# Ranking system

In "Heroes of Crypto AI," players progress through a competitive ranking system that tracks and rewards skill development. You'll be placed into one of five leagues based on your Matchmaking Rating (MMR):

1. Watchdog
2. Warrior
3. Landlord
4. Overlord
5. Emperor

Your MMR changes based on your wins and losses, as well as your opponents' win rates. Winning matches boosts your MMR and can lead to league promotions, while losses result in MMR drops. This system ensures fairness and rewards consistent performance, much like other competitive games that use similar rating methods.

To kick things off, you'll need to play **four calibration matches**. Your performance in these matches, with win rates ranging from 0%...25%...50%...75% to 100%, will determine your starting league placement. This way, you’re matched with players of a similar skill level right from the start, ensuring a balanced and exciting experience.

As you climb through the leagues, victories come with slightly higher HOCAI token rewards. While the difference isn’t huge, it offers a little extra incentive to aim for the top. Rest assured, the reward structure keeps things fair, so everyone has a chance to thrive without being left behind.

Matchmaking focuses on pairing you with players from the same league, creating challenging and exciting battles. However, you may occasionally face opponents from different leagues if your win ratios are closely matched. This keeps every game fresh and ensures you always have a worthy challenge.

In "Heroes of Crypto AI," every battle and every win brings you closer to the top, creating a rewarding and thrilling journey as you compete to become the best.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://heroes-of-crypto.gitbook.io/heroes-of-crypto-ai/the-web3-turn-based-strategy/ranking-system.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
