summary: the ORB report has 8 variants — each slices the data by a different dimension. here's what each one measures, when to use it, how to read it, and how to layer them for a sharper read.

the ORB report measures how price behaves after breaking outside the opening range. the standard view gives you the overall breakout rate. the 7 subreports slice that same data by a different dimension — time of day, range size, weekday, and more.

if you're new to subreports, read the full subreports reference first. this article is specifically about how to use each one on ORB.

the base view. shows the overall ORB breakout rate — how often price breaks above the opening range high or below the opening range low during the session.

this is your starting point. every other ORB subreport slices this same data by a different dimension. standard gives you the unfiltered picture first.

when to use it: you're getting your first read on ORB behavior for a specific ticker, session, and date range. you want to answer: does this instrument break its opening range consistently, and in which direction?

how to read it: look at the overall breakout rate first. if price breaks the range 85% of the time, the ORB setup is active and worth exploring further. if it's only breaking 55%, the range is holding most days and ORB breakout trades may not be your best approach. then look at direction — a 70/30 bullish lean is a stronger read than a 52/48 split.

tip: change the date range to see how the breakout rate has shifted recently. compare across sessions — the same instrument can show very different ORB behavior in the NY session vs. London.

shows where the day's close landed relative to the ORB breakout level — did price close above the range high, inside the range, or below the range low?

a breakout that fades back into the range by the close is a very different trade than one that holds. this subreport separates those outcomes.

when to use it: you're trading ORB breakouts and want to know if the move is likely to sustain through the session close. this matters most if you're holding positions into the end of day rather than taking quick scalps.

how to read it: a high percentage of closes above the ORB high on bullish breakout days means the move tends to stick. a high percentage of closes back inside the range means breakouts tend to fail or reverse by end of day. this directly shapes your exit strategy — if 70% of breakouts close back inside the range, holding to end of day is fighting the data.

tip: pair with standard. if standard shows a strong breakout rate but by-close shows most fade back, the setup is better suited for quick scalps than swing holds.

shows how often price reaches specific extension targets beyond the opening range — 25%, 50%, 75%, 100%, and further.

this is the most directly actionable subreport for setting take-profit targets. instead of guessing where to exit, you're using historical data to see how far price has actually gone after breaking out.

when to use it: you're setting a take-profit target and want to know the historical odds of price reaching that level. also where algo traders validate their TP settings — if you're running an ORB algo with a TP at 1.5x, pull up by-levels and see how often that target gets hit.

the break type setting: this subreport has a key setting most others don't. all breaks counts every breakout instance during the session, including re-breaks. first break counts only the first break — giving you the cleanest read on the initial move. use "first break" for initial breakout trades; "all breaks" for a broader picture.

how to read it: each extension level shows a fill rate that naturally decreases as you move higher. look for the point where the fill rate drops off sharply — that's where the move typically stalls. set your primary TP before that cliff.

tip: compare "first break" vs "all breaks." if "all breaks" shows a much higher fill rate at 100% than "first break," many of those extensions happen on the second or third attempt — not the initial one.

shows the full distribution of how far price traveled beyond the range after breaking out — not just whether it hit a specific target, but the entire spread of outcomes.

think of it as a histogram of breakout quality. how many moves were small? how many ran big? where does the typical breakout end up?

when to use it: you want to understand the overall quality of ORB breakouts on a given instrument. are most breakouts big moves, or do they stall early? use this to calibrate expectations before setting specific targets with by-levels.

by-performance vs. by-levels: this trips a lot of people up. by-levels asks "did price reach 50%?" — a yes/no at specific targets. by-performance shows the full spread of outcomes. use by-performance first to understand the range of possibilities, then by-levels to evaluate specific targets.

how to read it: look at where the bulk of the distribution sits. if most breakouts cluster around 25-50% extension, the instrument produces modest moves. a distribution with a long right tail means the instrument occasionally produces outsized moves — those are what make the setup profitable.

shows how often price pulls back toward the broken level after a clean single-direction breakout — and how deep those pullbacks typically go.

important: by-retracement only includes days with a single clean break. days where both sides of the range broke (double-break days) are excluded, since a double break changes the context entirely.

when to use it: you're looking to enter on a pullback after the initial breakout rather than chasing the move. this shows how often that re-test happens and how deep it goes — so you can decide where to place a limit order.

this is not fading the ORB. by-retracement shows pullbacks after a successful breakout — you're entering with the breakout direction on a pullback. fading the ORB (betting it fails) is a completely different thesis.

how to read it: if 70% of breakouts retrace to 25% but only 30% retrace to 50%, you're better off entering at the 25% level — waiting for 50% means missing most of the trades.

tip: pair with by-levels. by-retracement tells you where to enter on the pullback, by-levels tells you where to set your take-profit once you're in.

shows how breakout behavior changes based on the physical size of the opening range itself.

a 5-point ORB on NQ is a very different setup than a 50-point ORB. the breakout rate, extension, and follow-through can all shift dramatically depending on range size.

when to use it: you're filtering ORB setups by volatility conditions. also directly useful for setting max/min ORB size thresholds in your algo — if the data shows ORBs above a certain size tend to fail, set your max threshold there.

how to read it: the report groups ORBs into size buckets and shows the breakout rate, direction, and extension for each. look for size ranges that consistently outperform — those are your sweet spots. check the sample size in each bucket — a 90% breakout rate with only 5 occurrences isn't reliable.

tip: use this data to set your algo's min and max ORB size filters. instead of guessing what range size works, you're using the actual data for your instrument and session.

shows when during the session the breakout occurred — not whether it happened, but when.

a breakout at 9:45 AM often plays out very differently from one at 2:00 PM. early breaks tend to have more follow-through; late breaks can behave differently depending on end-of-day dynamics.

when to use it: you're optimizing entry timing. if 90% of ORB breakouts happen in the first hour and late-session breaks have poor follow-through, you know your window and don't need to sit in front of the screen all day.

how to read it: look for concentration — if most breakouts cluster in a specific time window, that's your highest-probability trading window. also look at follow-through by time — an early breakout might have a 70% continuation rate, while late-session might only continue 45%.

tip: combine with your algo's trading hours parameter. if breakouts after 2:00 PM tend to fail, set your algo to stop trading by 2:00 PM — you're filtering out bad setups, not missing good ones.

shows ORB breakout behavior broken down by day of week — Monday through Friday.

some instruments show meaningful differences by weekday. the ORB breakout rate on a Monday might look very different from a Friday, especially around regular economic releases or end-of-week flows.

timezone: weekdays are always determined by ET (Eastern Time), regardless of your location or the asset's primary trading timezone.

when to use it: you're day-of-week filtering your setups. if you can only trade 3 days a week and want to pick the best 3, by-weekday tells you which days historically produce the strongest breakouts on your instrument.

how to read it: each day shows its own breakout rate, direction lean, and sample size. a common pattern: Mondays and Fridays show weaker breakout rates, while midweek tends to produce cleaner moves. but this varies by instrument — the data will tell you.

tip: combine with by-time. if a specific day tends to break later in the session, that's a different setup than one that breaks early. layering weekday + time gives you a sharper picture.

you don't have to pick just one. most traders build their ORB process by layering multiple subreports:

that's not the only order — adjust based on what matters most to your process. the point is that each subreport answers a different question, and combining them builds a sharper picture than any single view.

what's the difference between by-performance and by-levels?

by-performance shows the full distribution of post-breakout moves — the shape of all outcomes. by-levels asks a specific question: how often did price reach a particular extension target? use by-performance to understand the range of possibilities, then use by-levels to evaluate specific price targets.

what's the difference between by-retracement and fading the ORB?

by-retracement shows pullbacks after a successful breakout — price broke out, then came back to retest the range. it's for entering with the breakout direction on a pullback. fading the ORB (betting it fails) is a different thesis entirely.

why does by-retracement exclude double-break days?

on a double-break day, price broke both sides of the range. that changes the context so much that including those days would distort the pullback data. by-retracement isolates clean single-direction breakouts for a cleaner read.

does the ORB timeframe affect subreport data?

yes. your ORB timeframe setting affects every subreport. a 5-minute ORB and a 15-minute ORB will show different data across all variants because the range itself is different.

what does "first break" vs "all breaks" mean on by-levels?

"first break" counts only the first time price broke the range in the session. "all breaks" includes every breakout instance during the day. use "first break" for initial breakout trades; "all breaks" for a broader picture.