- Giving roughly a half hour of time before and after a call, the following schedule analysis was created via data from the Google Doc. Any dual-color blocks indicate an overlap of time, or an exact same time occurrence from week to week.
- The suspect appears to have normal sleep hours, apart from a Litchfield Towers call around 2AM.
- The suspect also has not made threats on weekends.
- This is either because they have other activities and interests, or because they know few people are on campus and in classes on weekends (very likely the latter).
- Activity between 12PM and 1PM is rare. Again, the suspect could be taking a lunch break, just like anyone else.
- Wednesday, to this date, has the highest number of threats. Apart from weekends, Tuesday has the least.
- 10:30 AM and 5:30PM (roughly) are key time points. This cycle repeats itself almost daily. It's likely the suspect has normal evening activities or interests and is making the threats before these activities.
- At this point, it is highly unlikely the suspect will be out of his hidden location at 10:30 AM or 5:30 PM.
- If the suspect is a student, it is unlikely they have class around 10:30AM, but it is very likely they have an earlier class or an afternoon class before 5PM.
- If the suspect is not a student, they are likely unemployed or only working part time. Consider: tt seems highly unlikely they would be able to leave work around 10AM, and get home in time to set up the requirements to cloak their call, then go back to work. Early afternoon threats are relatively rare, meaning the person is likely taking a shift at work (again, assuming they are NOT a student).
- Key analytic assumption: The suspect is not using a scheduling program that is sending out pre-scheduled threat e-mails at various times. This would mean the suspect would not even need to be at home or near a computer for the threats to be sent and received. While this may seem like a "we're screwed" scenario, I see it as a pretty decent outcome, since at some point, the actual professionals in the FBI and JTTF will find him. Again, in my best estimation, I highly doubt this guy makes it another two weeks without getting caught.
Everyone is welcome to analyze the data. I will publish additional key findings that I find are best supported by the evidence so far. Again: Weekends off. 10:30AM/5:30PM. What do these key data points signify?