Users bet on the prediction market and receive winnings from other users.

SX is a non-custodial, community-owned sports betting and political prediction market. It is built on SX Network, an EVM-compatible Polygon Edge application blockchain. SX was founded by Andrew Young, Julian Wilson, Jake Hannah, and launched in 2019.

SX tokenholders own and govern the protocol. They currently take all of the total betting fees paid by users (revenue). SX's investors include CMCC Global, Nascent, Sybil Capital, etc.

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# SX Average fees per user (AFPU) Methodology

## 1. Overview

The SX Average Fees Per User (AFPU) metric measures the average daily revenue generated per active user on the SX prediction market platform. This metric is calculated by dividing daily fee revenue by the number of daily active users, providing insight into user monetization and platform efficiency. The calculation uses data directly from SX's API rather than parsing blockchain transactions, reflecting the platform's centralized data collection approach.

## 2. Data sources

The calculation relies on the following data sources:
- **SX API metrics**: Raw daily metrics from SX's prediction market platform API, containing both revenue and user activity data
- **Token denomination metadata**: Information about the token types used for revenue tracking on the SX platform  
- **End-of-day price feeds**: Token price data used for USD conversion of revenue amounts
- **Chain availability data**: Data quality filters to ensure complete and accurate metric calculation

## 3. Step-by-step calculation

### Component A: Fee revenue extraction
- **Purpose**: Extract daily fee revenue from SX's prediction market platform
- **Logic**: Revenue data is sourced from SX's API scraper, capturing daily fee amounts generated from prediction market activities. The data is filtered to include only records from December 7, 2020 onwards. Each revenue record is categorized with business metadata including `Prediction market` as the business line, `betting` as the business segment, and `prediction_markets` as the market sector. The revenue `amount` field is cast to a high-precision numeric format, and the token `denomination` is normalized to lowercase for consistency.
- **Key fields**: Daily `timestamp`, revenue `amount`, token `denomination`, and business categorization fields

### Component B: Daily active user calculation  
- **Purpose**: Calculate daily active user counts with dimensional breakdowns
- **Logic**: User activity data is extracted from the same SX API source, focusing on users classified as `Transaction sender` type. The raw user count data is transformed into multiple dimensional views: project-level aggregation (labeled as `project_dbt_tag`), chain-level breakdown using the `sx` chain identifier, and user-type classification. Each dimensional view maintains the daily `user_dau` count while setting appropriate dimension identifiers. Data is limited to before January 18, 2024 due to API adapter limitations.
- **Key fields**: Daily `timestamp`, `user_dau` count, `chain` identifier, `user_type` classification, and dimensional categorization

### Final aggregation
- **Combining components**: The fees and user DAU components are combined using the `calculate_arpu` macro, which performs a division operation to calculate average revenue per user. The macro matches records by date and divides the daily fee amounts by the corresponding daily active user counts.
- **Currency conversion**: Revenue amounts are converted to USD using end-of-day price feeds, with the conversion applied during the finalization process. Token denominations are used to identify the appropriate exchange rates.
- **Time aggregation**: Data is aggregated on a daily basis with a `day` timestamp grain. Missing days are filled with zero values to maintain time series continuity using a `fill_zeros` strategy.
- **Final calculation**: The final AFPU value represents the daily fee revenue divided by the daily active user count, expressed in USD. Chain availability filters ensure only complete and valid data points are included in the final metric.

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

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Average fees per user (AFPU)

Average fees per user (AFPU)

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