# For Stakers

**In prediction markets, participants who enter the prediction market and bet on a given outcome of future events are commonly referred to as "bettors" or "stakers".** Unlike traditional betting, where participants wager on the outcome of an event, prediction market participants trade tokens representing the likelihood of various outcomes. Some key characteristics of Bettors/Stakers:

1. Bettors are individuals or entities who engage in prediction markets with the goal of making a profit based on their predictions of future events. They take positions on different outcomes depending on their assessment of the likelihood of those outcomes.
2. Bettors contribute their knowledge, insights and information to the market through their activity. The outcomes in the market are influenced by the collective wisdom and information of all participants, making prediction markets effective tools for aggregating diverse perspectives.
3. Some bettors engage in arbitrage, exploiting price discrepancies between different contracts or markets. Arbitrageurs aim to profit from inefficiencies in pricing by buying low and selling high or vice versa.
4. Bettors can have various objectives, including financial speculation, hedging against specific risks, expressing opinions on future events, or simply participating for entertainment. Prediction markets attract a mix of participants with different motivations.

<div><figure><img src="/files/yXCZgoOA0EsLEbxDSst9" alt=""><figcaption></figcaption></figure> <figure><img src="/files/IhDVFSLxSNMfK6PxGIzO" alt=""><figcaption></figcaption></figure></div>


---

# 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://whitepaper.earn.network/en/prediction-markets/for-stakers.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.