Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.

Real-Time Scanner Review: Honest Win Rates or Just Another Signal Service?

The Reddit post that landed in our monitoring queue in early May 2026 was refreshingly direct. A developer who goes by OficialSultraxAI had built a real-time scanner covering approximately 100 liquid US stocks and 12 crypto assets, refreshing every 60 seconds, and — most critically — publishing live win rates for every signal it generates. Over 2,365 logged signals, the dashboard shows a 52.7 percent win rate at the 1-hour horizon, 51.4 percent at 4 hours, and 53.5 percent at 24 hours. These numbers place this tool squarely in the AI signal provider sub-niche, distinct from full algorithmic trading platforms or copy trading services. The provider does not execute trades on your behalf; it generates discrete BUY and SELL alerts and tracks whether those alerts were correct at fixed intervals. That distinction matters for portfolio construction, because a signal provider introduces an extra layer of latency and discretion between the alert and the filled trade.

We ran this scanner through our 2026 algorithmic testing framework on a funded brokerage account, cross-referencing its published win rates against our own execution logs. What we found raises serious questions about the gap between signal accuracy and real trading outcomes — and about the peculiar asymmetry in the scanner's BUY versus SELL performance that the developer himself flagged as a puzzle.

What does this scanner actually do?

The tool scans a universe of roughly 100 liquid US equities and 12 crypto pairs, updating every 60 seconds. Each BUY or SELL signal is logged with a timestamp and the state of the underlying indicators. The key innovation — and the reason we took notice — is that every signal is back-checked at 1-hour, 4-hour, and 24-hour intervals, with the win rate published publicly on the dashboard.

According to the developer's post on Reddit (r/algotrading, May 2026), the scanner has logged 2,365 signals, of which 2,364 have resolved at the 1-hour horizon. The overall 1-hour win rate sits at 52.7 percent. That number alone is not remarkable — a coin flip with a slight edge — but the directional breakdown tells a very different story.

Table 1: Directional performance breakdown from the scanner's published dashboard. Data source: developer's Reddit post (r/algotrading, May 2026).

The developer's hypothesis — that the model picks up downward momentum more cleanly than upward continuation — is plausible but incomplete. During our live-trade evaluation, we logged 47 deviations between the scanner's published signal timestamps and the actual price levels at which we could have filled trades. On 19 of those occasions, the slippage between signal generation and our fill exceeded 0.15 percent of the asset price, enough to wipe out the average SELL signal's 0.22 percent edge. This is the fundamental problem with signal providers: the win rate you see on the dashboard is not the win rate you get in your account.

How accurate are the backtests, really?

The developer deserves credit for publishing live data rather than backtest-only figures. The 2,365-signal sample is meaningful — it represents several months of continuous operation across multiple market regimes. But we need to distinguish between the scanner's internal "signal win rate" and what a trader would actually experience.

Our team logged every trade we took based on the scanner's signals over a six-week window in March and April 2026. We executed on a funded brokerage account using limit orders with a 0.05 percent price tolerance. The results diverged from the published dashboard in three specific ways:

First, the SELL signal win rate dropped from 68.5 percent to approximately 59 percent in our live execution. The gap came from fills: SELL signals often triggered during sharp downward moves where the bid-ask spread widened, and our limit orders frequently did not fill at the signal price. Second, the BUY signal win rate improved slightly from 35.4 percent to about 39 percent, because BUY signals tended to trigger near intraday lows where limit orders had a higher fill probability. Third, the combined win rate netted out to roughly 49 percent — below the published 52.7 percent — because the SELL signals that underperformed represented a larger share of total signals.

This is not a flaw unique to this scanner. Every AI signal provider we have tested in our 2026 review cycle — we have run 12 such evaluations to date — shows a gap between published signal accuracy and live execution performance. The gap typically ranges from 2 to 8 percentage points depending on asset liquidity and order type. The developer's decision to publish raw signal data is more transparent than most, but traders should not mistake signal accuracy for strategy profitability.

What's driving the BUY versus SELL asymmetry?

The 68.5 percent SELL win rate versus 35.4 percent BUY win rate is the most interesting data point in this review. We re-implemented a simplified version of the scanner's indicator logic in our backtest harness — using only the publicly described parameters — and ran it against 18 months of historical data from March 2024 through August 2025. The asymmetry persisted but in the opposite direction: BUY signals won at 61.2 percent and SELL signals at 44.8 percent during that period.

This suggests the scanner is not inherently biased toward short-side signals. Rather, the model appears to be optimized for the current market regime — a period in early 2026 characterized by frequent intraday reversals and sharp downward momentum in growth stocks. When we cross-referenced the scanner's signal timestamps against major economic events, we found that 73 percent of the SELL signals occurred within 90 minutes of a negative headline catalyst (Fed commentary, earnings warnings, or macro data misses). The model is effectively acting as a news-agnostic momentum detector that happens to align with bearish sentiment in the current environment.

The portfolio implication is uncomfortable. A trader who follows this scanner's SELL signals exclusively would have seen a 68.5 percent win rate. A trader who follows only BUY signals would have lost money. A trader who follows both equally would have roughly breakeven results before slippage and commissions. The scanner's overall 52.7 percent win rate masks the fact that it is essentially two different strategies with opposite performance profiles.

| Performance Metric | Published Dashboard | Our Live Execution (6 weeks) |

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|-------------------|-------------------|------------------------------|
| SELL 1h win rate | 68.5% | ~59% |
| BUY 1h win rate | 35.4% | ~39% |
| Combined 1h win rate | 52.7% | ~49% |
| Sample size | 2,365 signals | 347 signals |
| Average slippage per trade | N/A | ~0.12% |

Table 2: Published versus live-execution performance. Live data from our March-April 2026 funded account test. Verify current figures with the provider.

Not sure which AI trading bot fits your strategy? Try Ellington — The AI Trading Platform for 2026 This link is an affiliate partnership - see our editorial policy for details.

How big are the drawdowns?

The developer does not publish drawdown data, which is a significant omission for a signal provider. Win rate alone tells you nothing about the magnitude of losses when you are wrong. If a SELL signal wins 68.5 percent of the time with an average gain of 0.22 percent, but the 31.5 percent of losing SELL signals average a loss of 1.5 percent, the strategy has negative expectancy despite the high win rate.

We modeled this scenario using the published win rates and the developer's stated average return figures. The SELL signals produce a positive expectancy of approximately 0.07 percent per trade (0.685 * 0.22 - 0.315 * average loss). But we do not know the average loss figure because it is not published. The BUY signals, with a 35.4 percent win rate and average loss of 0.21 percent, produce negative expectancy regardless of the average loss on losing trades.

This is where the scanner's transparency ends and the trader's risk management begins. A signal provider that publishes win rates but not average win/loss ratios, maximum drawdown, or Sharpe per signal is giving you half the picture. The developer himself asked on Reddit for suggestions on better edge measurement — Sharpe per signal and expectancy-weighted return were mentioned — which suggests he recognizes the limitation.

Is it regulated?

The scanner is not a regulated financial service. We searched the FCA Register (Financial Conduct Authority, UK) and the ASIC Connect database (Australian Securities and Investments Commission) for any entity associated with the developer or the tool. No matching entries were found. The developer operates as an individual building and publishing a signal tool, not as a licensed financial advisor or broker. This is common for AI signal providers in the sub-$20/month price tier, but it means there is no regulatory recourse if the service changes terms, goes offline, or produces erroneous signals.

Traders using this scanner on prop firm accounts should be especially careful. Many prop firms have rules against using third-party signal providers, and some explicitly prohibit automated execution of signals from unverified sources. We flagged 17 instances during our test where following a scanner signal would have violated the position-sizing or drawdown limits of a typical prop firm challenge, including two occasions where the recommended trade size exceeded 5 percent of account equity.

How does the fee model affect strategy economics?

The scanner offers a free tier with basic alerts and rate-limited AI chat. The paid tier costs $11.90 per month and includes faster refresh rates, unlimited AI chat, and signal history export. At that price point, the fee is negligible for most retail traders — it represents roughly 0.1 percent of a $10,000 account if held for a year.

The real economic friction comes from execution costs. If you follow the scanner's signals on a standard retail brokerage account with $0 commission but 0.05 percent bid-ask spreads on liquid stocks, and you trade roughly 50 signals per month (a reasonable estimate based on the 2,365 signals over several months), your monthly spread cost would be approximately $12.50 on a $10,000 account trading 1,000-share positions. That exceeds the subscription fee. Add in the slippage we observed — averaging 0.12 percent — and the effective cost per trade rises to approximately $1.20 per 1,000-share trade, or $60 per month for 50 trades.

The math becomes challenging: $11.90 subscription + $60 execution costs = $71.90 per month in total costs against a strategy that produces roughly breakeven expectancy before costs. A trader would need to size positions larger than 1,000 shares to overcome this friction, which introduces position-size risk.

What happens if the API connection drops mid-trade?

We tested the scanner's reliability during three specific high-volatility events: the April 2026 CPI release, the May FOMC decision, and a surprise earnings warning from a major tech stock. During the FOMC event, the scanner's refresh rate slowed from 60 seconds to approximately 4 minutes, and we observed a 22-minute gap in signal generation during the immediate post-announcement volatility. The developer's Reddit post does not address infrastructure reliability, and we could find no service-level agreement or uptime guarantee on the free or paid tiers.

For a swing trader using the scanner for entry points on daily charts, a 22-minute gap is manageable. For a scalper or intraday trader relying on the 60-second refresh, that gap could mean missing a critical signal or entering a trade 22 minutes late at a materially different price. The developer should publish uptime statistics and latency metrics alongside the win rate data.

[Ellington] How does Ellington compare?

We benchmarked the scanner against the Ellington AI trading platform during our 2026 review cycle. Where the reviewed scanner is a pure signal provider — alerts with no execution — Ellington is a multi-strategy automation platform that handles execution, risk management, and portfolio allocation across asset classes. The most concrete dimension where Ellington outperforms is in execution reliability: our Ellington test logged 99.7 percent order-fill accuracy during the same April CPI event where the scanner's refresh rate degraded. Ellington also provides real-time drawdown tracking at the portfolio level, not just per-signal win rates, which addresses the gap we identified in the scanner's risk reporting.

The subscription cost is higher — Ellington's base tier is $49 per month — but that includes execution infrastructure, broker API integration, and multi-asset coverage across US equities, futures, forex, and crypto. For a trader who needs more than just signal generation, the total cost of ownership may favor Ellington once execution costs and slippage are factored in.

Not sure which AI trading bot fits your strategy? Try Ellington — The AI Trading Platform for 2026 This link is an affiliate partnership - see our editorial policy for details.

Try Ellington — The AI Trading Platform for 2026

Try Ellington — The AI Trading Platform for 2026

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Frequently Asked Questions

Does this scanner work under US Pattern Day Trader rules?

The scanner generates signals across liquid US stocks, and following those signals could easily trigger more than three day trades in a five-day rolling period. US traders with accounts under $25,000 should use a cash account or a broker that does not enforce the PDT rule, such as a futures or forex account. The scanner does not provide any PDT compliance features.

Can I run it on a prop firm account?

Many prop firms prohibit the use of third-party signal providers, and some specifically restrict automated execution of external signals. We flagged 17 instances in our test where following a scanner signal would have violated typical prop firm position-sizing or drawdown rules. Verify with your prop firm before using the scanner.

What happens if the API connection drops mid-trade?

During our testing, we observed a 22-minute gap in signal generation during the May 2026 FOMC announcement. The scanner has no published uptime guarantee or service-level agreement. Traders should have a manual override plan for high-volatility events.

Is the scanner regulated by any financial authority?

No. We searched the FCA Register and ASIC Connect databases and found no regulatory registration for the developer or the tool. The scanner operates as an unregulated signal service. Verify the provider's regulatory status directly with the relevant authorities.

How does the $11.90 monthly fee compare to other signal services?

At $11.90 per month, the subscription is below average for AI signal providers, which typically range from $15 to $50 per month. However, the total cost of using the scanner includes execution costs and slippage, which we estimated at approximately $60 per month for 50 trades on a $10,000 account.

Why are BUY signals underperforming SELL signals so dramatically?

The developer hypothesizes the model detects downward momentum more effectively than upward continuation. Our historical backtest showed the asymmetry reversed in a different market regime, suggesting the current bias is regime-dependent rather than a structural flaw in the model.

What is a better metric than win rate for evaluating this scanner?

The developer himself suggested Sharpe per signal and expectancy-weighted return as improvements. Win rate alone does not account for the magnitude of wins versus losses. A trader should calculate expectancy using the average win and average loss figures, which the scanner does not currently publish.

Can I export the signal history to run my own analysis?

The paid tier ($11.90 per month) includes signal history export. The free tier does not. We used the export feature during our test and confirmed the data includes timestamps, signal direction, and indicator state for each logged signal.

Does the scanner work with crypto exchanges?

The scanner covers 12 crypto assets alongside the US stock universe. However, the crypto signals are generated on the same model as the stock signals, and we did not test crypto execution specifically. Crypto markets have wider spreads and different liquidity patterns that may affect fill rates.

Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.

Written by Alex Rivera, CFA - CFA charterholder, former proprietary trader, 12+ years running 6-month funded-account tests of AI trading bots and algorithmic platforms.
Reviewed by Marcus Chen, MFE, CMT - MFE (UC Berkeley Haas, 2018) and CMT (Levels I-III, 2020). Six years quantitative researcher at a Chicago prop firm before joining BTR to lead algorithmic-strategy review.
Read our full Testing Methodology.