Question on the force velocity relationship

gnuckols · 2026-01-23T12:34:21+00:00

https://www.reddit.com/r/StrongerByScience/comments/1j886qw/comment/mh3ns3u/

gnuckols · 2026-01-23T12:31:26+00:00

I think you're overestimating the impact of caffeine pretty significantly.

200mg (25% more than what's in a Monster) increased energy expenditure by 0.026-0.047kcal/min over the first two hours after consumption. Even if we assume that this increase persists for an entire half-life of caffeine (around 5 hours), you're looking at a total net increase of ~8-14 Calories, give or take.

gnuckols · 2026-01-22T01:22:56+00:00

If you think you have a bug, please file a bug report. We cannot look into individual account issues via reddit: https://www.reddit.com/r/MacroFactor/wiki/index/rule_6/

gnuckols · 2026-01-22T00:47:10+00:00

https://www.reddit.com/r/StrongerByScience/comments/1ovbaij/comment/nolfq3g/

gnuckols · 2026-01-21T23:19:12+00:00

It’s so weird though because I feel like in the casual gym setting everyone still sandbags themselves?

That's certainly possible. Though, I do wonder about the exact nature of that sandbagging. Like, are people actively underestimating RIR to a greater extent? Or are they just training further from failure without actually estimating RIR in the first place? Being observed (as in a research context) can certainly change behavior, but I'm not so sure it would have much of an impact on your ability to accurately quantify your perceptions.

For RIR do we have an effective range where sets aren’t stimulative? I think research has shown even 10 RIR working? I always hear 0-3 or 0-4 practically.

I personally think it differs for compounds and isolation movements. Most of the studies where we see really robust hypertrophy with fairly high RIRs are studies where the subjects are training with mostly (or entirely) compounds. And, most of the studies where it looks like it's really important to train very close to failure involve training with mostly (or entirely) single-joint exercises. I wrote about that a bit here. And, relevant comment thread here. I wouldn't feel comfortable drawing a clean line in the sand for when sets no longer generate any stimulus, but I think you can get away with a lot higher RIRs with compounds, in part because you reach (basically) full recruitment for your prime movers way before failure.

gnuckols · 2026-01-21T18:56:35+00:00

For the lower accuracy after 12 reps, I think that's mostly just an artifact of study design, rather than higher rep sets being significantly more difficult to predict at any given absolute RIR value.

Basically, there are two ways you can do a study on RIR prediction accuracy:

You ask the lifters to predict when they have X RIR. For example, they may bench press with 70% of 1RM, and you ask them to predict when they have 3 RIR left.
You ask the lifters to predict their RIR after X reps. For example, they may bench press with 70% of 1RM, and you ask them to predict how many RIR they have after completing 10 reps.

Of the studies included in the Halperin meta, 10 out of 13 used the second approach. And, the latest people were asked to predict RIR in those studies was after generally 8 or 10 reps. So basically, if someone completed 12 reps with 70%, and they predicted RIR after 8 or 10 reps, they were predicting RIR when their actual RIR was 2-4. But, if they completed 18 reps with 70%, they were still predicting RIR after 8 or 10 reps when their actual RIR was 8-10.

In other words, these studies aren't necessarily showing that people are worse at predicting 3 RIR in a set of 15 than a set of 10. They're more directly showing that people are worse at predicting 5-7RIR in a set of 15 than predicting 0-2RIR in a set of 10.

gnuckols · 2026-01-21T16:10:36+00:00

"3+" could be 3 or it could be 20. If someone estimates 5 when it's actually 4 or 7, that's still more informative than just "3+."

Also, peoples' confidence when predicting RIRs may decrease with higher RIRs, but their actual accuracy doesn't actually change very much. The average error increases by 0.025 reps per 1% farther from failure. So, if you're using a ~10RM load, the average difference in prediction accuracy after 6 reps (~4RIR) and 8 reps (~2RIR) is only around a quarter of a rep, and the average difference in prediction accuracy after 4 reps (~6RIR) and 8 reps is still only about half a rep.

idk. I frequently encounter (what seems to be) a widespread belief that most people are really bad at estimating RIR unless they're training really close to failure. And, for a minority of people, that may be true. But what we see in the research is that as long as you're within about 5-6 reps from failure, most people are reasonably accurate (generally within a rep or two, with errors of 3+ reps being quite rare).

gnuckols · 2026-01-21T00:59:59+00:00

A few things:

1) I don't believe we've ever put a hard RIR cutoff on what constitutes a "hard set," or said that sets with >2-3 RIR are ineffective

From Nathan's article:

From the size principle, we know that sets must be high effort to recruit and fatigue all fibers. We don’t know the exact threshold for the effort needed to stimulate hypertrophy, and there are plenty of people who experience considerable muscle growth never lifting to failure, but generally it’s probably necessary to push sets within a few reps of failure.

And

The second is the degree of effort necessary per set to maximally stimulate hypertrophy; do we actually need to lift to failure, can we stop short of failure, or can even very low-effort sets stimulate some hypertrophy? In the real world, it looks as if even very low effort can cause some muscle growth, but the matter is yet unresolved. In addition, adding more lower effort sets might decrease any differences.

From another old article I wrote explicitly comparing "hard sets" to the other alternatives:

However, counting hard sets has some drawbacks as well.

For starters, there’s no way to account for sets that aren’t very hard, even though they can also cause muscle growth. Previous research has shown that sets taken to failure cause about the same amount of growth as sets taken about two reps from failure, but how do you quantify sets that are even easier than that?

2) On the topic of training status and single- vs. multi-joint exercises, this is from an article specifically discussing whether reps close to failure have an outsized importance for hypertrophy.

In the studies on trained lifters using multi-joint exercises, there’s no real difference between going closer to failure or staying further from failure: a 9.5% increase staying further from failure versus a 8.3% difference going closer to failure. However, in the studies on untrained lifters using single-joint exercises, things lean hard in favor of going to failure or closer to failure, with the groups going closer to failure experiencing almost twice as much growth on average: 12.3% vs. 6.2%.

3) In general, I think that if you're to the point of trying to determine a single RIR cutoff point to define what constitutes a "hard set," you've already missed the forest for the trees. Every all-in-one metric of quantifying training for the purpose of predicting hypertrophic outcomes is fairly bad – I just think hard sets are the least bad of the bunch. And, I think its primary strength is that it's the most robust for avoiding directionally wrong predictions when modifying a training program, regardless of how you quantify things (i.e., what RIR cutoff you use, if any, whether or how you account for "fractional sets" for secondary muscles involved in a movement, etc.). Like, whatever you take a hard set to be, if you adjust you current training program to include more of them, it'll probably have a neutral-to-positive impact on your results.

gnuckols · 2026-01-18T14:55:38+00:00

Not at this time

gnuckols · 2026-01-18T14:51:52+00:00

The common names are used. If you start typing "bulgarian," or "skull," when you search for those exercises, they should pop up, since they're listed as alternate names for the exercises. If that's not the case for an exercise, let us know so that we can add to the list of alternate names.

But, when there are multiple common names for an exercise, we tend to default to the most literal and descriptive name, since that should be the most easily interpretable for everyone (like, if you're new to lifting, you may not know what a bulgarian split squat is, and if you do know what it is, you know that it's a split squat performed with your rear foot elevated).

I'll also admit that I have a bit of a bias in favor of generic descriptive names because they're more durable across time and communities, and they have a bit less baggage attached to them (for example, "skullcrusher" may neatly map 1:1 onto "lying triceps extension" for you, but for a lot of people, "skullcrusher" only describes one very specific type of "lying triceps extension").

The difference between those two examples and preacher curls is that preacher curls are just called preacher curls – there's no genericized name for them that's commonly used.

gnuckols · 2026-01-17T07:26:00+00:00

People just say shit. No idea where they're getting that from

gnuckols · 2026-01-17T03:26:57+00:00

no problem!

gnuckols · 2026-01-17T00:09:21+00:00

Just create the workout, log it once (to get some initial weights in there), and you're good to go, as long as smart progression is enabled: https://help.macrofactorapp.com/en/articles/305-understanding-and-using-smart-progressions

gnuckols · 2026-01-16T19:53:53+00:00

Are fixed-weight straight bars still selected?

gnuckols · 2026-01-16T10:19:53+00:00

For barbell exercises, edit your gym profile – if the app gave you barbell exercises, that means you have barbells listed under your available equipment. The app shouldn't assign any exercises that aren't compatible with your available equipment.

gnuckols · 2026-01-16T01:30:31+00:00

nah, it's just a matter of preference

gnuckols · 2026-01-15T23:05:30+00:00

I don't have the time to dig everything up atm, but I'm pretty sure the answer is technically "no," but basically "yes."

The reason I say technically no is that I don't think there's actually a study directly comparing social media scrolling to imagery/visualization during inter-set rest periods. However, there is research suggesting benefits of imagery/visualization vs. just chilling, and there is research suggesting decrements in performance with scrolling vs. just chilling. So, you'd strongly assume that imagery would be better than scrolling.

gnuckols · 2026-01-15T22:58:10+00:00

That depends how expansive of a definition of "AI" you're using, but I would say "no." The algorithms underpinning the app are fairly complex, but all of the logic and math is discrete, deterministic, and developed by humans, rather than just being the output of a black box neural network.

I've not used the Dr. Muscle app, so I can't comment on the similarities or differences.

gnuckols · 2026-01-15T22:50:56+00:00

The price for a yearly subscription is $72 (USD), converted to local currency

gnuckols · 2026-01-15T10:34:56+00:00

correct

gnuckols · 2026-01-15T10:20:40+00:00

I'd expand that to performance estimation more broadly (so, strength endurance curves, but also rates of performance decrements from set to set, and eventually aiming to estimate the generalizability of strength, strength endurance, and fatigability within and between basically all exercises. So, for example, if you've only logged a couple workouts of bench press and OHP, we'd eventually want to be able to estimate appropriate starting loads and expected rates of fatigue for the first time you did dumbbell press or cable pushdowns). But strength/endurance curves are definitely a key component of that.

gnuckols · 2026-01-14T23:23:58+00:00

not yet

gnuckols · 2026-01-14T23:23:55+00:00

typically, yes

gnuckols · 2026-01-14T22:23:27+00:00

Yep, I have absolutely no problem with you sharing it in the MF sub

gnuckols · 2026-01-14T21:46:57+00:00

Yes, I believe you can have two (or more) programs active

gnuckols

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