> For the complete documentation index, see [llms.txt](https://all-your-base.gitbook.io/all-your-base/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://all-your-base.gitbook.io/all-your-base/price-prediction-games/daily-prediction.md).

# Daily Prediction

The Daily game is similar to the 15-minute game, but the rounds last for 24 hours.

{% hint style="success" %}
**More details coming soon! Expected launch in January, 2024.**
{% endhint %}

## Overview

Players select a token and cast their vote with $AYB on whether the USD price will rise (up) or fall (down) in 24 hours **and** they must enter a price prediction. Players that correctly vote the direction (up or down) win $AYB, and players that vote incorrectly win nothing. The amount of $AYB a player receives depends on how their prediction ranks compared to the other players in that round.

### Winning Strategy

The amount a player wins depends on how accurate their predictions are compared to other players for the selected token. 

* **1st place** receives a progressive grand prize that can reach **100x or more!**
* The top ranked players will earn 10x more than the bottom ranked players.

The more knowledgeable players will have an advantage, so we encourage all players to do their research to improve their prediction skills.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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://all-your-base.gitbook.io/all-your-base/price-prediction-games/daily-prediction.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.