01
Move from dashboard to evidence
Use a metric as the start of the review, then open the trades behind it. Screenshots, notes, and emotions help explain whether the change came from a strategy, behavior, or risk decision.
Analytics built from journal data
Net P&L
$12,480.00
Trade Win %
64.3%
Average Win vs Loss
$13,652
$0
$68,195
01
Use a metric as the start of the review, then open the trades behind it. Screenshots, notes, and emotions help explain whether the change came from a strategy, behavior, or risk decision.
02
Separate accounts, playbooks, symbols, and periods. Focused groups reduce the chance that unrelated trades hide the pattern you are trying to understand.
03
Win rate alone can mislead. Review profit factor, average win and loss, R-multiples, equity, and drawdown together for a more complete view of the recorded sample.
Equity & drawdown
Net P&L
$12,480.00
Trade Win %
64.3%
Average Win vs Loss
$13,652
$0
$68,195
Analytics can only explain the fields you capture, so keep prices, risk, account, setup, and context consistent.
Start with a week, month, quarter, or another sample that matches the decision you want to evaluate.
Compare symbols, setups, accounts, days, and other journal dimensions to locate the difference.
Open the underlying trades, verify the story, and create a rule or experiment for the next review cycle.
The analytics and reporting workflows include P&L, win rate, profit factor, average R, equity curves, max drawdown, streaks, and breakdowns such as symbol, setup, period, and account where supported by the recorded data.