Weekly review metrics that say more than win rate
Posted: Sat Oct 31, 2026 8:43 am
Win rate is the least informative number in a scalper's week. A 70 percent hit rate with small winners and occasional large losers can be worse than 45 percent with tidy risk. Three metrics are worth the effort instead.
First, average all-in cost per trade: spread, commission and slippage, in pips. Compare it to the average gross winner. If cost is eating 35 percent or more of the average win, the edge is thinner than the equity curve suggests.
Second, expectancy per trade after costs, expressed in R, and broken out by session. A strategy that is positive overall can easily be negative in one session that drags the rest down.
Third, MAE and MFE, meaning how far each trade went against you and how far it went in favour before closing. Two readings are especially useful. If winners almost never go more than 1 pip against the entry, the stop can probably be tighter. If losers regularly reached half the target before reversing, the target is likely too ambitious or the exit rules are missing a partial.
Spreadsheet formulas are enough for all of it, no special software needed.
Do you pull MAE and MFE by hand or with a script, and what did the first month of data reveal?
First, average all-in cost per trade: spread, commission and slippage, in pips. Compare it to the average gross winner. If cost is eating 35 percent or more of the average win, the edge is thinner than the equity curve suggests.
Second, expectancy per trade after costs, expressed in R, and broken out by session. A strategy that is positive overall can easily be negative in one session that drags the rest down.
Third, MAE and MFE, meaning how far each trade went against you and how far it went in favour before closing. Two readings are especially useful. If winners almost never go more than 1 pip against the entry, the stop can probably be tighter. If losers regularly reached half the target before reversing, the target is likely too ambitious or the exit rules are missing a partial.
Spreadsheet formulas are enough for all of it, no special software needed.
Do you pull MAE and MFE by hand or with a script, and what did the first month of data reveal?