Engagement Optimized Matchmaking
It's actually the opposite of cool stuff unfortunately.
Excerpt:
"In this paper, we propose an Engagement Optimized Matchmaking (EOMM) framework that maximizes overall player engagement. We prove that equal-skill based matchmaking is a special case of EOMM on a highly simplified assumption that rarely holds in reality. Our simulation on real data from a popular game made by Electronic Arts,Inc. (EA) supports our theoretical results, showing significant improvement in enhancing player engagement compared to existing matchmaking methods."
Translation:
In free to play games, we need to find a way to keep players coming back because it seems like sbmm doesn't do that. Instead we match people who likely will play games together and the results of those games will keep them coming back.
You can't really describe it as "winners/losers" queue because that's not the purpose. Winners and Losers queue would be if the desired outcome was to get you wins. That doesn't mean anything to a publisher of the game. They've given you a free game and they need you to stick around and play it.
Instead, using your match history, frequency of play and other data points, how likely will you continue to play regardless of the outcome of the game.
Discord