This reference article explains the key performance metrics shown in MetaTrader 5 Strategy Tester reports.
It is designed to support learning and interpretation, not to act as a scoring system or pass/fail checklist.
Key point: Metrics should be read together, not in isolation, and always in the context of testing conditions, sample size, and risk assumptions.
1. Profitability Metrics
Net Profit
Total profit minus total loss over the test period. This shows the overall result of the test but does not describe risk or consistency.
Gross Profit / Gross Loss
The total of all winning trades compared to the total of all losing trades. Useful for understanding raw win/loss contribution before drawdown is considered.
Profit Factor (PF)
Gross Profit ÷ Gross Loss.
Shows how much profit is generated for each unit of loss. Often referenced as a high-level efficiency measure, but it should always be read alongside drawdown and trade count.
Expected Payoff
Average profit or loss per trade.
Calculated as Net Profit ÷ Total Trades. Helps assess whether the strategy’s edge is meaningful on a per-trade basis, not just in aggregate.
2. Risk & Drawdown Metrics
Balance drawdown
Drawdown based only on closed trades from any peak to biggest trough. Cand occur at anytime during backtest period – Expressed in % and dollars.
Equity drawdown
Drawdown including open trades – critical for potential for margin calls if there is a big difference between balance and equity DD. This is the drawdown shown in optimisation testing.
Absolute Drawdown
The difference between the initial deposit and the lowest equity point reached during the test.
Shows whether the strategy ever fell below its starting balance.
Maximal Drawdown (DD)
The largest peak-to-trough decline in equity during the test.
This is a core risk metric used to understand the worst historical drawdown behaviour under the tested conditions.
Relative Drawdown
Maximal drawdown expressed as a percentage of the highest equity reached.
Useful for comparing risk across tests with different account sizes or growth profiles.
Note: These drawdown measures describe various aspects of risk and are often reviewed together rather than individually.
3. Trade Behaviour & Quality
Total Trades
Number of completed trades in the test.
Generally, a larger sample size provides more reliable insight than a small number of trades.
Win Rate
Percentage of trades that were profitable.
This metric alone does not indicate strategy quality and should be interpreted alongside average win and average loss.
Profit / Loss Trades
The count of winning trades versus losing trades.
Provides context behind the win rate by showing the actual distribution of outcomes.
Average Win / Average Loss
Average profit of winning trades compared to the average loss of losing trades.
This relationship strongly influences whether a strategy can be profitable with a given win rate.
Risk / Reward Ratio (RR)
Average Win ÷ Average Loss.
Shows the payoff structure of the strategy rather than how often it wins.
Largest Profit / Largest Loss Trade
The biggest single winning and losing trades in the test.
Useful for identifying whether results depend heavily on outlier trades.
Maximum Consecutive Wins / Losses
Longest streaks of wins and losses.
Helps set expectations around drawdown clustering and psychological pressure during live use.
4. Stability & Robustness Metrics
Sharpe Ratio
A measure of return relative to variability in returns.
Often used to assess the smoothness of equity growth rather than raw profitability.
Recovery Factor
Net Profit ÷ Maximal Drawdown.
Shows how effectively the strategy recovered from its largest drawdown during the test period.
These metrics are commonly revisited as experience grows and as testing becomes more comparative and risk-focused.
Important Use Notes
- No single metric defines whether an EA is “good” or “bad.”
- Profit metrics without drawdown context are incomplete.
- Win rate should always be interpreted alongside average win and average loss.
- Strategy Tester results describe historical test behaviour under specific conditions, not future performance.
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Final thoughts:
Knowing what your numbers mean and what are acceptable and ideal levels is critical at all stages of EA deployment, whether that be from test to live or LIVE to scaling position size (YES! You should always start on low trading volume). It is you who sets the minimum standard for each of these stages and when you may progress from one stage to another. Pre-plan these, and as we know from any type of trading, planned interventions that are reliably followed are far better in terms of both system evaluation and refinement than using the “force” or some other supernatural power on which to make decisions.
