Trading performance metrics are the numbers that summarise a strategy's closed trades and its equity over time. Expectancy, win rate, payoff ratio and profit factor describe the average trade. Maximum drawdown and losing streaks describe the losses along the way. Sharpe and Sortino ratios relate return to variability, the Calmar ratio relates it to drawdown, and sample size shows how far to trust any of them. No single metric is enough, because each one answers a different question.
The tables below index PineConnector's trading metrics library by the question each metric answers. Each row gives the definition and formula used across the library, and links to a page with a worked example, limitations and platform details.
Notation used throughout. W = win rate and L = loss rate, as shares of closed trades. AW = average win and AL = average loss, both positive amounts in account currency. N = number of closed trades. R = initial risk per trade, from entry to the initial stop, in account currency.
Per-trade edge: does the average trade pay?
The first group describes closed-trade results. Win rate, average win and average loss are the building blocks. Payoff ratio, expectancy, average trade and profit factor each combine them into a single figure.
Scroll horizontally to read every column.
| Metric | What it measures | Formula |
|---|---|---|
| Win rate | Share of closed trades that win | W = winning trades / all closed trades (state how breakevens count) |
| Payoff ratio | Size of the average win relative to the average loss | AW / AL |
| Expectancy | Average result per trade, in currency or in R | E = (W × AW) − (L × AL) |
| What a good expectancy means | How to judge an expectancy figure when no universal threshold exists | Mean R-multiple, after all costs, over a large sample |
| Average trade | Net result per closed trade; each unit of cost per trade lowers it by that unit | Net profit / N (equals E when breakevens count as zero) |
| R-multiple | One trade's result in units of its initial risk | Trade result / initial R |
| Profit factor | Gross profit per unit of gross loss | Gross profit / |gross loss| = (W × AW) / (L × AL) |
| Break-even win rate | Win rate at which expectancy is zero, before costs | AL / (AW + AL) = 1 / (1 + payoff ratio) |
| Risk-reward ratio | Planned target distance relative to planned stop distance; says nothing about how often the target is reached | (Target − entry) / (entry − stop), for a long |
| MAE and MFE | Worst and best open result reached during each trade | Lowest and highest unrealised profit between entry and exit |
TradingView's "Percent profitable" divides winning trades by all closed trades and keeps even trades in the denominator.[1] Its "Average profit / average loss" is the payoff ratio, and its "Expected payoff" is net profit divided by closed trades.[2][3] TradingView's profit factor divides the value of winning trades by the value of losing trades.[4] Van Tharp defines R as the initial risk set by the initial stop, and expectancy as the mean R-multiple.[5]
In a TradingView-to-MT5 workflow, the initial stop that defines R can travel in the alert message as sl_pips=, sl_price= or sl_pct=. PineConnector's syntax reference calls these requested levels that the broker must still accept. A sl_pct= value is a percentage of the entry price, not a percentage of account risk.[6] For executed R-multiples, measure R from the actual entry fill and the initial stop recorded on the MT5 position. TradingView and MetaTrader can use different quotes and spreads, so both can differ from the strategy's simulated values.[23]
Risk and drawdown: how deep can the losses go?
Drawdown metrics describe the path of the equity curve, not the average trade. Risk of ruin and the Kelly fraction are estimates built on estimated inputs, and neither one is a recommendation of what fraction of an account to risk.
| Metric | What it measures | Formula |
|---|---|---|
| Maximum drawdown | Largest fall from a running balance or equity peak | Max of (running peak − equity) / running peak; a drawdown d needs d / (1 − d) to recover |
| Recovery factor | Net profit relative to the worst drawdown | Net profit / maximal drawdown (currency) |
| Losing streak probability | Chance of a run of consecutive losses | Lk for k losses in a row from a given trade |
| Risk of ruin | Chance of reaching a defined loss level | Probability that equity reaches the ruin level; usually estimated by simulation |
| Kelly criterion | Bet fraction that maximises long-run growth, if the inputs were exact | f* = W − (1 − W) / b, where b = payoff ratio |
MetaQuotes' testing report defines recovery factor as the ratio of profit to maximum drawdown, and reports balance and equity drawdown separately.[7] J. L. Kelly Jr. derived the growth-maximising bet fraction in 1956. The form above extends his even-money case, where the fraction is W − L, to a payoff ratio b.[8] A drawdown of d = 0.5 needs a gain of 0.5 / 0.5 = 100% to return to the peak.
Risk-adjusted return: was the return worth the variability?
As defined here, the Sharpe and Sortino ratios use a series of period returns, such as daily or monthly equity changes. The choice of period, riskless rate and target return all change the result. Some platform reports compute their version from per-trade results instead.
| Metric | What it measures | Formula |
|---|---|---|
| Sharpe ratio | Excess return per unit of total volatility | (Mean period return − riskless rate) / standard deviation of period returns |
| Sortino ratio | Excess return per unit of downside deviation; only below-target returns count as risk | (Mean period return − target) / downside deviation |
| Calmar ratio | Compound growth rate relative to the worst drawdown | CAGR / |maximum drawdown| |
| Volatility | Spread of period returns; the Sharpe ratio's denominator | Standard deviation of period returns |
William F. Sharpe proposed the measure in 1966 as the "reward-to-variability ratio". His 1994 paper defines the historic ratio as the average differential return divided by its standard deviation.[9] The paper also shows the ratio scaling with the square root of the number of periods when returns are serially uncorrelated. Converting a monthly ratio to a one-year basis relies on that assumption, so state it. The Sharpe ratio treats upside and downside variability alike. TradingView computes its Sortino ratio with the downside deviation of returns below a target, averaged over all returns, so gains above the target do not raise the denominator.[10] IBKR Quant credits Terry W. Young with introducing the Calmar ratio in 1991.[11]
Robustness: is the sample large enough to trust?
Every figure above is an estimate from a finite list of trades. The robustness pages ask how far that estimate could move with more trades.
| Metric | What it measures | Formula |
|---|---|---|
| Sample size | How uncertain a win rate is after N trades | SE = √(W(1 − W) / N); 95% margin ≈ 1.96 × SE |
| System Quality Number (SQN) | Mean R relative to the spread of R, scaled by sample size | √N × mean(R) / stdev(R); some versions cap N, as the SQN page explains |
For W = 0.5, the 95% margin is about 1.96 × √(0.25 / 100) = ±9.8 percentage points at N = 100, and ±4.9 points at N = 400. NIST notes that this normal approximation is the most frequently used interval, and that its lower limit can fall below zero, an impossible value for a proportion.[12] The System Quality Number is Van K. Tharp's measure.[25] Without a cap on N, the SQN formula equals the one-sample t-statistic of mean R tested against zero.[13]
Where do TradingView and MT5 report each metric?
TradingView's strategy report, formerly the Strategy Tester, shows metrics for a Pine strategy's simulated trades.[14][15] MetaTrader 5's Strategy Tester runs Expert Advisors on MT5 history data and produces its own report.[16] For field-by-field guides, read TradingView strategy tester metrics explained and the MT5 Strategy Tester report explained. The mapping below uses each platform's field names as of 25 September 2026.[17][7]
| Metric | TradingView strategy report | MT5 Strategy Tester report |
|---|---|---|
| Net profit | Net PnL | Total Net Profit |
| Win rate | Percent profitable | Profit Trades (% of total) |
| Payoff ratio | Average profit / average loss | Average profit trade and Average loss trade; divide one by the other |
| Expectancy or average trade | Expected payoff | Expected Payoff |
| Profit factor | Profit factor | Profit Factor |
| Maximum drawdown | Max drawdown, intrabar and close-to-close | Balance and Equity Drawdown: Absolute, Maximal, Relative |
| Net profit relative to drawdown | Return of max drawdown | Recovery Factor |
| Sharpe ratio | Sharpe ratio | Sharpe Ratio |
| Sortino ratio | Sortino ratio | Not among the report's listed fields |
| Calmar ratio | Not listed; CAGR and max drawdown are shown separately, so check the drawdown's percentage basis | Not among the report's listed fields |
| Losing streaks | Not a listed metric; count runs in the Trades tab | Maximum consecutive losses |
| MAE and MFE | Adverse excursion and Favorable excursion columns, Trades tab | MFE-Profits and MAE-Profits distribution diagrams |
| Largest win and loss | Largest profit and Largest loss | Largest profit trade and Largest loss trade |
| Holding time | Average bars in trades | Minimal, maximal and average position holding time |
| R-multiple, SQN, risk of ruin, Kelly fraction | Not reported; compute from the trade list, which downloads as XLSX | Not reported; compute from the deal history |
The same name can hide different conventions. TradingView's Sharpe ratio uses monthly returns and a default riskless rate of 2% a year, set by the risk_free_rate parameter.[18] MetaTrader 5's Strategy Tester sets that rate to zero.[7] TradingView's "Return of max drawdown" compares profit with the largest drop in equity, which is close to the idea behind MT5's recovery factor.[19] Check each drawdown basis before comparing the two.
Executed results are a separate record. MetaTrader 5's Trading Report is built from the current account's trading history and includes the Sharpe ratio, profit factor, recovery factor, maximum drawdown and consecutive wins and losses.[20] PineConnector Analytics shows net profit, drawdown, profit factor, win rate, reward-to-risk and expectancy for connected MT5 accounts. The published guide requires MT5 EA v3.41 or later with PineConnector Analytics enabled in the EA, and lists Analytics as not available for MT4.[21]
PineConnector's docs note that a good-looking historical chart does not confirm that live signals arrive at the same points.[22] TradingView data and the broker's MT5 feed can also differ in quotes, spreads and timestamps.[23] Some gap between simulated and executed figures is therefore normal; its size and cause are what to investigate. The backtest-to-demo verification guide walks through that reconciliation.
Why is no single metric enough?
Each metric compresses a trade list into one number, and each compression discards something. Win rate ignores the size of wins and losses. Payoff ratio ignores how often each occurs. Profit factor ignores the number of trades and their order. Expectancy ignores the spread of results and the streaks inside them. Maximum drawdown reflects one historical path.
Profit factor = (W × AW) / (L × AL) · Expectancy = (W × AW) − (L × AL)
Both formulas use the same two products. Profit factor divides them and expectancy subtracts them, so two strategies can tie on one and differ on the other.
Worked example: one profit factor, two different trade profiles
Illustrative, not a recommendation. Profiles A and B are assumed inputs, not results of any strategy. Every loss is exactly the 1R stop of 100 USD, trades are independent, and costs are ignored.
| Measure | Profile A | Profile B |
|---|---|---|
| Win rate (W) | 60% | 30% |
| Average win / average loss | 100 / 100 USD | 350 / 100 USD |
| Payoff ratio | 1.0 | 3.5 |
| Profit factor | 60 / 40 = 1.5 | 105 / 70 = 1.5 |
| Expectancy per trade | 60 − 40 = 20 USD (0.2R) | 105 − 70 = 35 USD (0.35R) |
| Break-even win rate | 100 / 200 = 50% | 100 / 450 = 22.2% |
| Five losses in a row from a given trade | 0.45 ≈ 1.0% | 0.75 ≈ 16.8% |
| 95% margin on W, if measured over 100 trades | ±9.6 points | ±9.0 points |
Profit factor ties at 1.5. Win rate ranks A first, while expectancy ranks B first: 35 USD against 20 USD per trade. B's chance of five losses in a row from a given trade is about 16 times A's (0.16807 / 0.01024 ≈ 16.4). If each win rate had been measured over 100 trades, A's lower 95% bound would be 50.4%, just above its 50% break-even rate. B's would be 21.0%, below its 22.2% break-even rate. At that sample size, the evidence that either profile clears break-even is thin, even before any uncertainty in the payoff ratio.
How to use this library
- Start with the question. Choose the group above that matches what you need to know, then read every metric in that group together.
- Pair win rate with payoff ratio. Neither figure means much alone. The break-even win rate shows where the two balance.
- Read losses as a path. Compare maximum drawdown, its duration and the longest losing streak with the loss limits in your own written plan, as the risk management hub describes.
- Check the sample. Before relying on any figure, count the closed trades and estimate the uncertainty with the sample size guide.
- Keep conventions and records apart. Compare strategies only on the same platform, period, costs and settings. Label each figure as simulated or executed.
What can trading performance metrics not tell you?
- The future. Every metric summarises past trades. PineConnector's Analytics guide states plainly that a historical average is not a promised result.[21]
- Costs that were not modelled. TradingView's strategy properties include commission and slippage settings.[24] A report run without realistic values overstates the average trade by the missing cost per trade.
- Whether settings were chosen after the fact. Picking parameters because they produce the most attractive figure on one history fits the metric to that history. The backtesting hub covers out-of-sample and walk-forward checks.
- Execution quality. A strategy report measures simulated fills. The alert condition being true, the alert triggering, webhook delivery, PineConnector processing the signal, the EA's order request, and the broker's acceptance and deal are separate stages, each with its own evidence.
Automation executes the rules it is given. A metric describes those rules' history; neither the metric nor the automation creates an edge.
Frequently asked questions
What are the key trading metrics?
The key trading metrics are win rate, payoff ratio, expectancy and profit factor for the average trade; maximum drawdown and losing streaks for losses; the Sharpe, Sortino and Calmar ratios for risk-adjusted return; and trade count for reliability. Read them together, because each summarises a different part of the same trade list and none is sufficient alone.
Which strategy performance metrics matter most?
No strategy performance metric matters most in every case, because the right metric depends on the question. Expectancy shows whether the average trade pays after costs. Maximum drawdown shows how deep losses went. Sharpe and Sortino ratios relate return to variability, and trade count shows how far to trust the other figures.
Is profit factor or expectancy more useful?
Profit factor and expectancy use the same inputs, W × AW and L × AL, but combine them differently. Profit factor divides the two, so it has no units. Expectancy subtracts them, giving an average result per trade in currency or in R. Two strategies can share a profit factor of 1.5 and still differ in expectancy.
Why do TradingView and MT5 show different Sharpe ratios?
TradingView's strategy report computes the Sharpe ratio from monthly returns, with a default riskless rate of 2% a year. MetaTrader 5's Strategy Tester sets the riskless rate to zero, and its account Trading Report uses mean profit over position holding time. Different inputs give different numbers, so compare Sharpe ratios only from the same platform and settings.
What is a good value for a trading metric?
No trading metric has a universal good value. Any figure depends on the market, costs, trade frequency, sample size and the period tested. Platform help pages sometimes print interpretation bands, but a band is a convention, not a threshold that fits every strategy. Positive expectancy after all costs, over a large sample, is the common baseline.
Reviewed 25 September 2026. Facts were checked against the linked sources on that date. Nothing in this article was tested on a trading account and no code was compiled.
Related reading
- How to backtest a trading strategy: the backtesting library
- Trading risk management: the rules that survive automation
- Trading mechanics: orders, lots, margin and costs
- Pine Script for TradingView: the complete guide
Sources
- TradingView – Percent profitable, accessed 25 September 2026.
- TradingView – Average profit / average loss, accessed 25 September 2026.
- TradingView – Expected payoff, accessed 25 September 2026.
- TradingView – Profit factor, accessed 25 September 2026.
- Van Tharp Institute – A Short Lesson on R and R-Multiples, accessed 25 September 2026.
- PineConnector – Syntax: stop loss parameters, accessed 25 September 2026.
- MetaQuotes – MetaTrader 5 Help: Testing Report, accessed 25 September 2026.
- J. L. Kelly Jr. – A New Interpretation of Information Rate (Bell System Technical Journal, 1956), accessed 25 September 2026.
- William F. Sharpe – The Sharpe Ratio (Journal of Portfolio Management, 1994), accessed 25 September 2026.
- TradingView – Sortino Ratio, accessed 25 September 2026.
- IBKR Quant – Mastering the Calmar Ratio for Risk Analysis, accessed 25 September 2026.
- NIST/SEMATECH e-Handbook of Statistical Methods – Confidence intervals (proportions), accessed 25 September 2026.
- NIST/SEMATECH e-Handbook of Statistical Methods – Confidence limits for the mean, accessed 25 September 2026.
- TradingView – Pine Script release notes, accessed 25 September 2026.
- TradingView – Pine Script v6 User Manual: Strategies, accessed 25 September 2026.
- MetaQuotes – MetaTrader 5 Help: Strategy Testing, accessed 25 September 2026.
- TradingView – Strategy report metrics, accessed 25 September 2026.
- TradingView – Sharpe Ratio, accessed 25 September 2026.
- TradingView – Return of max drawdown, accessed 25 September 2026.
- MetaQuotes – MetaTrader 5 Help: Trading Report, accessed 25 September 2026.
- PineConnector – Trading analytics: read the performance metrics, accessed 25 September 2026.
- PineConnector – Best Practices & Tips: treat backtests and repaints as separate checks, accessed 25 September 2026.
- PineConnector – Frequently asked questions: price differences, accessed 25 September 2026.
- TradingView – Strategy properties, accessed 25 September 2026.
- Van Tharp Institute – January 2021 System Quality Number Report, accessed 25 September 2026.
PineConnector executes the instructions you send it. It does not select trades, manage money, or hold funds. Trading carries risk, and past performance of any strategy does not indicate future results.
