# Price Prediction **Price Prediction** is a game in which players make guesses about the future value of a digital asset. A mathematical model is used to determine the accuracy of a prediction, which influences the size of the reward. In general, the closer the forecast is to the actual outcome, the greater the benefits. Price Prediction happens on a weekly basis. At the beginning of every week, the initial price of an asset is registered. Until the end of Thursday, the users can make guesses of a specific number or a percentage change in this price. At the end of the week, the system will register the closing price in order to compute the scoring and the final rewards. A detailed timeline will be given below. In this game, participants will bet in USDC, with the **minimum amount of 5 USDC** and **no maximum**. Players can make multiple bets with different predictions. Each bet will be recorded as one separate entry. Price Prediction uses real-time data from Chainlink Oracle. ## Timeline Every week, there are 04 important milestones: 1. **Betting begins** (00:01 UTC on Monday): The system registers the opening price. Participants may begin submitting their wagers and forecasts. 2. **Betting ends** (23:59 UTC on Thursday): The system stops accepting predictions. Participants await the outcome. 3. **Score calculation** (23:30 UTC on Sunday): The system registers the closing price and computes the scoring and the final reward. 4. **Reward**: The reward will be accessible after the score computation, often concurrently with the start of a new betting round. Within 30 days, all participants should verify and claim their awards. --- # 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://docs.lamas.co/1.0/games/price-prediction.md?ask= ``` 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.