Abstract
Recent developments in criminology that allow investigators to statistically analyse patterns in criminal cases can create an impression of scientific profiling. However, many criminal cases, for example child abduction–homicides (CAH), seldom follow clear statistical patterns. This study critically examined the limitations of two contemporary temporal analysis techniques, crime script analysis (CSA) and behaviour sequence analysis (BSA), using 48 closed CAH cases sourced via open-source intelligence (OSINT). Although CSA offered structured frameworks and BSA provided statistical mapping, both undermined the chaotic, interrupted, and non-linear nature of real-world crimes. A comparative analysis of the crime data revealed minimal variation in offender profiles but significant differences in crime sequences. The study also highlighted how cognitive biases and statistical representations—e.g. standardised residuals (SRs) versus prevalence scores (PrevScores)—can distort investigative outcomes. Ultimately, the article advocates for flexible, context-sensitive approaches that integrate analytical tools with experiential insight, treating each case as unique rather than extrapolating from generalised data.