A professional-grade tool for calculating trading expectancy, Polymarket edges, and arbitrage boundaries to ensure every decision has a positive expected value.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ev-calculator
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ev-calculator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is EV Calculator?
The EV Calculator is a specialized financial tool designed for the Openclaw Skills ecosystem to help traders and developers quantify the potential return of any decision based on probability and risk. By calculating the Expected Value (EV), users can move beyond intuition and make data-driven choices in high-stakes environments like crypto trading, prediction markets, and technical arbitrage.
This skill supports multiple calculation models, including basic EV for standard trades, market-specific probability analysis for platforms like Polymarket, and edge detection for complex arbitrage scenarios. Integrating this within Openclaw Skills allows for automated risk assessment directly within your development or trading workflow.
EV Calculator Use Cases
- Evaluating trade setups to confirm they have a positive expected value (EV > 0) before execution.
- Identifying price discrepancies and 'edges' on prediction markets like Polymarket by comparing personal probability assessments against market pricing.
- Assessing arbitrage opportunities such as lottery roll-downs or market-neutral sports betting strategies.
- Performing odds conversion and win-loss ratio analysis for portfolio risk management.
How EV Calculator Works
- The user provides input parameters such as win probability (p), potential profit (win), and potential loss (loss).
- For market-based analysis, the skill compares the user's judged probability against the current market price to calculate the 'edge'.
- The skill applies the core mathematical formula: $$EV = p \times win - (1 - p) \times loss$$.
- A verdict is returned classifying the opportunity as positive, neutral, or negative expectancy.
- Results can be output in human-readable format or as parsable JSON for further automation within Openclaw Skills.
EV Calculator Setup
To use this skill within your Openclaw Skills environment, ensure you have a compatible wallet configured on the Base chain.
# Standard usage via CLI
python ev_calculator.py --p 0.55 --win 100 --loss 80
# For Polymarket edge analysis
python ev_calculator.py --market 0.40 --your 0.60
# Output JSON for automation
python ev_calculator.py --p 0.6 --win 50 --loss 50 --json
EV Calculator Data Schema & Taxonomy
The skill processes and returns data structured for both financial reporting and automated triggers.
| Field | Description | Type |
|---|---|---|
type |
The calculation model used (basic or polymarket) | String |
ev |
The calculated net expected value in currency units | Float |
edge |
The percentage difference between personal and market probability | Percentage |
verdict |
A status indicator (Positive, Negative, or Neutral) | String |
ev_per_dollar |
Expected return for every 1 unit of currency staked | Float |
EV Calculator Advanced Features
- Polymarket Integration: Specialized logic for calculating edge based on market price vs. true probability.
- Arbitrage Detection: Boundary checking for Winfall roll-down and other specific arbitrage scenarios.
- JSON Interoperability: Designed to pass data to other Openclaw Skills like
kelly-formula-cryptofor automated position sizing. - X402 Payment Protocol: Native support for pay-per-use execution on the Base network using USDC.
SKILL.md
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