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Edgeful

Edgeful is a trading analytics platform that analyzes 7+ years of exchange data to calculate historical probabilities across market conditions. traders use it to identify high-probability setups, determine directional bias, and automate strategies across futures, stocks, ETFs, forex, and crypto. the platform includes 150+ customizable reports, a real-time screener, AI-powered cross-report analysis, 7 automated algos, and 50+ TradingView indicators.

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-26T02:32:37.988Z. Cached copy · Source on edgeful.com

# Edgeful

> Edgeful is a trading analytics platform that analyzes 7+ years of exchange data to calculate historical probabilities across market conditions. traders use it to identify high-probability setups, determine directional bias, and automate strategies across futures, stocks, ETFs, forex, and crypto. the platform includes 150+ customizable reports, a real-time screener, AI-powered cross-report analysis, 7 automated algos, and 50+ TradingView indicators.

## About

- Type: WebApplication
- Category: Financial Software — Trading Analytics, Market Data
- Audience: Futures traders, stock traders, forex traders, crypto traders — beginner to advanced
- Language: English
- Data Coverage: Futures, stocks, ETFs, forex, crypto
- Data Source: Direct exchange feeds, 7+ years of historical price data
- Last Updated: 2026-04

## Methodology

Edgeful analyzes historical price behavior across multiple dimensions: ticker, session (NY, London, Asian, full day), weekday, gap size, range size, and volatility conditions. reports calculate observed frequencies of outcomes (e.g., how often a gap fills, how far price extends past an initial balance level) over user-selected lookback windows ranging from 1 month to 10 years. outputs are probability percentages, directional biases, and statistical distributions — not predictions or signals.

Inputs: historical price data, ticker selection, session, date range, report filters, customization settings.
Outputs: probability percentages, directional bias (long/short/neutral), setup identification, target levels, stop placement data.
Example output: "ES gap downs on Mondays in the NY session fill 72% of the time over the last 6 months."

## Use Cases

- Determine directional bias (long, short, or neutral) before market open using historical probabilities
- Identify high-probability trade setups based on gap fills, opening range breakouts, initial balance breaks, and other patterns
- Backtest and validate trading strategies against historical data before risking capital
- Analyze cross-report confluence (e.g., what happens when a gap up aligns with an IB breakout) using Edgeful AI
- Automate trading strategies using data-driven rules with broker integration
- Screen multiple tickers across multiple reports simultaneously for session planning

## Features

- [Reports](https://www.edgeful.com/features/reports): 150+ historical probability reports covering gap fills, initial balance, opening range breakout, inside bars, outside days, FVG, and more. filterable by ticker, weekday, session, date range, and size.
- [Daily Bias Screener](https://www.edgeful.com/features/screener): scans up to 49 tickers across multiple reports simultaneously and returns a data-backed directional bias (long, short, or neutral) for each session.
- [What's In Play](https://www.edgeful.com/features/live-data): real-time setup discovery tool that filters all reports by probability and bias to surface active trading setups with target levels and dista
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