Updated on May 12, 4:03 p.m. (GMT+8): Added images.

There are two aspects to your competitive rank in Valorant — the rank division you see and your hidden MMR.

Unlike other games, there is no rank decay in Valorant. This means that if you reach Immortal, you will not slip to Ascendant just because you didn’t play for a month.

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That said, your hidden MMR is a different matter altogether. Your MMR will decay if you stop playing for a long time, Jonathan “EvrMoar” Walker, Senior Competitive Designer on Valorant, confirmed on Twitter.

So while the rank you see hasn’t changed, the behind-the-scenes algorithm that decides which opponents you get matched up with is shifting.

No rank decay, but your MMR will decrease

Valorant Competitive Ranks
Screenshot by Koh Wanzi/ONE Esports

MMR is one of the four things that impact the rank you see. In addition to MMR, your rank rating is also affected by your wins and losses, your performance bonus if you play better than expected, and the round differential.

When you’re absent from the game for an extended period, your MMR will be lowered. At the same time, your “variance” will also increase, said EvrMoar.

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“Variance is how confident we are in your MMR,” he explained. “The higher your variance, the further you may match up with players, and gain/lose MMR as well. It’s how we tell the range at which you play. If you have high variance, we are probably less sure about where you belong.”

This is why some players may sometimes encounter opponents who are two rank divisions above or below them. Their MMR spans a wide range, so their opponents’ skill level varies more widely.

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This method of decay gives room for players to earn back the MMR they lost quickly, while ensuring that their teammates don’t suffer if they have actually become a worse player.

“This ensures you don’t get paired with someone who may be a little rusty and not at peak performance,” added EvrMoar.

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However, because this decay is not very punishing, some players may not even notice it.

“It’s pretty small, and we use data and machine learning to learn how much a player’s skill goes down over time,” said EvrMoar. “There are also limits to how much we let the decay set in, and it’s something we are always looking to improve and tweak.”

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