curve estimation; (2) linear regression; (3) ANOVA analysis; and (4) t-test. The correlation of the result is discussed considering three assumptions: (1) the structure of the day; (2) global vs. local; and (3) Movement vs. Transporting and Walking. The result shows a significant correlation between Direct Work and Movement with an average R2 of 0.328. This is considered acceptable predictability taking the socio-technical system aspect of a construction site into account.