# The win-rate trap: 84% winners, and the biggest loss of the lot

> Same 120,643 entries, six different profit targets. As the win rate climbs from 43% to 84%, the loss after costs more than doubles. Why chasing win rate is the fastest way to lose money intraday.

- Published: 2026-10-07
- URL: https://datapointx.com/research/in/win-rate-trap/
- Tags: win-rate, risk-reward, strategy-test
- Verdict: Win rate 43% → 84% while the loss more than doubles, −₹1.98 Cr → −₹4.52 Cr.
- Source: DataPointX Research (education and research only, not investment advice)

"80% accuracy" is the most common pitch in Indian trading courses and Telegram groups. A high win rate is easy to
build: take profits quickly. Whether it makes money is a separate question, and the two are easy to confuse.

To separate them we held **everything** fixed except the profit target. The entry is a plain opening range
breakout: the first 5-minute close above (or below) the first 15 minutes' range, one trade per stock per day, a 1%
stop, ₹5 lakh per trade, every NIFTY 50 stock from January 2016 to August 2026. That gives the same 120,643 trades
every time. Only the target changes: 0.1%, 0.25%, 0.5%, 1%, 2%, or none (hold to 15:15).

## Why more winners lose more money

A 0.1% target on a ₹5 lakh trade is ₹500. The 1% stop is ₹5,000. Every winner is small and every loser is ten times
bigger. To break even you need about 91% winners **before** costs, and with ~6.5 bps (about ₹325) of costs per trade, the
₹500 winner shrinks to roughly ₹175. Tiny targets also make the trade very short (the median trade lasts about 5 minutes),
so you pay the full round-trip cost again and again for a move that is mostly noise.

As the target widens, fewer trades hit it, but each winner pays for more losers. Once the target is gone, trades
are held to 15:15 and keep the full move when the breakout follows through. That version has the lowest win rate and
the smallest loss. It still loses: this entry has very little edge to begin with (about 3 bps before costs at best),
which the [ORB guide test](/research/in/orb-strategy-guide-tested/) also found.

| Variant | Trades | Gross / trade | Win % | Net after costs | Net with +3 bps | 2016-20 | 2021-23 | 2024-26 |
|---|---:|---:|---:|---:|---:|---:|---:|---:|
| Target 0.1% | 1,20,643 | −1.0 bps | 83.9% | −₹4.52 Cr | −₹8.13 Cr | −₹2.26 Cr | −₹1.26 Cr | −₹1.00 Cr |
| Target 0.25% | 1,20,643 | −0.5 bps | 74.0% | −₹4.19 Cr | −₹7.80 Cr | −₹2.05 Cr | −₹1.18 Cr | −₹96.1 L |
| Target 0.5% | 1,20,643 | 0.2 bps | 60.5% | −₹3.78 Cr | −₹7.40 Cr | −₹1.79 Cr | −₹1.09 Cr | −₹90.2 L |
| Target 1.0% | 1,20,643 | 1.0 bps | 48.1% | −₹3.33 Cr | −₹6.95 Cr | −₹1.51 Cr | −₹93.8 L | −₹88.3 L |
| Target 2.0% | 1,20,643 | 2.4 bps | 43.6% | −₹2.49 Cr | −₹6.10 Cr | −₹93.9 L | −₹78.0 L | −₹76.6 L |
| No target (hold to 15:15) | 1,20,640 | 3.2 bps | 42.9% | −₹1.98 Cr | −₹5.59 Cr | −₹51.7 L | −₹69.8 L | −₹76.2 L |

_₹5 lakh per trade, 5-minute bars, v2026.08 snapshot (Jan 2016 – Aug 2026), NIFTY 50 point-in-time members, discount-broker (₹20/order) and statutory charges + 1 bp slippage per fill._

## What to take from this

- **Win rate alone tells you nothing about profit.** Always ask for the average win, the average loss and the cost
  per trade. Profit factor (gross wins ÷ gross losses) is a better single number: below 1.0 is a loser, whatever
  the win rate.
- **Small targets make costs dominate.** At ₹5 lakh a round trip costs about ₹325. A ₹500 target spends most of its
  profit on charges.
- **A seller quoting accuracy without these numbers is giving you the number that's easiest to inflate.**

### The exact code we ran

```python
def orb_fixed_target(target=None, stop=0.01, or_min=15):
    """First 5-minute close beyond the 15-minute opening range, stop 1%, fixed % target (None = hold to 15:15)."""
    def strategy(p):
        orh, orl = p.opening_range(or_min)
        long, short = p.close > orh, p.close < orl
        first = p.once_per_day(long | short)
        return bt.Signals(long=long & first, short=short & first, stop=stop, target=target)
    return strategy
```