Backtest archive · 1,233 trades · Silver futures · Apr 2022 – Apr 2026

Learn how to trade our zones with statistical edge.

Support and resistance zones, generated by a mathematical model — every reaction studied across 4 years of silver futures.

1,233 documented examples. Every level. Every outcome. Every lesson.

Built for intraday, swing, and position traders studying silver futures.
56.5% of winning trades never went into drawdown — see how, in every single setup.

From $49 · one-time · lifetime options available

You think you know your strategy.
But without data, you're only remembering the trades that worked.

Most traders carry a mental highlight reel — the wins they remember, the painful losses, a few "I called it" moments. What's missing is the full record.

The setups that almost worked. The ones that quietly stopped out. The patterns that look obvious in hindsight but blended into noise in real time.

This library is that full record. 1,233 trades. Every entry. Every exit. Every loss. Studyable, filterable, teachable.

Four years. Documented. Teachable.

1,233
Documented setups to learn from
56.5%
Of winning trades never went into drawdown
3.4x
Wins are larger than losses on average
Apr 2022 → Apr 2026
Continuous 4-year window
1.60
Profit Factor (fixed 1:3 risk-reward)
$354,957
Net PnL across the dataset
Every year profitable
4 full years studied — all positive
84%
Of months were profitable (41 of 49)

A complete, filterable, studyable record of every setup.

Not signals. Not predictions. A research and learning archive.

📊

Every trade, charted

1,233 dark-themed charts. Entry, stop, target, runup, drawdown. Every level visible.

🎯

Statistical Reaction Score

Each trade pre-scored on a 7-9 quality scale. Filter by score. See which setups have the cleanest entries.

🔍

Filter and drill down

By zone (S1/S2/S3/R1/R2). By outcome (bounce/break). By year. By score. By first-touch behavior.

📈

Full statistics dashboard

Equity curve. Monthly heatmap. Distribution charts. By-zone breakdowns. By-score comparisons.

📝

Structured trade observations

Each trade includes concise, structured observations — not generic AI commentary. Pre-generated for every setup.

Save trades to collections

Found a pattern? Save it. Annotate it. Reference it later. Build your own study library.

🔒

Lifetime access

One payment. Full archive. All updates as we add data.

What you'll actually be able to do

The library isn't theory. It's pattern recognition fuel.

🎯

Identify high-quality zones faster

Study 1,233 documented setups across all zone types. Train your eye to spot the structural conditions that precede clean reactions.

🚫

Avoid low-probability setups

See which Statistical Score levels lead to clean wins versus which ones bleed before paying. Skip the ones that don't fit your criteria.

🔍

Understand when levels fail

838 losing trades documented in full detail. Learn the conditions under which support and resistance break — so you stop expecting bounces that won't come.

⚖️

Improve risk-reward decision making

Watch how a 1:3 risk-reward ratio plays out across hundreds of real setups. See exactly how asymmetric payoffs compound over time, even at 32% win rate.

How the library teaches you to trade these zones.

The library doesn't tell you "enter here, exit here." It does something better — it shows you 1,233 documented examples of these zones in action, and lets you build your own pattern recognition.

By the time you've studied a few hundred setups, you'll see things you didn't see before:

📌Which zone characteristics precede clean entries

You'll spot them in live charts before they happen — not after.

📌What zone failure looks like before it confirms

838 losing trades are documented in full. You'll learn the warning signs.

📌Why some zones run 4R+ while others stall at 1R

The data shows you which structural conditions support continuation versus reversal.

📌How Statistical Score 9 setups differ from Score 7

A Score 9 trade earns 12x the expectancy of a Score 7 trade — you'll learn to wait for the difference.

No rigid rules. No black-box system. No "follow these signals." Just pattern recognition built from 1,233 real examples — the same way professional traders learn.

Different traders. Different lessons. Same library.

The Backtest Library isn't a one-size-fits-all signal feed. It teaches you what you specifically need to learn — based on how you trade.

Win rate is a vanity metric without context. 32% wins at 1:3 RR makes more money than 70% wins at 1:1 RR. The library teaches you why — and how to apply it to your style.

Strategy A
70% WR @ 1:1
Strategy B
32% WR @ 1:3
Risk per trade
$100
$100
Win
+$100
+$300
Loss
−$100
−$100
Over 100 trades
+$4,000 net
+$5,600 net

Same risk, same number of trades — Strategy B's asymmetric payoff wins, despite a much lower hit rate.

📈 If you're a INTRADAY trader

Learn how to trade our zones intraday.

What you'll learn
  • How S/R zones behave on first touch versus second versus third
  • Which intraday hours produce the cleanest reactions
  • How volume confirms or invalidates zone reactions in real time
  • Why some zones break instantly while others hold for hours
  • When to wait, when to enter, when to skip

You'll come away knowing: which intraday zones are worth waiting for, and which ones are statistical noise.

🔄 If you're a SWING trader

Learn how to trade our zones for multi-day holds.

What you'll learn
  • First-touch reactions that signal a multi-day reversal
  • Zone freshness scoring — why the 1st test of a level differs statistically from the 5th
  • Failure patterns — what a 'break' looks like before it confirms
  • R-multiple expansion data — how often winners run 3R, 4R, 5R
  • Which zones deserve overnight commitment

You'll come away knowing: which zones are worth holding overnight, and how to maximize R-multiples on the ones that work.

🎯 If you're a POSITION trader

Learn how to read our zones for structural commitment.

What you'll learn
  • Major support/resistance scoring — which zones held for months, which got blown through
  • Annual breakdowns — how the same zone types performed in trending years vs ranging years
  • Drawdown profiles — when the strategy struggled (and why) helps you stay in your seat during your own drawdowns
  • Setup quality at multi-touch zones — levels that get tested 4+ times before resolving

You'll come away knowing: which structural levels deserve position-sized commitment, and which are just noise dressed as structure.

🎓 If you're a STUDENT of trading

Learn how professional zone analysis actually works.

What you'll learn
  • 1,233 worked examples of zone identification, scoring, and outcome
  • Side-by-side comparisons of clean wins vs near-miss losses
  • Statistical Score breakdowns showing what makes a 9/9 setup different from a 7/9
  • The math of expectancy demonstrated across hundreds of real outcomes
  • Methodology documentation showing exactly how zones are generated

You'll come away knowing: how professional traders actually evaluate setups — not the YouTube version.

The library is a research and educational tool. It does not make trading recommendations specific to your situation, and we are not licensed financial advisors. How you apply what you learn is your decision.

The math behind the library — statistically verified.

Anyone can show profitable backtest numbers. The real question is: is this edge real, or is it luck?

We tested the strategy against four formal statistical benchmarks. Here's what the data says.

Test 1

Statistical Significance

A standard t-test on per-trade expectancy: p-value = 0.0003

There is a 99.97% probability that the strategy's profitability reflects a real edge — not random luck. Passes the strictest scientific significance threshold (p < 0.001).

Test 2

Beats Random Entry at Same RR

At a 1:3 risk-reward ratio, random entry needs ~25% win rate to break even. The strategy hits 32.04%.

Edge over random: +7 percentage points. Translated to dollars: 4.3x the profitability of random entries across the same 1,233-trade sample.

Test 3

Edge Persists Across Every Year Studied

YearTradesWRNet PnL
202221832.1%+$23,240
202332132.1%+$30,610
202430129.6%+$29,661
202530334.0%+$95,810
2026 (partial)9033.3%+$175,636

Every calendar year profitable. Edge doesn't depend on a single lucky year.

Test 4 — Most important finding

Statistical Score Has Real Predictive Power

If the scoring system is meaningful, higher scores should produce better outcomes. The data confirms it:

ScoreTradesWin RateAvg PnL/Trade
7/91,07031.3%$179
8/910735.5%$370
9/95639.3%$2,206

A Score 9 trade earns 12x the expectancy of a Score 7 trade.
This isn't a vanity metric. It's a measurable, replicable signal that tells you which setups carry the highest probability of clean, profitable execution — exactly the pattern recognition the library teaches you to develop.

This is what separates a research and education product from a signal service. We didn't write a sales page first and back-fit the numbers. We ran the math, found the edge, and documented it for you to verify — and to learn from.

Most strategies sell high win rate. We teach high trade quality.

Why is the win rate 32%?

Because we target 3x our stop distance. At wider targets, fewer trades reach them — but each win pays 3x what each loss costs. This is asymmetric payoff trading, and the math works.

When MPM-SCM wins, it wins clean.

  • 56.5% of winning trades never moved against entry
  • 88.6% of winners experienced less than three-quarters of stop distance in adverse movement
  • Average winning trade earned $2,407
  • Average losing trade cost $711
  • Wins are 3.4x larger than losses on average

The math doesn't need a 70% win rate to compound capital. It needs asymmetric payoffs — risking $1 to make $3, repeated across a large enough sample for the edge to play out.

That's what this library teaches. Every loss disclosed. Every assumption transparent.

For traders who want to verify the math.

A 32% win rate forces you to confront the math directly. You cannot rely on "feeling right often" — you have to trust the expectancy. That discipline is what separates retail traders from professional ones.

MetricValueWhat it means
Statistical Significancep < 0.00199.97% probability edge is real, not luck
Recovery Factor9.29xNet profit was 9x larger than worst drawdown
Profit Factor1.60Gross profit divided by gross loss
Realized Win/Loss Ratio3.4xAverage win compared to average loss
Expectancy per trade$288What an average trade contributed
95% Confidence Interval[$134, $442]Range expectancy likely falls in
Max DD as % of gain10.8%Worst drawdown was 11% of total net profit
Profitable months84% (41/49)Most months were net positive
Worst month-$2,421November 2023
Best month+$90,373February 2026
Avg holding time3.2 hoursTrades resolve in same session typically
Beats random entry+7pp WRAt same 1:3 risk-reward

All metrics derived from backtest data assuming next-bar-open execution with no slippage. Live trading performance will differ.

Three trades. Three different outcomes. All from the actual dataset.

Click any chart to enlarge. These are the same charts you'll study in the full library.

watermarked chart preview
S1 · Long BounceWIN
+$3,450
Score 9/9 · Zero drawdown

Price tagged S1 zone bottom, never dipped below entry, ran $3,450 favorably.

watermarked chart preview
S2 · Long BreakLOSS
-$600
Score 8/9 · Stopped cleanly

S2 support failed on second test. The library documents every loss this clearly.

watermarked chart preview
R2 · Short BounceWIN
+$4,000
Score 8/9 · Zero drawdown

R2 resistance held. Short entry filled at zone top, target reached without retest.

Rigorous methodology. Full disclosure.

What we did
  • 4 years of 1H silver futures data (CME SI contract)
  • ATR-based zone generation (MOD1 mathematical engine)
  • Walk-forward backtest with no look-ahead bias
  • Risk-reward locked at 1:3 across every trade
  • Statistical Score filter ≥ 7 (no cherry-picking)
  • Monte Carlo robustness testing (1,000 reshuffled trade orderings — 100% remained profitable)
What we don't do
  • Curve-fit parameters to past data
  • Hide losing trades or unfavorable periods
  • Promise live trading performance matches backtest
  • Sell signals — this is a study and education tool, not a copy-trade service
What you get
  • The raw trades CSV (downloadable)
  • Methodology documentation
  • All parameters disclosed

To be clear, this library is NOT for:

  • Traders who want a black-box system that trades for them
  • Anyone who needs 70%+ win rate to feel confident
  • People unwilling to study charts and patterns
  • Anyone expecting backtest to equal live performance
  • Buyers expecting refunds (digital product, all-sales-final)

If any of those apply, this isn't the right product. We'd rather you not buy than be disappointed.

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Stop guessing. Start learning.

1,233 documented setups. Every entry. Every exit. Every loss. Every win.
A 4-year window into how levels actually behave — and how to read them.

Built for traders who want to learn how the zones work, not gamble on what they hope will happen.

Launch price · One-time payment · Lifetime access · Pricing increases as data expands