Trade Analysis Software: 60+ Analytics Views That Show Why You Win and Lose
Trading performance analysis goes beyond a P&L chart. This trade analysis software gives you 60+ views of your trading statistics, including Mistake Cost Analysis, Trader DNA profiling, a 0–100 Edge Score, Trading Seasons trend tracking and session performance, all calculated from the trades you log. Updated 5 October 2026.
Trading Performance Analysis: What Trading Statistics Actually Mean
Most trading journals offer a P&L chart and a win rate. That tells you what happened, not why. The Trading Terminal's analytics layer is built around a different question: which specific conditions make you profitable, and which ones have the weakest results? With 60+ views across 16 configurable modules, every trade you log feeds a growing dataset that answers that question precisely — by setup, by session, by mistake, by confluence and by instrument.
All 60+ views are available from Pro (A$19/mo) or Elite (A$29/mo). The free plan includes the dashboard — equity curve, P&L calendar, win rate and profit factor.
Core Analytics Modules
Mistake Cost Analysis
Adds up the net P&L of trades tagged with each mistake and ranks the most expensive habits first. 12 mistake categories built in.
Trader DNA
Performance sliced by instrument, session, setup, direction, timeframe, grade, day of week and confluences. 9 dimensions in one view.
Edge Score
Composite 0–100 gauge from 6 weighted signals. One number that shows if your edge is improving or degrading over time.
Trading Seasons
Tracks performance trends over rolling periods — identifying hot and cold patches so you can see hot and cold patches.
What the 60+ Analytics Actually Analyse
Every one of the 60+ views is calculated directly from the trades you log — entry, exit, size, setup tags, confluences, session, emotion and discipline ratings. Nothing is pulled from the market or from other users' data. The analytics layer takes that raw trade history and organises it into eight categories, so instead of one P&L number you get a breakdown of exactly where that number came from:
- Performance — total trades, net P&L, max drawdown, profit factor, expectancy, best/worst trade, long/short ratio
- Setups — win rate and P&L ranked by each tagged setup, so you see which patterns you trade actually work
- Sessions — P&L, win rate and expectancy split by London, New York, the overlap and Asia
- Instruments — performance broken down per symbol, so a strong overall number can't hide a losing instrument
- Confluences — win rate and P&L for each confluence tag, alone and in combination with others
- Risk — R-multiple distribution, risk per trade, payoff ratio, fees and slippage impact
- Behaviour — emotion and discipline trends, overtrading detection, revenge-trade flagging, win/loss streaks
- Execution & time — holding time vs P&L, day-of-week and month-of-year patterns, consecutive-outcome runs
How Edge Score, Trader DNA & Mistake Cost Analysis Work
These three modules go beyond a single chart — they combine multiple categories above into one readout. Here's exactly what each one measures and, just as importantly, what it doesn't claim to do.
Edge Score
A composite 0–100 gauge built from six weighted signals in your historical trades: win rate, risk-reward consistency, expectancy, drawdown control, rule adherence and session discipline. It summarises how consistent your past performance has been — it is not a forecast, a signal, or a prediction of future results, and it can't account for trades you haven't taken yet.
Trader DNA
Slices your closed trades across nine dimensions at once — instrument, session, setup, direction, timeframe, grade, day of week, market conditions and confluences — to surface which combinations of conditions your data shows as your strongest and weakest, rather than any single metric in isolation.
Mistake Cost Analysis
Every trade where you tag a mistake (moved stop, oversized, revenge trade, etc.) is added up into a dollar total for that mistake type, using your own logged entry/exit/size data. It quantifies the historical cost of habits you've already tagged — it doesn't detect mistakes automatically or judge trades you haven't labelled.
Trading Seasons
Tracks how your Edge Score and expectancy have moved over rolling historical periods, so you can see whether your results are trending up, flat or down — a look backwards at your own trend, not a forecast of what comes next.
Win Rate Is Not Enough on Its Own
Win rate is the easiest metric to track (wins divided by graded trades) and the easiest to misread in isolation. A 70% win rate sounds strong until the average win is 0.5R and the average loss is 1R, which loses money over many trades. A 40% win rate sounds weak until the average win is 2.5R and losses are clean 1R stop-outs, which has a positive expectancy. The metrics that carry more information are expectancy, profit factor and the shape of your R-multiple distribution. Win rate feeds into expectancy but is not the whole story.
A Worked Expectancy Example
In R terms, expectancy = (win rate × average winning R) − (loss rate × average losing R). If you win 45% of trades, your average winner is 2.2R and your average loser is 1R:
(0.45 × 2.2) − (0.55 × 1.0) = 0.99 − 0.55 = +0.44R per trade
That is an illustration of the arithmetic, not a forecast: the same figure would mean an average of 0.44 times your risk per trade across that set of trades. Expectancy is only as steady as the sample behind it, so it is worth looking at whether it stays positive across different sessions, setups and market conditions. The full definitions are on how we calculate.
R-Multiple Distribution: What the Shape Can Show
An R-multiple is a trade's result in units of the risk you took: a trade that wins twice its risk is +2R, a full stop-out is about −1R. Plotting every trade this way shows the shape of your results. Patterns that can show up, and what they may indicate:
- Losses at −1.5R, −2R or −3R can mean stops were moved or losing positions were added to, which is a process question rather than a strategy question.
- Winners clustered near +0.5R when the plan targets 2R can mean profits are being taken early.
- Lots of −1R and lots of +3R with little in between can mean a binary strategy is being run consistently, or that break-even trades are being closed early.
- Winners and losers both clustered near zero can point to low-conviction entries or setups with a poor reward-to-risk.
These are readings of your own data, not instructions. Your logged R values come from the stop and target you enter on each trade.
Session Performance: Finding the Pattern in Your Own Data
Many traders have a home session where they are most alert, but few know from data which session it is. Session performance shows P&L, win rate and expectancy by London open, New York open, the London/New York overlap and Asia. For many forex traders the data shows either that most results come from one session, or that all sessions are traded but one has noticeably better expectancy. What to do with that is each trader's decision; the analytics only show where the results sit.
Analytics Quality Depends on Your Data
Every view on this page is a mirror of what you've logged — it can only find patterns that exist in your trade history, and it can't correct for trades that were mis-tagged or never logged. Two things worth knowing before you act on any single chart:
- Small samples are noisy. A setup or session with 5–10 trades can show a misleadingly high or low win rate purely by chance. Treat breakdowns under roughly 20–30 trades as directional, not conclusive, and let the sample grow before making sizing decisions off it.
- Consistent tagging matters. Setup, confluence and mistake tags are only as useful as they are consistent — if "FVG" means something different from one trade to the next, the analytics for that tag will blend two different things together.
The kinds of insights your own data can surface
Illustrative examples only — these are hypothetical scenarios showing how the analytics work, not results from a real account.
Session Performance
A trader logs 40 London-session trades and 25 Asia-session trades. Session Performance shows a 68% win rate in London against 41% in Asia — surfacing that Asia trades have been dragging down the overall result.
Mistake Cost Analysis
12 trades tagged "moved stop loss" have a combined net P&L of -$1,840 once totalled — turning a vague habit into a specific figure ranked against every other tagged mistake.
Trader DNA
A trader is profitable on long setups (+0.6R expectancy) but slightly negative on shorts (−0.1R) in the same instrument — a split that's invisible in a single win-rate number but immediate in a Trader DNA breakdown.
A performance platform, not a prediction engine
- A trade journal and performance-analytics platform
- A way to see your own historical results by setup, session, instrument and confluence
- A tool for finding and quantifying habits already in your trade history
- A signal service or trade-alert provider
- A prediction engine — Edge Score and every other view describe the past, not the future
- A guarantee of profitability — trading carries risk and past results don't ensure future ones
Curious how the numbers are worked out? Read how we calculate Edge Score, Process Score, expectancy, profit factor, max drawdown and the Risk Desk budget.