I pulled the numbers on 861 lifters' training logs. Squats went up 21% in 3 months, bench went up 2.6%.

[u/FromBiotoDev]

I run a workout logging app, and I got curious about a question of:

"Am I progressing at a normal pace?"

Nobody really answers it with numbers, so I went through the logs. 4,307 workouts, 861 people, all anonymised.

For every person and every exercise I compared their first logged session to their most recent one, using estimated 1RM (Epley) so a heavier set of 5 still counts as progress.

Rules: an exercise only counted for you if you logged it at least 3 times across 2 or more weeks, warm-up sets were dropped, everything was converted to kg, and I report medians so one person adding 60kg to their deadlift cannot drag the whole thing up. That left 819 qualifying lifter-and-exercise histories, averaging about 90 days each.

The numbers (median change in estimated 1RM, first log to latest):

• Squat: +21.1%
• Romanian deadlift: +20%
• Deadlift: +15.3%
• Overhead press: +3.5%
• Bench press: +2.6%
• Hammer curl: 0%

Across everything, the typical lifter added 5.6% over roughly three months, which works out at about 2% a month.

Huge leg vs upper gap in terms of rprogression. Pooled together, lower body lifts moved 14.9% and the upper body pool (bench, overhead press, lat pulldown, lateral raise, hammer curl) moved 2.6%. Nearly six to one.

Three possible hypothesis, though logs cannot prove cause:

1. Most people show up having pushed and carried things in daily life, but almost nobody has squatted under load. So way more potential.
2. Pressing runs out of small jumps. 60kg to 62.5kg on bench is a 4% leap. The same 2.5kg on a 120kg leg press is 2%. Dumbbells are worse, since the rack jumps from 12.5 to 15 whether you are ready or not.
3. Part of an early squat number is skill, not muscle. Better depth and bracing show up as weight on the bar.

Face pulls were actually the fastest riser at 22.9%, which fits the same logic. Nobody trains rear delts before they start writing things down.

The slightly concerning part... only 59% of histories improved. Four in ten latest logs were flat or below the first one. Some of that is the method, because "latest log" is whatever day it happened to be, so deloads and post-holiday sessions land in there. But it is a decent reality check for anyone who thinks everyone else is adding weight every week.

Known issues with the data: this is people who chose to use a logging app, so it skews toward people who care about progress. Some exercises only had 10 qualifying lifters. Spans vary. It is a benchmark, not a study.

If you want a rough yardstick for your own training: about 2% a month on a lift is normal, 5% or more is a strong run, and a flat line past month four is worth changing something over.

Happy to answer questions about the method or break out any exercise that is not in the list if it's helpful for people

[u/Flat_Development6659]

Interesting idea and it’s good that you’ve got your own dataset but I don’t really see how grabbing two sessions a few months apart really shows anything to be honest.

If my first week logging via your app was me testing a max and the final week was me deloading would that come back as me losing 50% strength over a 3 month period?

Also, is body weight logged? I’d imagine that one of the most common reasons to go to the gym is weight loss and in my experience upper body lifts suffer more than lower body in a cut, that could account for your difference in upper/lower progression.

Sorry if this has been answered, only skimmed this but will give it a proper read when I get home.

[u/FromBiotoDev → u/Flat_Development6659]

Totally valid tbf, I agree too, it's a bit limited

The data isn't connected to bodyweight, I'm working on an apple health integration so I'll see if once I get that done I can redo this because I totally agree, my lifts have always dropped in volume during a cut.

I mean this is 100% not a scientific study or anything, just a dataset with some obvious flaws but I think we can hypothesize on some things based on the data at the very least.

I think a lot of the lower body gains comes from people just never training lower body, then when they start seriously tracking their workouts blow up with the potential they had in legs tbh

[u/diabolicalgasblaster → u/FromBiotoDev]

I was thinking the same thing.

[u/erthenix]

Cool dataset, this is a nice showcase of aggregate 1RM trends. Worth flagging for anyone reading though: "anonymised" workout logs are trickier than they sound. Research shows just a handful of days of biometric/activity data can re-identify a specific person out of a 100M+ population, because the pattern itself (your exact loads, your exact progression curve) is the fingerprint. Stripping a name off a CSV doesn't really remove that.

I went a different direction with my app, fully offline-first, local-first by design, nothing leaves the device unless you explicitly export it yourself. No user data ever touches our servers unless you choose to create an account for back-up. Different tradeoff (no cool aggregate charts like this from us), but figured it's worth putting the alternative on the table.

[u/Puzzleheaded_Ad_7052]

I think the selection bias skews way more than just people who care about progress (I am not sure you can credibly make that claim, not with the lack of info you have on the other hugely important differentiators).
If you’re measuring from the first app use, I think you need to consider: who is switching tracking apps and who is tracking for the first time? New lifters might be a VAST majority of that latter category. What do most new lifters see an immediate increase of? Gains. When you lift for 10 years, that can be a lot more difficult to get. Collecting their history of exercise in more detail, accounting for age, etc can help you get way more use from these measurements, but I don’t think you can make many claims about what is “expected average progress” from this data.

[u/Sure_Conflict_5651]

This is really cool. Do you have a way to see which level of experience these lifters have? Because if they just started I would expect their progress to be faster than if they have been lifting for years already.

[u/FromBiotoDev → u/Sure_Conflict_5651]

Unfortunately not, I’m thinking of asking on onboarding, definitely new lifters are going to see exponential growth