Every session, quantified.

The OHLC Table is an indicator that turns every session on your chart into structured data you can study — live in TradingView.

See for yourself
01 / 06

The OHLC foundation.

The basic values: Open, High, Low and Close, with the exact time the High and the Low formed during the session.

02 / 06

Direction, Raid, Range.

Direction and Range print themselves. Raid watches the closed levels — a high or low traded through is stamped the minute it breaks.

03 / 06

Derived depth, on demand.

Toggle in Avg Range \ Avg R Consumed and Volume \ Relative % — each window measured against its own baseline, over a lookback you set: 10 sessions by default, up to 20, chart history permitting.

04 / 06

Range anatomy.

Manipulation \ Distribution \ Retracement — each leg in points, or points with its share of the window's range. The readout is a setting, and every metric is its own checkbox: have them all, a few, or none.

05 / 06

Live tick precision.

Tick by tick: a new extreme prints stamped to the minute, and a raid is logged the minute the level breaks — on the chart's symbol, or any other you point the table at.

06 / 06

Each session, side by side.

Six fully configurable slots — customizable for any trader, style or preference. Build your own version, or start from a ready-made roster in the Roster Library.

NQ1! 5m · interactive recreation New York · forming
Your Dataset

The table does the math,
so you can build your own record.

Collecting session data used to be manual work. Now it prints itself, every session.

Context and outcome, side by side.
DateSessionLow @ManipDistDirR:R
05-12Asia23:4087.25214.25Long+1.4R
05-13London02:30121.50108.50Short−1.0R
05-14Premarket07:1033.75152.75Long−0.6R
So hindsight stops rewriting the story.

Memory grades a trade by how it ended; a record grades it by what was true at the time. Keep context beside outcome and, rows later, you can see where your results actually come from — which windows, which kinds of days — instead of where you remember them coming from. One screenshot and the pack’s transcription prompt fills a row.

columnsdatewindowlow_timemanip_ptsdist_ptsdirection_pts+ yours
Score your performance
?%
your session · your trades
Tag a session — New York AM, the London close — log each outcome, and a win rate builds.
So you learn where you’re actually good.

A day has many sessions, and most traders grade the whole day. Grade each window instead, and the record starts answering the only version of the question that matters: not whether the approach works — whether it works for you, in the hours you trade it.

columnswindowyour outcome
Track what follows a raid
ContinuesReverses
Continuation or reversal? Log each raid’s outcome and build your own split.
So an assumption gets a price check.

Everyone carries a belief about what follows a raid. The log exists to test yours: after twenty or thirty entries you’ll know whether your market’s record agrees with your instinct — before you keep paying for the difference.

columnsraided_highraided_lowraid time+ your note
Learn when your market prints its extremes
Collect the High and Low timestamps for a month, and see when your market tends to print its extremes.
00:0009:3016:00
So you know when your market does its business.

If the day’s extremes cluster in a particular hour, that hour deserves your attention — and the hours that never print them can stop costing you focus. A month of stamps turns “I feel like the open matters” into a shape you can point at.

columnshigh_timelow_time
Do both extremes get raided?
?%of days
A question the Raid row answers within a month — one cell a day.
So “safe until it isn’t” gets a number.

How often does one day take both sides? Whatever you’d guess, the record answers it exactly — and knowing that number tells you how much weight a single standing level can actually carry in your market.

columnsraided_highraided_low
Measure your market’s average range anatomy
Log manipulation, distribution and retracement per session, in points and share of range.
Distribution361.25
Manipulation117.50
Retracement88.75
So you know what normal looks like.

Average the legs and you own your market’s typical shape — how deep the counter-move usually runs, how much gives back. The value isn’t the average; it’s the moment a live session stops matching it — visible only because you know normal cold.

columnsmanip_pts · sharedist_pts · shareretr_pts · share
Combine different metrics.
Does the opening range set the morning’s scale? Opening Range against AM Range makes the line; add Relative Volume and it becomes a surface. Your record does the fitting.
6010015020020406080100 Opening Range (pts) AM Range (pts)
100150200 Opening Range (pts) Rel Volume (%) AM Range (pts)
So folklore has to pass a test.

Every trader carries relationships on faith — quiet overnight, wild day; deep fake, strong move. Plot yours from your own record — two metrics make a line, a third makes a surface — and keep only what survives the fit. A slope is never a forecast; it’s a way to retire stories that were never true.

columnsany numeric column× any other

A few angles to steal. Collect it your way: a spreadsheet, a notebook, whatever you already use.

Illustrative samples — not track records. Yours will look nothing like these.

The questions a record can answer — and the prompts that ask them — live in the Docs.