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0.1 pip average slip sounds tiny until you multiply.

On 100 EURUSD tickets, 0.1 pip average against you is 10 pips of pure cost before commission. At my average winner size that can be a meaningful fraction of monthly expectancy. I estimate slip from the deals tab by comparing the price I requested to the fill where I can, imperfectly, then track a rolling median rather than one horror story.

Quick maths for a standard lot: 10 pips is roughly 100 USD per 100 trades. If you take 400 tickets a month, that is 400 USD a month disappearing without anyone noticing. Now put that next to your commission line and the picture changes. For someone making 2 pips a trade on average, a 0.1 pip slip is a five percent haircut on gross edge.

The point is not precision to the third decimal. It is refusing to ignore a leak because each drop looks small. Cost in R terms belongs on the same sheet as win rate.

Has anyone here measured their own average slip over a few hundred trades? Curious how far people are from zero.

I'd question the rolling median, though. For cost purposes the mean is what you actually pay, and slippage is exactly the kind of number where the two drift apart.

Picture 100 trades where 90 fill at the requested price, 8 slip half a pip, and 2 stop-outs into a data release slip 3 pips each. The median is zero, which looks perfect, but the total is 10 pips, the same 0.1 pip average as your example.

I sketched how that looks against a smooth 0.1 pip per trade in the attached illustration. Same end point, completely different shape, and the steps are where the money goes.
That's why I split my slippage log by order type. On market entries mine is small and fairly even, while stop orders carry most of the damage, and a median across both mostly hides the stop side. It also changes the fix, because if the cost sits in a handful of stop-outs, cutting exposure into scheduled releases does more than shaving a tenth of a pip off every entry.

Do you count positive slippage against the negative, or log it separately? I net it in the total but keep it in its own column, because a feed that only ever slips one way is worth knowing about.

LondonScalper, the other split that changed my number was by session, not only by order type. London hours on my EURUSD book average about 0.06 pips of adverse slip, while the New York afternoon stretch sits near 0.18, and almost all of the horror fills live in that second bucket.

Once I cut that out, the 0.1 pip headline looks like a blend of a clean morning and a messy late day. The fix was a hard stop on new market entries after 15:00 London, which dropped my rolling mean from 0.11 to 0.07 over the next 200 tickets.

On positive slip I now keep a separate policy. Positive fills net into the total cost line, but if positive slip is under 10% of adverse slip over a month, I flag the feed for a path check rather than celebrating the rebate.

That ratio caught one account where stops slipped out and limits almost never slipped in. Have you measured slip by London versus New York on your book, or does it stay flat across the day?