Copy Trading Results 2026: Real P&L Data From 2,753 Verified Trades
90-day performance data from 11 professional traders. Every trade recorded directly from Bybit exchange execution. No simulations. No paper trading. No cherry-picked results.
Why This Data Matters
Most copy trading platforms publish win rates without context. They show you "85% win rate" but hide the sample size, the leverage, the drawdown periods, and the losing trades. That makes it impossible to evaluate whether their traders are actually profitable or just got lucky over 20 trades.
This page publishes every metric that matters for evaluating copy trading performance: win rates with sample sizes, worst-case losses, take-profit distribution, risk-reward ratios, and per-trader breakdowns. The data updates from the same API that powers our live results dashboard. You can verify every number yourself.
Per-Trader Performance Breakdown
Each trader on AO Trading operates independently with their own strategy, risk profile, and trading schedule. Below is the full breakdown for Q1 2026 (last 90 days).
Haseeb
Human TraderStrategy: Short-biased momentum trader. 100% short positions in this period. Focuses on altcoin volatility with a structured take-profit ladder. TP1 hit rate: 83.65%. Uses DCA on 18.25% of trades.
TP distribution: TP1 hit on 83.65% of trades, TP2 on 37.30%, TP3 on 22.38%, TP4 on 9.68%, TP5 on 2.22%. Average 1.55 take-profits hit per winning trade.
Most traded: RIVER (13), POWER (13), LYN (12), BULLA (12), FHE (12).
AO Crusher
AlgorithmStrategy: Fully automated short-biased algorithm. Runs 24/7 with no human intervention. Uses breakeven management aggressively (260 breakeven exits in 90 days). 15 open positions at time of writing, with $6,173 in open unrealized profit.
TP distribution: TP1 hit on 78.21%, TP2 on 54.47%, TP3 on 28.49%, TP4 on 2.51%. Average 1.64 take-profits per winning trade.
Most traded: SIREN (23), RIVER (16), LYN (14), ARC (14), BTR (13).
Andre Outberg
FounderStrategy: AO Trading founder. Short-biased with extremely selective entry criteria. Only 4 losing trades in 232 positions this period (1.79% loss rate). Uses DCA on 11.21% of trades. TP1 hit rate: 94.40%.
TP distribution: TP1 hit on 94.40%, TP2 on 54.31%, TP3 on 29.74%, TP4 on 0.86%. Average 1.79 take-profits per winning trade.
Most traded: BTR (6), SIREN (5), ZBT (5), SLP (4), APR (3).
Recent trades (last 10): 100% win rate. BTRUSDT +131.32%, APRUSDT +33.21%, PIPPINUSDT +38.16%, RIVERUSDT +70.16%, XAN +75.00%, GIGGLE +25.36%, TRUMP +68.57%, BANANA +340.78%, GODS +87.91%, ANIME +33.61%.
Ryaan
Human TraderStrategy: High-volume trader taking both long and short positions (524 longs, 31 shorts). Highest risk-reward ratio on the team at 2.82, meaning winning trades average 2.82x the size of losing trades. Lower win rate offset by significantly larger average wins (+130.54%) vs average losses (-46.32%).
TP distribution: TP1 hit on 61.80%, TP2 on 20.90%, TP3 on 9.37%, TP4 on 4.32%, TP5 on 1.26%.
Most traded: RIVER (39), MYX (22), LYN (17), XNY (12), HUMA (11).
Aggregate Trade Analysis
Win Rate Distribution
The 73.74% aggregate win rate across 2,753 trades is built on 2,030 winning trades and 437 losses. Individual win rates range from 64.62% (Ryaan, highest volume) to 98.21% (Andre Outberg, most selective). The AO Crusher algorithm sits at 78.21% with 260 additional breakeven exits that protect capital.
| Trader | Trades | Win Rate | Wins | Losses | R:R Ratio | Cum. P&L |
|---|---|---|---|---|---|---|
| Haseeb | 630 | 89.02% | 527 | 65 | 1.01 | 40,534% |
| AO Crusher Algo | 552 | 78.21% | 280 | 68 | 2.16 | 39,566% |
| Ryaan | 555 | 64.62% | 358 | 193 | 2.82 | 37,794% |
| Andre Outberg | 232 | 98.21% | 219 | 4 | 0.87 | 23,389% |
| Group Total | 2,753 | 73.74% | 2,030 | 437 | - | $184,124 |
Risk and Drawdown Data
Transparency means publishing the bad trades alongside the good ones. Here is the worst-case data from each trader on the platform. These numbers represent the maximum single-trade loss observed in the 90-day window, using leveraged P&L (a -100% leveraged loss means the position lost the equivalent of the initial margin).
| Trader | Worst Single Trade | Avg Loss | Loss Rate | Avg Win |
|---|---|---|---|---|
| Haseeb | -330.31% | -87.12% | 10.98% | +87.66% |
| AO Crusher | -148.23% | -73.53% | 18.99% | +159.16% |
| Ryaan | -177.72% | -46.32% | 34.84% | +130.54% |
| Andre Outberg | -124.95% | -124.95% | 1.79% | +109.09% |
Key observation: Ryaan has the highest loss rate at 34.84% but compensates with the best risk-reward ratio (2.82). His average winning trade (+130.54%) is 2.82 times larger than his average loss (-46.32%). Meanwhile, Andre Outberg takes the opposite approach: extremely selective entries with only a 1.79% loss rate but a lower R:R ratio (0.87). Both strategies are profitable. The difference is in style, not outcome.
Take-Profit Ladder Performance
AO Trading uses a structured take-profit system with up to 5 targets (TP1 through TP5). When a trade is entered, partial profit is secured at each target level. This data shows how often each TP level is reached across all traders:
| Trader | TP1 Rate | TP2 Rate | TP3 Rate | TP4 Rate | TP5 Rate | Avg TPs/Win |
|---|---|---|---|---|---|---|
| Haseeb | 83.65% | 37.30% | 22.38% | 9.68% | 2.22% | 1.55 |
| AO Crusher | 78.21% | 54.47% | 28.49% | 2.51% | 0% | 1.64 |
| Ryaan | 61.80% | 20.90% | 9.37% | 4.32% | 1.26% | 0.98 |
| Andre Outberg | 94.40% | 54.31% | 29.74% | 0.86% | 0% | 1.79 |
Andre Outberg's 94.40% TP1 hit rate is the highest on the platform. When he enters a trade, 94 out of 100 times the position reaches the first profit target. This precision is why his win rate sits at 98.21% despite running a lower risk-reward ratio.
What These Numbers Mean for Copy Traders
If you copy a trader on AO Trading through AO Shadow, your results will differ from theirs. The gap comes from three factors:
Entry Slippage
Your entry price will differ from the signal trader's by 1-5 ticks depending on market liquidity and your copy delay. On a 25x leveraged position, 3 ticks of slippage at entry equals roughly 0.15-0.75% of P&L difference per trade. Over 500 trades, this compounds. AO Shadow's execution is sub-200ms via Bybit API, which minimizes but does not eliminate this gap.
Position Sizing
Your account size determines your position size. A trader running $10,000 on 25x leverage opens a $250,000 notional position. If you have $1,000, your position is $25,000 notional. The percentage returns should be similar, but the dollar P&L will scale linearly with your capital. There is no minimum account size, but smaller accounts experience more rounding on partial take-profits.
Drawdown Timing
If you start copying a trader during their worst week, your first experience will be losses even though the trader is profitable over 90 days. Ryaan's worst drawdown period included 6 consecutive stop-loss hits (recent 10 trades showed 40% win rate vs his 64.62% average). Timing your start date does not eliminate this risk. The only mitigation is copying over a long enough period to capture the full distribution.
How This Data Is Collected and Verified
Every trade on AO Trading is recorded through direct Bybit exchange API integration. When a trader opens a position, the entry price, leverage, direction, and timestamp are logged. When the position closes (via take-profit, stop-loss, manual exit, or DCA adjustment), the exit data is recorded automatically.
There is no manual data entry. There is no way for traders to delete losing trades or modify historical results. The same data that appears on this page feeds the live results dashboard, which updates in real time. You can audit any trader's full history on that dashboard at any time.
Trade classification (win, loss, breakeven) is determined by the close reason recorded by the system. A "Profit secured at TP1" close means the trade reached the first take-profit target. A "Stop Loss Hit" means the trade was closed at a loss. "Breakeven Hit" means the position was closed at the entry price after the stop-loss was moved to breakeven. All classifications are system-generated, not trader-reported.
How This Compares to Industry Benchmarks
The typical crypto copy trading platform does not publish aggregate performance data. When they do, sample sizes are small (under 100 trades) and drawdown data is absent. Here is how AO Trading's verified data compares to publicly available industry claims:
| Metric | AO Trading (verified) | Industry Average (claimed) |
|---|---|---|
| Sample size | 2,753 trades | 50-200 trades |
| Win rate | 73.74% | 60-80% (often unverified) |
| Drawdown disclosed | Yes, per-trade | Rarely |
| Data source | Exchange API (Bybit) | Self-reported or simulated |
| Full trade history | Public dashboard | Usually locked or limited |
| Losing trades visible | Every single one | Sometimes hidden |
For a deeper comparison of copy trading platforms, see our Best Crypto Copy Trading Platforms analysis. For an explanation of how copy trading works mechanically, read What Is Copy Trading Crypto?
Verify These Results Yourself
Every number on this page comes from the same API that powers the live dashboard. You can audit any trader's full history, including every losing trade, right now.