Analyzing Rankdle With An MDA Lens

Rankdle has a simple premise: pick a game, you will be shown three submissions from players playing that game, guess the competitive ranking of each player based on what you saw in each submission.

The core mechanics of the game are that you are to watch a video without looking up the user, you select one of the set ranks (or range of ranks for some games, e.g. elo in chess), and you check your guess against the ground truth rank of the player. Close guesses (one rank away) net you one star, perfect guesses net you two, and otherwise off guesses net you zero.

Interesting dynamics come into the picture as you can replay the videos, analyze them freely, compare your own or outside experiences to what is happening, or even try to cooperate with others to average out experiences and opinions on what the believed rank of each submission is. Much of the aesthetic of the game is dependent on factors which aren’t rooted in the core mechanics of the game itself–but instead on the dynamics and relationships of each player to the game.

The end aesthetic is that of challenge because there are lots of plausible inconsistencies which may arise. Playing with friends builds fellowship but also competitiveness in gauging whose judgement is more accurate. This can vary drastically across categories which can make it more engaging as you may find yourself drawing from various expertise which is best suited for each compartmented challenge.

Overall, it’s a fun past time where much of the enjoyment is rooted in biases that are formed outside of the game (Rankdle) itself, which is an interesting and refreshing dynamic to immerse yourself in.

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