Evidence-aware analytics
Trading performance analytics without metric overload
Start with the metrics that answer whether the observed process is profitable, repeatable and controlled, then open advanced analysis only when the sample supports it.
Review your performanceCore performance
Review realised P/L, expectancy, profit factor, win rate, valid R and drawdown with a visible sample size.
Useful segmentation
Compare the same metric by account, model, symbol, session and review period without changing its definition.
Planned versus realised
Keep plans, confirmed executions, costs and final outcomes separate so execution gaps remain measurable.
Availability and confidence
Show why a metric is unavailable or low-confidence instead of substituting a plausible-looking estimate.
Simple on the surface
The overview prioritises a compact set of performance and risk measures. Detailed distributions, execution analysis and recovery diagnostics remain available when the trader needs to investigate a specific question.
One definition in every view
Expectancy, profit factor, R and drawdown use governed definitions across dashboards, exports and reports. Filters change the sample, not the formula.
Review the metric principlesLearn the metrics before comparing them
Frequently asked questions
Which trading metrics should be reviewed first?
Start with sample size, realised P/L, expectancy, profit factor, valid R-multiples and drawdown. Advanced metrics should appear only when their evidence and sample requirements are met.
Why can R be unavailable when P/L exists?
P/L can come from a confirmed broker result, while R also requires reliable initial-risk evidence. When that evidence is missing, ATC keeps R unavailable rather than reconstructing certainty.
Do strong historical metrics predict future profits?
No. Historical analytics describe an observed sample. Market conditions, execution and trader behaviour can change, so metrics do not guarantee future results.