As matchmaking algorithms move beyond pure skill-based ranking (SBMM) to maximize player retention and spend (EOMM), new legal risks emerge regarding transparency and deceptive practices.
The Black Box Problem
Players are increasingly aware that their multiplayer experience is curated not just for fairness, but for psychological engagement. Our paper dissects the potential liability under the FTC Act for 'dark patterns' if matchmaking is secretly weighted to encourage microtransaction purchases (e.g., matching a player with a paid skin against lower-skill opponents to showcase the item).
We propose a framework for 'Algorithmic Disclosure' that allows studios to maintain trade secrets while satisfying consumer protection requirements.