What is Strategy Scorecard?
A strategy scorecard is a one-page summary of the core performance metrics for a specific trading strategy — including win rate, expectancy, profit factor, max drawdown, average R-multiple, and sample count. It enables side-by-side comparison of multiple strategies and quick identification of which deserve more capital allocation.
Indian market context (NSE)
Reference levels: Nifty 50 at 24,300, Reliance Industries at ₹1,300, Bank Nifty futures at 55,000 (lot size 30). Examples below show how Strategy Scorecard shows up on Indian index, equity, and futures books — update to live quotes in your journal.
Nifty 50 perspective
Strategy Scorecard in Indian context at Nifty 24,300: apply SEBI/regulatory framing where relevant and tag index trades separately in weekly review.
Reliance Industries perspective
Strategy Scorecard using Reliance at ₹1,300 as a liquid large-cap example — adjust numbers to your live quote and contract note.
Bank Nifty futures perspective
Strategy Scorecard with Bank Nifty futures at 55,000 — respect lot size 30 and quarterly vs monthly contract rules on NSE.
How to validate
- Minimum sample: 30 closed trades on one strategy tag before trusting Strategy Scorecard.
- Check for one outlier week inflating Strategy Scorecard — export largest winners and losers.
- Recompute Strategy Scorecard after including brokerage, STT, and slippage on F&O tags.
- Compare Strategy Scorecard on the same date range as profit factor and max drawdown.
How to track in TradeLyser
- Open Strategy Board or analytics → filter by strategy tag and review period.
- Locate the widget or column reporting Strategy Scorecard (or export trades to compute manually).
- Store snapshot values in weekly review: Strategy Scorecard, profit factor, drawdown, trade count.
- If Strategy Scorecard is custom, add a spreadsheet column fed from TradeLyser CSV export.
Best practices
- Publish Strategy Scorecard per strategy, not only at account level.
- Use the same calculation window (weekly vs monthly) year-round.
- Pair Strategy Scorecard with sample size in every review slide or note.
- Reconcile Strategy Scorecard with broker statements before tax filing.
Common pitfalls
- Changing rules after fewer than 20 trades because Strategy Scorecard moved slightly.
- Mixing intraday and positional tags when computing Strategy Scorecard.
- Ignoring costs so Strategy Scorecard looks better than banked P&L.
- Letting one outlier trade dominate the Strategy Scorecard reading.
Reference guide
| Context | Value | Reading |
|---|---|---|
| Update frequency | Updated monthly with the latest trade batch | Reviewed only when a strategy is losing — confirmation bias in reviews |
Related terms
Blue chip stocks are large, established companies with steady liquidity — Reliance, HDFC Bank types.
An edge audit is a structured review — typically monthly or quarterly — in which a trader examines the expectancy, win rate, and profit factor for each setup tag and strategy in their journal to confirm that a statistical edge is present, stable, or improving. It also identifies setups that have degraded and should be paused.
Expectancy answers whether your edge pays each time you repeat the setup. Positive expectancy means the system earns over many trades; negative expectancy means it bleeds even with a high win rate.
Profit factor summarises whether total winning rupees outweigh total losing rupees over a window. Below 1.0 means net losing; above 1.0 means net winning before you judge consistency.
A setup tag is a user-defined label attached to each trade in a journal to identify the specific entry pattern or strategy used — for example, "VWAP Rejection", "Flag Breakout", or "OI Reversal". Consistent tagging allows traders to isolate the win rate, expectancy, and R-multiple for each distinct setup.
By trader level
Level up — system optimisation
Already journaling? Use these metrics to measure your edge, manage risk, and evolve your system.
FAQ
Does TradeLyser have a built-in strategy scorecard?
Yes — TradeLyser's Strategy Board shows a scorecard for each strategy you define: win rate, average R, expectancy, max drawdown, and profit factor, filterable by any date range. You can pin your top strategies to the dashboard for quick review.
How do I decide which strategies to focus on using a scorecard?
Rank strategies by expectancy and filter to those with 30+ trades. Any strategy with negative expectancy after 50+ trades should be paused or refined. Any strategy with expectancy above 0.3R and 50%+ win rate deserves increased allocation. Use the scorecard as an objective capital allocation tool, not a gut-feel exercise.
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