The long versus short split is the check people reach for when they want to know whether they can trade or whether they just owned things while things went up. It is the right question. It is also the check most likely to produce a confident wrong answer, because the short side of almost every retail book is too thin to say anything, and a thin row does not look thin. It looks like a number.
Before going further, a note on what I can and cannot see. The capture of the Performance tab I am working from shows the view controls and the summary tiles at the top of the page. I cannot see a two row long and short bucket in it, so I am not going to tell you where that control sits or what it is labelled on your screen. What follows is the reasoning and the arithmetic, which apply to any side by side comparison of your long and short records, wherever your platform puts it.
Start with what the whole book says
Splitting a record is only worth doing if the aggregate is ambiguous. Look at the tiles in the screenshot below. On that account the view is set to ALL ACCOUNTS (REAL), source filter ALL, all accounts cumulative, period 1Y, and it returns 87 total trades, a win rate of 25.29%, a profit factor of 0.08, expectancy of negative 1.20% and a max drawdown of negative 91.31%.
That aggregate is not ambiguous. A profit factor below one means gross losses exceeded gross wins, and 0.08 is not marginally below one. Expectancy of negative 1.20% per trade means the average trade cost money. When the whole book reads like that, splitting it into long and short is a way of hunting for the half that works, and hunting for the half that works in a sample of 87 is how people end up trading a subset that was never distinguishable from noise. The honest first move on a book like that is to reduce size until the process is fixed, not to find a bucket to keep.
The arithmetic that empties the short row
Take that 87 and split it the way most books actually split. Retail records skew long heavily, and eight to two is a generous estimate for someone who shorts occasionally. That leaves about seventy long trades and about seventeen short ones.
Now ask what a win rate calculated on seventeen trades is worth. The uncertainty on a proportion is the square root of p times one minus p, divided by n. Put p at a quarter, close to the win rate on the tiles, and n at seventeen. That is the square root of 0.1875 divided by 17, which is about 0.105. So one standard error on that short row is roughly ten and a half percentage points, and the usual two standard error band is about plus or minus twenty one points.
Read that back slowly. A short bucket showing 25% is consistent with an underlying process that wins 4% of the time and one that wins 46% of the time. Those are two completely different traders. The row cannot separate them, and no amount of squinting at it will. If your short count is under twenty, the correct interpretation of that row is that you have not yet run the experiment.
The same arithmetic applies to the long side, just less brutally. At seventy trades the standard error near a quarter is about five points, so a two standard error band is around ten points wide. That is readable, barely, for a large difference. It is useless for a small one.
Direction and regime arrive tangled together
Even when both rows have enough trades, the split does not cleanly answer the question you asked. You wanted to know whether your edge is directional or whether it was a rising market. The long and short buckets do not isolate that, because of when the trades happened.
Short trades are not scattered evenly through time. People short when things look weak, which means the short bucket is concentrated in drawdowns, corrections and choppy periods. The long bucket is concentrated in everything else. So a comparison of the two rows is partly a comparison of direction and partly a comparison of two different market environments, with no way to tell from the rows themselves how much of each you are looking at.
That confound cuts both ways, which is what makes it dangerous. A weak short row might mean you cannot short. It might equally mean you short at the wrong moments, or that your shorts happen to sit in the two violent squeezes that occurred in the period. Same row, three explanations, and the difference between them decides whether you should stop shorting or fix your timing.
Slice by period instead, at least once
There is a cheaper test for the bull market question, and the period buttons visible in the screenshot are what you use. They run 1D, 7D, 14D, 1M, 3M, 1Y, ALL and CUSTOM. The CUSTOM option is the one that matters here.
Pick two stretches of the past year you can characterise from memory or from a chart. One where the market you mostly trade went up, one where it went sideways or down. Set the custom period to the first, write down what the tiles say. Set it to the second, write down what they say. You are now comparing your own process across two environments rather than comparing two directions with the environments baked in.
If the numbers hold up roughly across both stretches, your process is doing something that is not purely a function of the tape. If the good period carries everything, you have your answer, and you did not need a short bucket to get it. The catch is the same as before. Slicing 87 trades into two periods leaves you with two small samples again, so treat this as directional evidence and not as a measurement.
How many trades the comparison really needs
It is worth knowing the target so you can stop asking the question early. Suppose you want to detect a ten percentage point difference between your long win rate and your short win rate, which is a large real difference. The uncertainty on the gap between two proportions is roughly the square root of two times p times one minus p, divided by n per side. At p near 0.4, that inner product is 0.24. Setting a two standard error band equal to 0.10 gives 0.05 equal to the square root of 0.48 divided by n, which solves to n of about 192.
So you need on the order of two hundred trades per side, four hundred in total, before a ten point gap between the two rows is something you should act on. Smaller gaps need far more. Most retail books never get there on the short side, and that is not a failure. It just means the long versus short split is permanently a low resolution instrument for you, and you should stop treating its output as a verdict.
What the split is still good for is spotting structural differences rather than skill differences. Look at the short trades as a group and ask whether they are held for a different length of time, sized differently, taken on different instruments, or run at different leverage than the longs. Those differences are visible in a handful of trades because they are properties of how you trade rather than estimates of how well. If your shorts are twice the size and a third of the holding period of your longs, you have found something actionable in seventeen trades, and it was never the win rate that told you.