Historical signal measurements — in-sample-labeled, measured not promised, and pre-fee. These are not guaranteed trading profits.
Our engine produces two kinds of signals with very different quality, and we report them separately and honestly: the higher-quality Confirmation signals (Type 1) — a real-time whale-aggregation and confirmation layer with measured in-sample directional accuracy, though not a standalone profit engine after costs — and raw Regime-Flip events (Type 2) — positioning context that shows what whales are currently doing, not a tradeable prediction (no measured out-of-sample edge). Every headline number on this page is Type 1 only. Type 2 lives in its own clearly-marked section further down.
Confirmation signals
Directional accuracy of the smart_money_confirm measured subset (in-sample — see methodology below) — the same numbers shown on the homepage, sourced from /v1/stats. This headline card is a fixed full-sample measurement — the Period filter above applies to the tables, charts and feed below, not to this card.
Whiskers = 95% confidence interval (Wilson) from the resolved sample size — the honest uncertainty around each rate. The dashed line marks 50%, what a coin flip would score.
Methodology. These figures are the smart_money_confirm subset, measured over distinct signal calls (31 calls, 31 resolved 4–24h outcomes), direction-adjusted. A live call is re-confirmed every few minutes while it persists — the raw feed logs thousands of rows — but each episode counts once here (a >12h gap starts a new call), so the win rate cannot be inflated by how long a call stays live or how often a bot polls it. The sample is small and in-sample: ~25 days (since Jun 10), largely one market regime — treat it as descriptive of that history, not a forward guarantee.
The only forward-looking honest number is our frozen forward-holdout, which is still accruing: accruing. Until it has enough resolved signals it does not yet report a win rate.
Historical directional accuracy of confirmation signals — not trading profit. Past performance does not guarantee future results. Not financial advice.
Live forward test · not a backtest
Every smart_money_confirm signal was published in real time and scored against the actual subsequent price — a forward test, not a hindsight backtest. Measured over distinct signal calls (5-minute re-emissions of the same call collapsed to one), the standalone directional record is roughly break-even before costs and slightly negative after — which is exactly why we position these as a confirmation / veto layer on top of your own setup, not a standalone strategy. We show the full curve, honestly, either way.
Each solid line is a different position size per signal; the muted dashed line is BTC buy-and-hold over the same window (both start = 100). Both return and drawdown scale with size — and since this standalone record is around break-even, larger sizing mostly just amplifies the swings. The shaded region is in-sample (scoring was tuned there); everything to its right is the forward holdout. The per-signal stats above don't depend on sizing. This is why the signal is built to confirm your setup, not to be traded blindly.
Forward test, not a backtest. Signals were generated live and scored on real subsequent price — no hindsight, no curve-fit entries. Scoring was tuned within this window (in-sample); the out-of-sample holdout since our scorer freeze is still accruing.
Pre-fee, no stop-loss. Figures use the raw 4–24h move; a stop would cap the −4%+ loss tail further. Drawdown depends on position sizing (shown above).
Past performance does not guarantee future results. Not financial advice.
Full transparency · live
The unfiltered feed — every smart_money_confirm signal as it fires, with symbol, side, entry price, time and result. Nothing cherry-picked.
— raw rows = the same calls re-firing every ~5 min while they stay live. The win-rate above collapses these into 41 distinct calls (a >12h gap starts a new call), so the rate can’t be inflated by how long a call persists or how often a bot polls it. See the methodology for the full breakdown.
| Generated · age | Symbol | Side | Entry | Best 4-24h | 24h | 48h | 72h |
|---|---|---|---|---|---|---|---|
| Loading live feed… | |||||||
Each column is the direction-adjusted move at that fixed holding period (green ✓ = correct call). Open signals show a live ◉ LIVE mark in the 24h column until they close at the 7-day mark. Same data behind the charts — download it (4h–7d) and check the math.
Only fires when several independent sources agree: derivatives positioning (funding, long/short ratio, open-interest momentum) + whale consensus + on-chain metrics + price-zone (premium/discount inside the 24h range). A stacking gate requires ≥2 factor families to confirm the same direction, and a confidence threshold drops the rest. Fewer, higher-quality calls — the ones with a measured edge (PF 1.77 across all distinct calls, 2.49 on the HIGH tier).
Fires whenever the aggregate whale consensus flips net direction (long↔short) on a symbol between snapshots. It describes what whales are currently doing — a lagging snapshot of crowd positioning, not a forecast. It catches every wobble, most of which mean-revert. On its own it has no measured out-of-sample directional edge; its value is situational awareness, and as one input the Confirmation engine weighs.
Why show a losing signal at all? Because hiding it would be dishonest — and because the gap between Type 1 (PF 1.77) and Type 2 (PF below 1) is the product: the Confirmation engine's entire job is to filter this Type-2 noise down to the Type-1 signal. Figures computed live from the same public /v1/signals feed, direction-adjusted 4–24h, pre-fee.
How a stop-loss policy + leverage reshape either signal type's outcome distribution — win rate, profit factor, expectancy, drawdown, and liquidation rate. Click to expand.
Every signal is replayed on its 15-minute price path. Pick a stop-loss policy and a leverage to see how the outcome distribution changes. Numbers are pre-fee, in-sample, over distinct calls (bot-poll repeats collapsed). This is a transparency tool, not a promise — many rows lose money (profit factor below 1) because these signals have thin-to-no edge once stops, leverage and cost are applied. Losing rows are shown and labeled, not hidden.
The Hold to horizon & close row (highlighted) is the current site scoring baseline: no stop, close in profit or loss at the horizon. Every stop level is a separate row. Click any row to select it for the summary and sweep below.
| Stop-loss policy | n | Win % | Profit factor | Expectancy % | Avg win % | Avg loss % | Max DD % | Liq % |
|---|
Same policy, leverage swept 1x→10x. Watch the liquidation rate and max drawdown climb. At 1x there is no liquidation.
| Leverage | Liq threshold | Win % | Profit factor | Expectancy % (ROE) | Liq rate % | Max DD % |
|---|
Complementary to the HIGH-confidence confirmation subset above — this is a broader, rolling 30-day measurement over all actionable signals (a different, larger dataset), so its numbers differ from the confirmation-signal figures at the top. This table contains two different accuracy measurements that answer different questions. Time-window accuracy measures what percentage of all signals were correct when checked at a specific time horizon (1h, 4h, 12h, 24h). Confidence-level accuracy measures correctness broken out by how confident the system was — HIGH or MEDIUM — regardless of when the outcome was evaluated.
| Metric | Accuracy | Correct | Wrong | Signals |
|---|---|---|---|---|
| HIGH confidence (example) | 71% | — | — | — |
| Sample row — live accuracy data loads when you open this page. | ||||
Directional accuracy of all actionable signals measured at each evaluation window — the same resolved outcomes shown in the time-window table above, drawn straight from live tracking with no smoothing. Accuracy tends to be highest at short horizons and decay as the window lengthens; we show that honestly rather than cherry-picking the best number. This is the "was it right when checked at 1h / 4h / 12h / 24h?" question — separate from the confidence-tier split (HIGH vs MEDIUM), which asks "how sure was the system when it fired?"
Directional win rate at each horizon (1h / 4h / 12h / 24h), computed from resolved outcomes only. Whiskers = 95% confidence interval; dashed line = coin flip (50%). Hover a bar for the resolved sample size.
Correct (green) vs wrong (red) signal counts per horizon — the raw resolved sample behind each accuracy bar. Taller stacks = more signals scored at that window.
Cumulative vs daily win rate — real tracked data
smart_money_confirm win rate over timeRolling 20-signal directional win rate over the resolved confirmation signals in the selected Period above (direction-adjusted, best 4–24h move, in-sample). Dips below the 50% coin-flip line are real and shown.
Breakdown by confidence level
Signal accuracy (4h/12h/24h resolved outcomes) — only symbols with 10+ scored signals shown
Win rate per symbol at selected time window — click a symbol to toggle visibility
deriv040 — live derivatives account tracked in real time
| # | Symbol | Dir | Entry | Exit | PnL | Duration | Exit Reason |
|---|---|---|---|---|---|---|---|
| 1 | BTC (example) | LONG | — | — | — | — | Sample — live trades load on open |
Our system monitors 3 major exchanges (Bybit, Binance, Hyperliquid) across 519 symbols in real time, tracking derivatives data, 601 whale wallets, funding rates, open interest, and liquidation levels. Every signal passes a 5-factor confirmation pipeline before publication.
Every 5 minutes, our engine scans 519 symbols for whale consensus regime flips. Each detected flip passes through a 5-factor confirmation pipeline: cross-asset alignment (BTC/ETH agreement), derivatives confirmation (funding rates, long/short ratios, OI momentum), price zone analysis (premium vs discount within 24h range), multi-snapshot consistency, and whale momentum acceleration. Only signals scoring above 0.45 confidence are published. Each signal includes direction (LONG/SHORT), a confidence score from 0.0 to 1.0, and entry price.
We auto-discover and monitor 601 whale wallets from Hyperliquid — the largest on-chain perpetual DEX. See what smart money is actually doing: position sizes, entry/exit points, which tokens they're accumulating, and when they're reducing exposure. This isn't aggregated data — it's individual wallet-level intelligence updated in real time.
Full derivatives screener for 519 symbols with sortable columns: open interest (absolute + 1h/24h change), funding rates across exchanges, long/short ratios, and top trader sentiment. Funding rate heatmap shows at a glance where leverage is building. OI rankings reveal which assets have the most speculative interest right now.
Every signal is tracked against actual Binance spot prices at 1h, 4h, 12h, and 24h intervals. These are live-tracked measurements, not backtested-only claims. The accuracy you see on this page is computed from real signals issued in real time, evaluated against real market data. You can click any signal to see its full outcome breakdown at each time window.
40+ API endpoints covering signals, derivatives, whale data, on-chain metrics (TVL, stablecoins, DEX volumes, gas), options flow (BTC/ETH PCR, max pain, OI by strike), ETF flows (BTC/ETH daily fund-level breakdown), and market indices. WebSocket streaming for real-time updates. Python and JavaScript SDKs. Integrate into your trading bot, dashboard, or research pipeline in minutes.
DeFi TVL tracking, stablecoin supply and flow analysis, DEX volume monitoring, BTC hash rate and difficulty, Ethereum gas prices, mempool congestion, and DeFi yield comparisons — all from a single API. See where liquidity is moving across chains and protocols. Identify capital rotation before it shows up on price charts.
Before entering any position, check if smart money signals agree with your thesis. A high-confidence signal (0.65+) means 5 independent factors confirmed the direction. A medium signal (0.45-0.64) provides partial support. Use the confidence score to gauge conviction strength.
Connect the API to your trading bot via REST or WebSocket. Filter signals by confidence score threshold and symbol. Execute trades automatically when conditions are met. Each signal already passed 5 confirmation gates — set your own minimum confidence (e.g. 0.60+) for additional selectivity.
Monitor liquidation levels, funding rates, and OI changes across your portfolio. Low confidence signals indicate weak multi-factor confirmation. Track stablecoin flows and exchange reserves as early warning indicators for market-wide risk events.
Track what the biggest wallets on Hyperliquid are doing in real time. See position openings, size increases, and exits. When multiple whales accumulate the same asset simultaneously, it's often a leading indicator of significant price movement.
Build custom dashboards combining on-chain data, derivatives metrics, and signal performance. Analyze funding rate arbitrage opportunities across exchanges. Study correlations between whale behavior, OI changes, and subsequent price action over historical data.
Monitor BTC and ETH options data including put/call ratio, max pain, and OI by strike. Track daily ETF inflows/outflows per fund with cumulative tracking and streak indicators. Understand institutional positioning through regulated product flows.
Visualize liquidation clusters across exchanges. Identify price levels where large cascading liquidations could trigger. Use this to set better stop-losses, avoid crowded liquidation zones, and anticipate sudden volatility spikes.
Combine long/short ratios, funding rates, and social sentiment to gauge market mood. When extreme greed meets high funding rates and leveraged longs, it's often a reversal signal. Our multi-factor confidence system quantifies this across 5 independent data sources.
Every 5 minutes, the Smart Money engine scans 519 symbols for whale consensus regime flips — moments when the short/long ratio shifts violently against the 7-day median. Each raw detection then passes through a 5-gate confirmation pipeline: (1) cross-asset check (BTC/ETH must not strongly contradict), (2) derivatives alignment (funding rate, global and top-trader LSR, OI momentum over 1h), (3) price zone filter (premium/discount within 24h range), (4) multi-snapshot consistency (4-6 whale snapshots moving monotonically), and (5) whale momentum acceleration. Signals below 0.45 confidence are rejected. Only confirmed signals are published with a direction, confidence score (0.0 to 1.0), and entry price.
Every signal is automatically tracked against Binance spot prices at four fixed intervals after issuance: 1 hour, 4 hours, 12 hours, and 24 hours. A LONG signal is marked correct if price is higher at the measured window; a SHORT signal is marked correct if price is lower. There is no manual curation — all outcomes are computed automatically and published as-is, including losses.
Win rate for each symbol and timeframe is computed as correct outcomes divided by total resolved signals for that window. A signal is unresolved until the measurement window has passed. The system caps recent signals at 2000 to keep the feed performant. Historical data beyond the displayed period is archived and available for download on Pro tier accounts.
1-hour accuracy is noisiest — even a correct directional signal can show a temporary opposite move within the first hour due to natural volatility. High 1h accuracy means the signal is capturing very immediate momentum shifts.
4-hour accuracy is the most actionable window for discretionary traders. It's long enough for a setup to play out with meaningful price displacement, but short enough that the original market regime — the conditions the signal was generated under — hasn't fundamentally changed. If you use signals for trade entries, prioritize symbols with high 4h win rates.
12h and 24h accuracy reflects the signal's ability to predict broader trend continuation. These windows are most relevant for swing traders and for evaluating whether the underlying thesis (derivatives positioning, whale accumulation) has lasting predictive value.
A win rate alone is not sufficient to evaluate a signal. A system that is right 60% of the time but loses twice as much on losers as it gains on winners has negative expected value. Use the accuracy percentage alongside the average return figures to estimate the quality of each signal category.
HIGH confidence signals (0.65+) are issued less frequently because they require all 5 confirmation gates to score strongly: cross-asset agreement, derivatives alignment, favorable price zone, consistent whale snapshots, and momentum acceleration. MEDIUM signals (0.45-0.64) passed the minimum threshold but with weaker multi-factor support. You should generally expect HIGH signals to carry higher win rates.
The per-symbol accuracy chart lets you spot which assets the system models well. Assets with consistently high accuracy across multiple timeframes are strong candidates for systematic trading. Assets with low accuracy despite sufficient sample size may have microstructure characteristics that resist the current signal methodology.
Every 5 minutes the engine scans 519 symbols for whale-consensus regime flips — moments when the aggregate long/short ratio shifts sharply against the 7-day median. Each candidate then passes a 5-factor confirmation pipeline before it is published:
Signals that do not reach a composite confidence score of 0.45 or above are rejected and never published. Only confirmed signals are recorded, stamped with a direction (LONG / SHORT), a confidence score from 0.0 to 1.0, and the market price at the moment of issuance.
All outcomes are tracked against Binance spot prices, captured automatically at four fixed intervals after each signal:
No prices are curated or adjusted after the fact. Price captures run on a fixed schedule and are stored as-is, including during volatile periods.
Each evaluation window applies a small deadband threshold to filter out micro-noise:
Win rate = wins ÷ (wins + losses) on fully resolved signals. Neutral outcomes are excluded from the denominator so they neither inflate nor deflate the rate.
A win rate computed from 2 or 3 signals carries no statistical meaning — yet it can look like 100 % or 0 %. To prevent misleading headlines, symbols and horizons with fewer than 10 resolved signals are flagged as low-sample ("thin data" badge) and are excluded from the headline summary cards. They are still visible in the per-symbol grid with a muted colour so you can see the raw count, but they are not surfaced as "best" or "worst" performers.
The numbers shown on this page represent historical directional accuracy of the confirmation-signal pipeline, not trading profit or loss. Fees, slippage, position sizing, and execution timing are not modelled.
Honest baseline
Real system-wide win rates across all periods and confidence levels have measured in the range of approximately 50–54 % — only modestly above a coin flip. High-confidence signals (0.65+) tend toward the upper end of this range; medium-confidence signals (0.45–0.64) toward the lower end. Do not assume the latest short-window figure represents a durable edge.
This is not financial advice. Past performance does not guarantee future results.
All accuracy statistics shown here reflect real signals generated and tracked in real time. However, past signal performance does not guarantee future accuracy. Market regimes change — a signal methodology that works well in trending conditions may underperform in ranging markets. Always evaluate recent performance (last 7d or 30d) alongside all-time statistics.
Accuracy statistics are only meaningful with sufficient sample size. Symbols with fewer than 20 resolved signals in the selected period should be treated with caution — small sample sizes produce large statistical variance in win rate. Focus on symbols with 50+ signals per window for reliable accuracy estimates. The system continues logging signals as long as derivatives data is available, so sample sizes grow over time.
Signal accuracy is measured against Binance spot prices and does not account for slippage, trading fees, or the difficulty of executing at the exact entry price shown. Actual realized returns from trading these signals will differ from theoretical accuracy-based estimates. A signal being "correct" means price moved in the right direction, not that a specific trade would have been profitable after costs.
Disclaimer: Signal performance data is published for transparency and informational purposes only. It does not constitute financial advice or a solicitation to trade. Past accuracy rates are not indicative of future results. Crypto markets are highly volatile and carry substantial risk of loss. Always apply your own risk management rules, use stop-losses, and trade only with capital you can afford to lose entirely.
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