[Sierra Chart]

SLS.*v1.2.3
Powerful Probability-Driven Analytics Suite

27 price levels — each with historical test rates conditioned on Open Type, IB Range Regime, and ETH Range Regime. A Markov-based sequence panel predicts the next target. Line thickness encodes probability at a glance.

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The Transformation

From guessing
to knowing.

See the difference between hoping a level works and knowing its historical probability.

Without StatLevels

Static lines, no hierarchy

Prior Day High
— no data
Prior Day Low
— no data
Overnight High
— no data

15+ levels on chart. Which ones actually matter today?

With StatLevels Suite

Probability-weighted zones

Prior Day High
pH 72.3%

High probability — primary target

Prior Day Low
pL 28.4%

Low probability — de-prioritize

Overnight High
oH 68.9%

Moderate-high — secondary target

Context: HIR Day

[Context-Aware]

Statistics change with market context

Every RTH open is classified based on position relative to the prior day's range and close. Statistics are segmented by Open Type — the first of three conditioning dimensions.

HOR

Higher Out of Range

Opens above prior day high

HIR

Higher In Range

Opens above close, below high

NOR

Neutral Open Range

Opens equal to close

LIR

Lower In Range

Opens below close, above low

LOR

Lower Out of Range

Opens below prior day low

Why context matters

On HOR days, prior day low test rates often exceed 70% (pullback expected). On LIR days, the same level might show only 35%. Same level, different context, different probability.

HOR: pL test >70%LIR: pL test ~35%

[Regime-Conditioned]

Same Open Type. Different regime. Different odds.

Open Type alone is not enough. A HOR day with a narrow IB after a quiet overnight behaves fundamentally different from a HOR day with a wide IB after an active overnight. SLS. conditions statistics on both dimensions automatically.

IB Range Regime

Initial Balance vs. Prior Day Range

N
Narrow

IB range small relative to prior day — range expansion likely

R
Normal

IB range proportional to prior day — balanced conditions

W
Wide

IB range already covers much of prior day — mean reversion likely

ETH Range Regime

Overnight Range vs. Prior Day Range

Q
QuietQUI

ETH range < 50% of prior day — limited price discovery overnight

A
ActiveACT

ETH range ≥ 50% of prior day — significant overnight movement

Combined key: Open Type + IB Regime + ETH Regime creates composite buckets like HOR_NQ, LIR_WA — each with its own test rates. Automatic fallback to unconditional stats when sample size is below 15 days.

Why regime conditioning matters

Unconditional test rates average across all market conditions — they're the right number for no specific scenario. Regime conditioning surfaces the actual edge: Narrow IB + Quiet ETH days show significantly higher range-expansion rates (pH/pL tests), while Wide IB + Active ETH days favor mean-reversion (IBH/IBL holds).

HOR_NQ: pH 83%HOR_WA: pH 42%HOR unconditional: pH 72%

[Visual Encoding]

Instant recognition without reading

Line thickness and style communicate probability at a glance. Scan your chart in seconds to identify high-priority levels.

75%+

Thick solid line

High-probability target

31-74%

Normal solid line

Secondary reference

30% or less

Dotted line

De-prioritize today

[Dynamic Updates]

Statistics that adapt as you trade

When a level is tested, probabilities update in real-time. Paired levels receive conditional AND-statistics.

1

Session opens

pH shows 67%, pL shows 45%

2

Price tests pL

pL stat drops to 0% (tested)

3

pH receives AND-stat

pH updates to 14.2% (conditional)

The AND-statistic represents: "Given pL was tested, what's the probability pH also tests?"

OR Statistics

"pH or pL" shows probability of testing either extreme. Useful for assessing overall range extension likelihood.

AND Statistics

"pH & pL" shows probability of testing both extremes. High AND-stat suggests trend day or double distribution.

[Predictive Panel]

Sequence prediction — what gets tested next?

A Markov transition matrix built from historical level-test sequences predicts the most likely next target. Conditioned on Open Type, IB Regime, and ETH Regime.

1

Sequence collected

Each historical day records the order in which levels were tested (e.g., oH → pH → IBL → pL)

2

Transition matrix built

From all observed sequences: given the last tested level, what was tested next? Grouped by regime composite key.

3

Panel ranks targets

After each live test event, probabilities update. Targets ranked by Bayesian-smoothed transition probability.

Fallback hierarchy: regime-conditioned bucket → Open Type bucket → aggregate over all types. Sample-size-aware weighting prevents thin buckets from dominating the prediction.

Markov Transitions

Historical sequences encoded as state transitions. Each level-test event updates the current state and recalculates next-target probabilities from the matching regime bucket.

Bayesian Ranking

Multiple ranking formulas available (incl. Bayesian Logit Blend, Robust Shrunk Ensemble). Confidence scores adapt to sample size — thin data shrinks toward the prior instead of showing noisy estimates.

VPOC Migration Targets

When the session VPOC migrates above IBH or below IBL, dynamic dH/dL levels appear. These represent directional conviction from volume migration — tracked with full test statistics.

OR Window Statistics

Five Opening Range periods (0.5m, 1m, 5m, 15m, 30m) — each with independent High/Low test rates. Automatically disabled when chart timeframe exceeds the OR period.

[Your Trading Day]

From preparation to edge accumulation

01

Pre-Market

Before market open

  • All key levels plotted — previous session and overnight activity
  • Review level placement and plan entry scenarios
  • Stats go live on first bar — full context from open
02

Market Open

RTH session start

  • Open Type auto-classified (HOR/HIR/NOR/LIR/LOR)
  • IB + ETH regime detected — statistics conditioned on context
  • Scan for thick lines (priority levels)
03

During Session

Live trading

  • Tested levels drop to 0%, partner levels receive AND-stats
  • Sequence panel predicts next target from transition matrix
  • VPOC migration creates dynamic dH/dL targets
04

Post Session

After close

  • Today's data added to database
  • Statistics improve over time
  • Your edge compounds daily

[27 Levels Tracked]

Complete coverage of key references

Prior day, overnight, initial balance, five opening range windows, and dynamic VPOC migration targets — each with historical test rate statistics conditioned on Open Type and market regime.

Prior Day

7

High, Low, POC, Midpoint, Close, VAH, VAL

pHpLpPOCpMDpClpVHpVL

Overnight

6

Globex session price and volume profile

oHoLoPOCoMDoVHoVL

Initial Balance

2

First 60 minutes of RTH

IBHIBL

Opening Range

10

Five OR windows — High + Low for each

OR 0.5mOR 1mOR 5mOR 15mOR 30m

VPOC Migration

2

Probability of a new day High/Low when the session VPOC migrates above IBH (dH) or below IBL (dL)

dHdL

[Built For]

Traders who think in probabilities

StatLevels Suite (SLS.) is designed for intermediate to advanced futures traders who understand that edge comes from objective data, not intuition.

SLS. builds its own statistics directly from the chart's historical data where it is loaded. You also receive a free starter dataset with more than three years of statistics.

Not for: Signal seekers expecting buy/sell alerts. SLS. provides statistical context — it doesn't replace your trading decisions.

Optimized for futures with defined RTH and overnight sessions

[Pricing]

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[The Statistical Edge]

Replace intuition with historical probability.

Every level on your chart becomes a data point, and your edge compounds over time — objectively, automatically.

Pair with Margin-9 for automatic position sizing and complete risk management.