Edgeful Reports Explained: Complete Guide

What Are Edgeful Reports?

Edgeful reports are statistical analyses of recurring market patterns in the futures markets. Each report examines a specific scenario — like "ES gaps up between 0.25% and 0.50% on a Monday" — and shows what happened historically. The goal is to give traders data-driven probabilities to inform their decisions.

Every report includes a win rate (how often the pattern played out as expected), a sample size (how many instances were analyzed), a date range, and breakdowns by day of week. The reports are based on historical backtesting of price data going back several years.

Edgeful currently offers over 150 individual reports covering major futures contracts including ES (S&P 500 E-mini), NQ (Nasdaq), YM (Dow), RTY (Russell 2000), CL (Crude Oil), GC (Gold), and several others.

Types of Edgeful Reports

How Edgeful Reports Work

The methodology behind Edgeful reports is straightforward backtesting:

1. Define the condition. A specific market scenario is defined — e.g., "ES opens with a gap up between 0.25% and 0.50% on any weekday."
2. Scan historical data. Edgeful scans years of historical price data to find every instance matching this condition.
3. Measure the outcome. For each instance, the outcome is measured — did the gap fill? How far did price extend? Did it hold a level?
4. Calculate statistics. Win rate, sample size, and day-of-week breakdowns are computed.
5. Present the report. Results are shown in a clean interface with the ability to filter by date range and contract.

The reports are updated as new data comes in, so the statistics evolve over time. However, Edgeful reports are inherently backward-looking — they tell you what happened, not what will happen.

How to Use Edgeful Reports in Your Trading

The most effective way to use Edgeful reports is as confirmation, not as your primary trading signal. Here's a practical approach:

• Pre-session preparation. Check relevant reports before the session opens. If ES gapped up 0.35%, check the gap fill probability for that range. This sets your bias before you even see a candle.
• Confluence with other analysis. If your technical analysis suggests a long entry near PDL and Edgeful's report shows PDL holds 68% of the time, that's useful confluence — not a trade signal on its own.
• Risk management. If a report shows that gaps above 0.75% only fill 35% of the time, it might discourage you from fading a large gap — saving you from a common mistake.
• Pattern filtering. Use reports to filter which setups to take. If your strategy is based on initial balance extensions, knowing which extensions have the best historical odds helps you focus on higher-quality setups.

Limitations of Edgeful Reports

It's important to understand what Edgeful reports can and cannot tell you:

• Historical accuracy is not predictive. A 72% win rate over the past 5 years doesn't mean the next instance has a 72% chance of success. Market regimes change, and past patterns may not persist.
• Survivorship bias concerns. Reports that "work" get highlighted, while patterns that stopped working get less attention. Be cautious about cherry-picking the reports that confirm your existing bias.
• No context for current conditions. Reports don't account for today's specific context — FOMC days, earnings season, VIX spikes, or unusual market conditions. A gap fill probability calculated across all days may not apply on a Fed decision day.
• Sample size matters. Some reports have small sample sizes (under 100 instances), which makes the statistics less reliable. Always check the sample size before trusting a win rate.
• No real-time component. Once the session is underway, Edgeful reports don't update. You can't see how the current session is tracking against historical patterns in real time.
• Correlation isn't causation. Just because a pattern has repeated historically doesn't mean there's a causal mechanism ensuring it continues. Market microstructure changes over time.

Supplementing Edgeful Reports with Real-Time Data

The biggest gap in Edgeful's approach is the lack of real-time context. Statistical patterns are more useful when combined with live market data that shows whether today's conditions align with the historical pattern.

This is where platforms like Profitabul complement (or replace) Edgeful's approach. With live orderflow data, you can see whether institutional participants are actually buying into a gap fill scenario or whether volume is drying up. GEX heatmaps show where options dealers have positioned, adding another layer of context that pure statistics can't provide.

The combination of "this pattern filled the gap 72% of the time historically" with "and right now, delta is strongly negative with heavy selling at VWAP" gives you a much more complete picture than either data source alone.