Hmmm, I’m also curious about their methods as there really isn’t a clean way to do this. They seem unaffiliated with anyone and isn’t paid for my anyone (seems more like a person trying to get another notch on their CV) but unfortunately the research is behind a paywall.

I know a lot of statistical models, and the only decent one I can think of are propensity score models that, put simply, try to match a game with denuvo with it’s nearest neighbor in a database, paired based on a variety of attributes. For example, Game A has cracked denuvo, Game B wasn’t cracked, matched on review score, price, and any other forward facing and easily quantifiable metric.

Those models aren’t without their flaws, though, and the attributes you pair with could be any variety of things and make it really easy to say whatever the hell you want with the data. There’s always something you’re missing, which is especially true if you’re looking at denuvo vs none.

Also 99% chance this guy probably isn’t even that rigorous in their method. CV fluffing, you usually don’t have time for that.

Edit: also the journal is in isn’t well regarded, although there aren’t many top tier journals that are that specific.