Why I Left MASS

Back in 2016, I shot Eric Helms a message, asking if he’d be interested in starting a research review together. Eric brought Mike Zourdos on board as well, and we started planning. By the spring of 2017, we were ready to launch. Ever since then, MASS (which stands for Monthly Applications in Strength Sport) has been far more successful and rewarding than I’d ever imagined or hoped for. So, it may come as a surprise that I’m stepping away.

I wanted to write this for a few reasons.

First, there’s frequently an air of suspicion when a founder of a business steps away. Was there bad blood internally? Were they forced out? Are they abandoning a sinking ship? So, I just wanted to head off any musings or assumptions people might have.

Second, I feel like I owe an explanation to subscribers. If you looked forward to my articles each month, you might be disappointed that I’m leaving. So, I feel like you deserve to know the reasons for my decision.

Finally, I just wanted to share my reasons for leaving. Partially because I simply like being understood – it’s preferable to tell people what I’m thinking, instead of leaving them to make assumptions. And partially for purely practical reasons – I’m sure a lot of people will ask me why I left. A full answer is better than a partial, hasty, one-off reply, and being able to link an article will save me from having to type it all out multiple times.

Just to get this out of the way early: everything’s good within the MASS team. We’re all still buddies. There’s no bad blood. The business is doing great. My reasons for wanting to step away are not related to any interpersonal or business-related conflict, and I’m leaving completely of my own volition.

So, what are my reasons for leaving?

The biggest, by far, is that I feel like I’ve said virtually everything I’d like to say about the topics at the intersection of my interests and the audience’s interests. I’ve written about 10,000-15,000 words per issue for 70 issues. I’m too lazy to get a word count on every single MASS article I’ve written, but it’s 500,000 words of content at minimum, and probably somewhere in the neighborhood of 1,000,000, spread across approximately 200 articles. In all of those words, and spread across all of those articles, I feel like I’ve said most of what I’d like to say.

Of course, science always advances, and exciting new topics of inquiry come to the fore every so often, so I don’t feel like I’ve said everything I will ever want to say. But, I don’t feel like I have 3-4 substantial new things to say each month (at least, on topics that would interest most readers). Maybe more like 3-4 new things to say per year. Not enough to be a regular contributor to a monthly research review.

My second reason for leaving dovetails with the first: I know MASS will simply be better with some fresh blood and fresh perspectives. I’ve had about six years to put my thoughts out into the world in MASS, and I’m acutely aware that my own insights and perspectives are inherently limited – any single person has a finite amount of useful thoughts and ideas to share with people. So, in a vacuum, I think that replacing me with anyone who was similarly competent would be a net positive.

Thankfully, MASS has done even better than that. Lauren Colenso-Semple is taking my spot. She’s smarter than me, better educated than me, has far more hands-on research experience than I have, and she’s probably a better writer than me as well. So, not only will she have fresh perspectives to bring to the table – we had very different journeys into fitness, into coaching, and through higher education – she’ll be an upgrade.

My final reason for leaving is a combination of time, and an innate need to feel like I’m pulling my weight. For most of my time with MASS, MASS was my highest business-related priority by far. However, that’s not the case anymore: I’m also part of the team behind a nutrition app now (MacroFactor). MacroFactor is (thankfully) doing really well, but success often brings expanded duties and obligations. I’ve reached a point where I don’t feel like I can do everything I need to do to make MacroFactor as successful as possible, and also do everything I need to do to make MASS as successful as possible. I’m not wired in a way that allows me that do something with half focus – I either need to be all-in or all-out, and I just can’t be all-in with both MASS and MacroFactor anymore.

So, this is where my first two considerations came in – which company can I contribute more to, and which company needs me more? After (honestly not that much) deliberation, the decision was pretty clear: I feel that I’ve contributed most of what I feel I can contribute to MASS already, and I sincerely believe that MASS will be better off without me (and knowing Lauren would be replacing me made the decision particularly easy). I could have stayed with MASS and just phoned it in, but that’s not something I’m capable of doing long-term. I’d feel too guilty about it. If I’m the part-owner of a business, I think I owe more than that to my partners and customers. The rest of the team deserves a partner who lives and breathes the business, and the subscribers deserve writers who are 100% focused on making the best content possible. If my personal financial interests conflict with the collective interests of everyone else involved, I wouldn’t be able to sleep easy if I picked myself over literally everyone else.

So with that, I’m closing the book on this chapter of my life. I really do love, value, and appreciate everyone who’s subscribed to MASS over the years, and I have nothing but respect for the MASS team. I’d also like to thank everyone who’s helped out or contributed behind the scenes – Chad Dolan, Katherine Whitfield, Kedric Kwan, Colby Sousa, Jay Ehrenstein, Leonardo Ehrenstein, Lyndsey Nuckols, and Anna Wilder. MASS would not be in the place it’s in without all of them. Last but not least, I owe a huge debt of gratitude to Sol Orwell for giving me the nudge I needed to start MASS in the first place.

A few final notes:

  1. I fully intend to keep shilling for MASS. And, if anything, I’ll probably start shilling harder. Promoting a product I profit from always feels a little weird (“is he promoting it because he thinks it’s really that good, or just because it’s good for his bank account?”), but now I’m fully unencumbered. To be 100% clear, I no longer have any financial or equity stake in MASS. It’s a clean break.
  2. If you’d like to read my MASS content, it’ll still be in the MASS archives. It’s not going anywhere.
  3. I hope this doesn’t make it sound like I’m primarily leaving MASS because of MacroFactor. On the contrary, I’d been feeling like I should probably step away for a while (for the first two reasons listed), and expanded time pressure from MacroFactor was just the consideration that provided the final nudge.
  4. If you subscribed to MASS solely (or primarily) to read my articles, shoot me a message and I’d be happy to personally refund you for the remaining time covered by your subscription (please don’t request a refund from MASS directly – I’m the one leaving, so the rest of the team shouldn’t have to pay the refund). So, for example, if you got a yearly subscription 8 months ago, I’d be happy to refund you for the forthcoming 4 months. You don’t even have to cancel your subscription – you can just treat it as a few free months on me. If anything, I suspect you’ll be pleasantly surprised if you stick around.

Looking forward

I’ve been in a creative rut for a while. Part of it relates to being overworked (by my own choosing, to be clear), but I think part of it goes deeper than that.

Knowing how much background information to include in your content is a persistent issue when writing anything in the fitness space. If you include too much, better-informed readers will generally check out before they make it to the interesting parts of an article, because they’ll assume the whole article is just rehashing information they already know. However, if you include too little background information, people who’ve consumed less fitness content may feel lost.

That’s relevant, because I’ve had a major project hanging over my head for about six years at this point: writing the second editions of the Art and Science of Lifting. I’m hesitant to write standalone articles, because a lot of the article content would be covered in the books. However, attempts at writing the books haven’t gone well, due to the aforementioned issue related to background information. More often than not, the relevant background information for a particular topic falls into two discrete buckets:

1) Basic science stuff – can I assume the reader knows the basics of respiration, muscle physiology, biomechanics, etc.?

2) Other broad fitness-related subjects – if I want to write about training volume, the effect of volume will interact with training age, intensity, frequency, exercise selection, etc. Can I assume the reader has a basic understanding of all of those other topics, or do I need to briefly explain the relevant bits before actually diving into the subject of training volume?

I’ve wanted the second edition of Art and Science to be a resource that doesn’t go over anyone’s head (i.e. I don’t want lack of background info to be a barrier for readers), but I also want it to go into enough depth that more advanced readers will still learn new things and benefit from reading it. That presented me with a problem: where should I start?

Books are generally meant to be consumed sequentially. However, I haven’t been able to hammer out an order of topics for the book, such that one topic builds on the next, and earlier topics don’t require information from later topics in order to be fully explained. For example, if I wanted to write a chapter about training volume, a chapter about training intensity, and a chapter about training frequency, I’m not sure how to fully explain volume without the supposition that people already understand at least a bit about intensity and frequency, I’m not sure how I’d fully explain intensity without the supposition that people already understand at least a bit about volume and frequency, etc. There is obviously an established method for tackling this problem (explain the bare minimum required about later topics in order to discuss the main topic of a chapter, and then dig into the other topics in more depth later on), but I find that to be an inelegant solution. I also just found myself needing to go into so much depth about forthcoming topics that I didn’t have much left to say about those topics later.

So, I’ve decided to opt for a completely different approach. Since so many fitness-related topics are interconnected, I’ve decided to expand the project considerably, and to publish it as a knowledge base. To start with, I’ll probably use Obsidian (hat tip to Brian Minor for telling me about Obsidian). I think this will effectively solve the “background info” problem. All necessary background information for any high-level topic will be self-contained within the knowledge base, so people who need to read the background information will be able to easily access it, and people who don’t need to read any background information on a particular topic can forge right ahead.

Of course, such an approach will require me to actually write the background information for all of the subjects I’d like to discuss. So, for now, that’s what I’ll be working on. It’ll start with a musculoskeletal anatomy database, upon which I’ll build an exercise database. Then, I’ll need to write some textbook-style content covering exercise physiology and biomechanics. And then I’ll be able to dig into subjects directly related to getting strong and jacked. So, this will be a pretty big project, but once it’s done, it’ll be an interconnected framework where you can start at any node in the network, and take yourself on a little journey through my brain. Ultimately, I want the knowledge base to contain virtually everything I know about lifting, arranged in a logical and easily navigable way.

Working on the knowledge base will also let me spend more of my time doing one of the things I find most fulfilling about my work: making evergreen content that can benefit a lot of people for a long time. I’ve spent most of the past few years answering one-off messages or working on paywalled content for MASS. My overall volume of work output has been very high, but only a small minority of the people who follow my work have seen a significant fraction of my total output. In keeping with the theme of my last post on here, I’m trying to be intentional about spending more of my time doing things that will be more beneficial to more people. I think a comprehensive knowledge base will ultimately have a far greater impact than a bunch of disconnected articles, or even a fresh pair of books. It’ll take a lot more work, obviously, but I think it’ll be worth it.

Stepping back

If you’re reading this because I sent you this link in response to a question, consider this an apology. I’d love to answer your question, but I just can’t.

I’m writing this on December 27th, 2021 at about 3am.

I was sick on Christmas. Nothing too serious, but I was running a fever, and I had some chills, body aches, and a deep cough I couldn’t shake. I still spent about four hours answering comments, messages, and emails. Today (well, technically yesterday; the 26th) my wife was sick – probably with the same bug I have – so I spent the day hanging out with her, and waited to start work until she went to bed. I just finished up. And by “work,” I just mean answering comments, messages, and emails. I’m still sick. Better than Christmas, but I’m still under the weather.

As I was finishing up work for the evening, I was struck by the absurdity of it all. I should be in bed right now. Even if I wasn’t sick, today was Sunday, and it’s the day after Christmas. It’s not a day to be working until 3am.

So, why was I working this late, under these circumstances?

It’s certainly not because I believe in all of the “rise and grind” workaholic bullshit. I very much believe in working to live, not living to work. I’m not writing this because I think you should adopt this type of lifestyle, and I’m absolutely not looking for any sort of “credit” for doing this to myself.

More than anything, I do it out of a sense of obligation, which I now recognize was probably a misplaced sense of obligation.

When I started gregnuckols.com (which became strengtheory.com, and now strongerbyscience.com) back in 2012, I told myself that I’d be 100% accessible to anyone who had any questions about fitness, nutrition, my articles, etc. I was 20 years old, and the very definition of a “nobody.” There were a lot of lifters and writers I looked up to, and I’d try to ask them questions (via email, on forums, on social media, etc.), because I respected their opinions and perspectives. They ignored me 90%+ of the time, because of course they did. They were busy people, and I’m sure that fielding random questions (which were probably pretty dumb questions) from some random kid was pretty low on their priority list. But I told myself that if I was ever in a position where people were asking for my opinion, I’d always be available, and personally respond to everyone.

Fast forward almost 10 years, and that’s exactly what I’ve done. When I wake up, I check (in this order, though it’s not necessarily the order of importance) my texts, my Instagram comments, my Instagram messages, my Reddit messages, my Reddit comment replies, new threads posted in the Stronger By Science subreddit, new threads posted in the Stronger By Science Programs subreddit, new threads posted in the MacroFactor subreddit, my Facebook comment replies, new threads posted in the Stronger By Science Facebook group, new threads posted in the MASS Facebook group, new threads posted in the MacroFactor Facebook group, Twitter messages, Twitter replies, ResearchGate messages, ResearchGate paper requests, comments on StrongerByScience.com, Facebook messages, and emails. Between all of those different places, I typically respond to 150-200 discrete questions per day, which takes me about 5-6 hours. That’s excluding internal communication within Stronger By Science, MASS, and MacroFactor, and purely personal communication (keeping up with family and friends).

At this point, it’s simply become untenable to keep this up. I dread publishing new content, because the influx of additional replies (which I feel obligated to respond to) will completely subsume my next workday. I barely have time to even write new, free long-form content, which is the part of my job I enjoy the most (my last “real” article that wasn’t just a republished MASS piece came out in March of last year). When I have to produce a fair bit of content (i.e. when I’m writing new MASS content), my workdays regularly stretch out to 13-15 hours and my personal life and relationships suffer. I feel like I can’t take time off of work – not even one day over the weekend, much less a full vacation – because if 150-200 things to respond to turn into 300-400 (with one day off) or 1000+ (with a week off), I’m fucked for several days after I get back to work. Hence working on Christmas when I’m sick, followed by working until 3am the next day.

And the thing is, I don’t have to do any of this. I’m my own boss, so it’s not like there’s any formal requirement. It’s purely predicated on my weird sense of duty and obligation.

And, to be clear, I don’t actually dislike responding to everything (so if you’re reading this, and you’ve sent me dozens of messages over the years, certainly don’t feel bad about it). I’m in this business because I enjoy helping people. I wouldn’t have kept it up for this long if I didn’t at least feel neutral-to-positive about responding to everything, sense of obligation be damned. It’s just reached the point where responding to everything is having a marked negative impact on the business as a whole (it’s hard to have a flourishing content-based business when you don’t actually have time to make new content), and a marked negative impact on my life. The amount of things to respond to just keeps increasing, so I’d need to pull back sooner or later (unless the business itself started shrinking, which isn’t really an option since I’m not the only person depending on it now). Responding to everything was very manageable 5 years ago, fairly manageable 3 years ago, and not very manageable (but not completely out of control) 1 year ago, but it’s now approaching the point of being completely overwhelming.

With that in mind…I’m done with it. For real this time. I actually tried to pull back when the podcast launched (I said I’d just collect the best questions and answer them on the podcast), but I didn’t stick to it. But for me, when I put something in writing, it feels more “real” and final.

In concrete terms, this just means I’ll be shifting priorities. Instead of making new content in the slivers of time I could find around responding to everything, I’ll be focusing on new content first and foremost, and peek at my notifications when the creative and productive juices stop flowing. I’ll still be pretty active in the Stronger By Science programs subreddit (at least through the end of the /r/weightroom program party), in the MacroFactor FB group and subreddit, and in the replies for new long-form articles I write. Otherwise, I may reply to other things here and there if I have time, but I’ll be quite a bit harder to get ahold of. I don’t particularly like it, and I know 20-year-old Greg would be disappointed in me, but I’ve finally reached the point where it’s necessary.

I’m sure this will come across as a trite and self-absorbed way of ending a trite and self-absorbed blog post, but I feel like I’m closing a significant chapter of my life; this is something I’ve done for close to a decade now. I anticipate that it will be painful in a way that’s difficult to explain (my strange sense of obligation runs deep), but I’m excited to see what I’ll be able to do with the time this decision will free up for me. I should be able to start writing free articles more consistently, and who knows; maybe I’ll even take a day off from time to time.

I’m publishing this now before I have a chance to get cold feet.

Now it’s time to get in bed.

Fitness stuff, August 2020

If you follow me on Instagram, you’ve probably seen I’m back to training pretty hard again. Recently, I hit a pretty big pressing PR: 315×10 on low incline press. This was considerably better than my prior PR. I can’t remember for sure if my old best was 315×6 or 315×8, but I’m sure I’ve never hit 315×10. Low incline is one of my main indicators of my overall pressing strength; for me at least, competition-style pronated grip and reverse grip bench press are pretty finicky. They’re influenced quite a bit by the bench I’m using and, more importantly, how much stretching I’ve been doing (and thus, how well I can arch). Performance is 1/3rd strength, 1/3rd technique, and 1/3rd magic. Low incline and feet-up close-grip bench, on the other hand, are honest. The range of motion is longer, I barely arch (it’s still probably a ridiculous arch by some peoples’ standards, but it’s almost nonexistent by powerlifting standards), and performance is pretty consistent day-to-day. So, I use low incline and feet-up closegrip as my barometers of how my overall pressing strength is doing. The rubber will meet the road once I start ramping intensity up, but I’m pretty sure my pressing is the strongest it’s ever been.

A little over three months ago, I could barely grind out 315×3. You can see the videos below.

 

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Quite a few people have asked me about my programming these last few months, and I’m not interested in typing out long Instagram comments, so I’m writing about it here.

I’m using an upper/lower split, with lower-body days alternating between squats and deadlifts. Each main lift is also alternating between two variations. So, here’s how things have looked:

1a) Close-grip feet-up bench

2a) Deficit trap bar RDL

1b) Low incline

3a) High bar squat

1a) Close-grip feet-up bench

2b) Sumo low block pull

1b) Low incline

3b) Front squat (recently switched for low bar paused squats)

I recently subbed low-bar paused squats in for front squats. I slightly strained my adductor magnus about a week ago doing high bar squats, and I think it’s because my AM was only getting challenged through a long ROM once per 8 workouts (high bar squat day; my AM certainly contributes for sumo block pulls, but the hip ROM is shorter), so it just wasn’t building up the load tolerance it needed. It’s feeling better, though, and otherwise things have been going swimmingly.

In terms of the workouts themselves, I started with ~3RM loads for each exercise, and I’m working up to one top set, trying to beat my prior rep PR. That’s followed by low-rep dropback sets that I aim to move as explosively as possible with reasonably short rest intervals, until bar speed starts substantially slowing down. After that, I end each workout with some accessory work that I do for moderate-to-high reps until failure.

For example, here’s how my last close-grip feet-up bench workout went:

Close-grip feet-up bench: 315×8; 225 10-12×5 (sets x reps) with 60-90 seconds between sets (I don’t count dropback sets; I just do them until I know I’m done).

JM press: 115xfailure, 95xfailure, 75xfailure

Flyes: 40xfailure, 30xfailure

Incline curls: 30 2xfailure, 20xfailure

That’s pretty typical for pressing workouts.

For lower body workouts, I generally do fewer dropback sets due to low back fatigue. Once I get a low back pump that doesn’t want to go away, I’ll end with some long-paused work (e.g. just sitting in the bottom of a squat with 225 for a couple minutes, or holding the bottom of an RDL position with 185 or 225 for as long as I can). I generally just finish lower body days with high-rep hip thrusts and single-leg bodyweight calf raises.

On off days, I’ll hop on a stationary bike for 30-60 minutes, and do some light accessory work (generally single-leg stuff, and occasionally rear delt work) if I have time. Speaking of off days, I’m letting recovery dictate training frequency. Once the muscles I’m about to train don’t feel sore and fatigued, I train again. On weeks I don’t have as much work (and can therefore sleep more), that generally works out to two consecutive training days, followed by one rest day. On weeks I’m busier and sleeping less, I generally take at least one day between workouts, and sometimes two. Overall, I’m pressing a little more than twice per week on average, and squatting and deadlifting slightly more than once per week.

This style of training has really been agreeing with me so far. Each workout is more challenging than I’m used to, and frequency is lower; for a long time, frequency for each lift was a lot higher, but each workout for each lift was quite a bit easier (to allow for higher frequency). I got a lot of mileage out of that style of training, but it hasn’t done much for me in a while; I think I wrung it dry, and that that style of training just doesn’t present a large enough stimulus for me to adapt to anymore. For now, higher per-session stress seems to be productive, which necessitates lower frequency.

I’ve noticed a similar pattern over time with my training. Higher frequency works well for a while until it doesn’t, then lower frequency and higher per-session volume works well for a while. By the time lower frequencies stop working, higher frequencies work pretty well again. I think I have a tendency to be loyal to one particular style of training for a bit too long, though. I think I’d be well-served by being more willing to make big changes sooner when I plateau.

So…that’s about it. We’ll see how long this style of training keeps working for me. Once I hit my goal sets of 10 with all of my current training weights (315 for close-grip feet-up bench, 405 for trap bar deficit RDL, 495 for high bar squat and low bar paused squat, and 635 for sumo block pulls; I’m still deciding if I want to go to 335 for low incline, or sub in another exercise), I should be at or near the strongest I’ve ever been overall. I REALLY want to squat and pull 800, and bench 500. I *think* I’d be able to take a run at the 800 squat and 500 bench once I hit the numbers I’m aiming for with this training cycle, but I’m considering keeping loads conservative until I hit one more batch of 10RMs (335 for my pressing movements, 455 for trap bar deficit RDL, 545 for the squats, and 675 for sumo block pulls). I’ve been so close to an 800 squat and a 500 bench for so long that I want to leave nothing in doubt when I make another run at them. For the time being, though, I’m really enjoying my current approach of aiming for rep RPs with manageable weights instead of chasing progress via more plates on the bar. I’m excited to see if it’ll get me where I want to go.

Sourdough hack

People who know me well will all testify to the fact that I am nothing if not forgetful. I also like sourdough bread. Or more specifically, I like making sourdough bread. Lyndsey really likes eating sourdough bread, which is probably why I enjoy making it so much.

Unfortunately, forgetfulness and sourdough don’t mix. A necessary element of making good sourdough is having a good starter. A good starter requires care and consistent feeding. I’ve made several good starters previously, but they would eventually die when I just forgot to feed them for a couple of days (or, in the case of starters I put in the fridge, a couple of weeks). When a starter dies, it generally takes at least a week or so to get a new starter going, and to ensure it’s healthy and active enough for baking, which just isn’t something I have the patience to do repeatedly. So, I just stopped making sourdough for a while, and spent some time perfecting a sandwich loaf. I’ll share that recipe at some point.

However, the hankering for sourdough hit me again, so I wanted to see if I could devise a little hack that would allow me to bake pretty darn good sourdough bread without needing to tend to a starter. I wish I could regale you with tales of trial-and-error and troubleshooting, but my first attempt worked out really well, and this little hack seems to be almost foolproof.

Before we get to that, however, a little background about sourdough starter:

Starter is composed of 4 crucial elements: water, flour, lactic acid producing bacteria (LAB from here on), and wild yeast. You provide the water and flour, and trace amounts of wild yeast and LAB are already present in the flour (and some may come from the air, from your hands, from the mixing utensils, etc. Wild yeast and LAB are everywhere). When you start tending a starter, a full-on bacterial war begins as the LAB fight for supremacy against other strains of bacteria. When a starter dies, or if it simply fails to thrive, it’s generally because the LAB lost the war, and you need to start over. However, when the LAB win, they form a symbiotic relationship with the wild yeast. The LAB decrease the pH of the mixture (making it more acidic) which kills off most other bacterial strains, while providing an ideal environment for the LAB and the yeast. Furthermore, the LAB break down starches, producing sugars. The yeast ferments those sugars, creating some alcohol and a lot of carbon dioxide. The carbon dioxide is what gives bread its bubbles. Once you have a stable community of LAB and wild yeast in your starter, they’ll generally maintain control over their territory, warding off other bacterial interlopers, as long as you feed the starter regularly.

Sourdough bread tastes different than bread made with commercial yeast, primarily due to the activity of the LAB. LAB produce (as the name implies) lactic acid, and also acetic acid. Lactic acid and acetic acid (moreso acetic acid) give sourdough its characteristic flavor. Acetic acid is also the primary acid in vinegar, so vinegar is sometimes added to bread made with commercial yeast to make something that approximates the flavor of sourdough. Commercial yeast works WAY faster than wild yeast does, which doesn’t give the LAB time to produce lactic and acetic acid to create flavor in the bread. You can make a loaf of bread with commercial yeast in ~2-3 hours start-to-finish (with 2 rises). Making good sourdough is an all-day (or multi-day) affair. The combination of time and the density of LAB in the sourdough starter allows more flavor to be developed.

While commercial yeast works faster than wild yeast, it’s also more fragile. Its speed contributes to its fragility. It multiplies rapidly, consumes sugars quickly, and then starves itself to death within a matter of hours. Wild yeast works slower, but it’s also heartier. Crucially, when wild yeast and commercial yeast are present in the same starter, the wild yeast will stick around after the commercial yeast has already worn itself out.

That’s the magic behind this sourdough hack. Here’s what I do to make an accelerated starter:

In a bowl, mix 100g of whole wheat flour, ~25-50g of something with high amounts of lactic acid bacteria that’s a liquid or at least semi-liquidy (I generally use nonfat kefir, but I’ve also used yogurt and cultured buttermilk. The key is to ensure it has active LAB cultures and an acidic pH), ~75ish grams of water, and a little shake of instant yeast (I never measure it, but it can’t be more than a gram or two). You may want to add a touch more water; the mixture should look like a flour/water mix at 100% hydration, and different LAB-containing ingredients have different water contents.

Leave this mixture covered in a bowl for about 12-16 hours at room temperature. During this time, the LAB and commercial yeast quickly colonize the starter, the commercial yeast die, and the wild yeast can rise up to take their place.

For the actual bread itself (note, this recipe assumes some basic level of boule-baking knowledge; if you need or want info about the actual steps of making sourdough, that’s easier to learn from a video. This is a really solid video on the topic):

  1. Mix 500g of bread flour and 350g of water in a bowl and let it autolyse for about an hour.
  2. After the autolyse, add the cheater starter to the dough. I generally just mix and fold it in with a silicone spatula. It doesn’t have to be 100% homogeneous at this stage.
  3. Leave that mixture to rest for about an hour, with 25g of kosher salt sprinkled over the top. Sprinkling the salt on top allows the salt to begin dissolving without actually incorporating into most of the dough yet. Salt tightens gluten strands and slows down yeast activity; at this stage, we’re trying to make sure the wild yeast and LAB are active and beginning to permeate the dough, so we don’t want the salt fully worked into the dough yet.
  4. After an hour, incorporate the salt into the mass of dough by pinching it in, and bring the dough together into a fairly smooth mass using the slap-and-fold-over technique. Place the dough in a covered bowl.
  5. Every 15-30 minutes, stretch and fold the dough to develop the gluten. Wet your hands with cold water before each fold so that the dough doesn’t stick to your fingers.
  6. After 4-5 rounds of stretches and folds, the dough should have started inflating with air and getting a little jiggly. That’s how you know the yeast and bacteria are active. If it’s not getting jiggly yet, just let it keep hanging out at room temperature (covered) until jiggliness is achieved, checking it every 30 minutes or so. At this stage, transfer the dough onto a lightly floured work surface.
  7. Shape your boule, close up the bottom seam, and put it in a floured and covered proofing basket (seam side up) overnight. By the next day, it should have expanded further.
  8. Preheat an oven to 475F with a Dutch oven inside. Let the Dutch oven hang out in the oven for about 30 minutes after the oven has fully preheated.
  9. Transfer your proofed boule into the Dutch oven, score it, and put the Dutch oven’s lid on.
  10. Bake at 475 with the lid on for about 20 minutes. Remove the lid, drop the temp to 425, and continue baking until the crust is nicely caramelized and the internal temperature of the bread reaches 205-210F (about 20-30 minutes).
  11. Let rest at room temp until cool before slicing.

Honestly, this technique has been a game-changer for me. It seems pretty robust and nearly fool-proof (I don’t have to be super precise about how much kefir or commercial yeast I add initially, and the timing for the starter seems to have at least several hours of leeway), and the results I’ve been getting are virtually identical to the results I got when baking with a happy culture I was tending every day. The bread is just as good, and the starter behaves exactly like a wild yeast starter. I haven’t sent it to a lab for analysis, but the taste and behavior lead me to believe that all of the commercial yeast dies off during the long 12-16 hour rest, leaving only wild yeast in my cheater starter. So now, instead of needing to remember to tend a starter every day (and wasting a lot of flour in the process), I just have to remember to get my cheater starter going the night before I plan on making bread.

 

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Very pleased with this loaf

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If you’ve wanted to give sourdough a shot, but you either don’t want to tend a starter or you’ve had trouble with keeping a starter alive, give this little hack a shot. You won’t regret it!

We did everything wrong, and it was awesome

About a week ago, we released an updated version of my training program, Average to Savage.  It is creatively and artfully named Average to Savage 2.0.  The response has been phenomenal.  Here’s how it looks graphically.

I’ve intentionally cut the units off. I’m not sharing this to flex. I’ll leave it up to your imagination.

I’m not completely naive to the world of digital product sales, so here’s how we “should have” sold it.

1) Before anything else, ideally a month or two in advance, we’d set up a system to curate an ideal list of people to launch to.  This probably takes the form of a free downloadable product that’s related to the product in some way (which you could get for free, in exchange for your email address).  After setting this list up, we’d start teasing the real product while providing free content to make sure the people on the list are happy and engaged.

2) At launch, test multiple versions of the sales page to see which one converts best.  Ideally this would be an exclusive pre-sale for a select group of people, so we can get the perfect sales copy pinned down before the main event.

3) Also test multiple prices to see which one maximizes profit.  People are less likely to buy at higher prices, but if the dropoff in conversion rate isn’t concomitant with the increase in price, you’re still good.  100 buyers at $50 nets you more value than 150 buyers at $25.

4) Give some exclusive offer to people who previously bought the first program to make the new program a tantalizing no-brainer upsale.

5) Use some form of scarcity.  Maybe there’s an exclusive bonus for the first 1000 buyers.  Maybe the price goes up if you don’t buy it within the first 72 hours.  There are plenty of scarcity options.

6) Make sure we have an elaborate launch infrastructure in place.  Affiliates are good, but might be challenging to get since most people are selling their own training programs.  An article lined up for publication on the day of launch is a must – the first 90% of it is informative content that hits on a salient “pain point,” and then it smoothly transitions into a sales pitch at the end (still providing value while essentially serving as long-form sales copy).  A series of emails each more desperate than the last (with subject lines tested and optimized for click rates) is also essential.

Here’s what we did instead:

1) About a year ago, I gave a beta version of the program away for free to everyone who bought the original version.

2) I let the program start being sold on another platform, and refused to take a cut of those sales (that requires more explanation than I feel like providing at the moment)

3) Once the program was finalized, I gave the final version away for free to everyone who bought the original version.

4) I also gave it away for free to everyone participating is a community program party on Reddit.

5) We dropped it at $5.  Did we test that price?  Fuck no.

6) Did we test multiple versions of copy on the sales page?  Also, fuck no.

7) Did we run an introductory offer with some sort of scarcity component?  Also…no.

8) Did we have any sort of launch plan or infrastructure, other than sending an email?  I think you can guess the answer to this question.

Here’s how things performed:

1) Over 10% of the money we’ve made on Stronger By Science products (note, this is separate from MASS, which is a different business entity) since the start of 2018 was made in the past week.

2) My Facebook post about the program got the 2nd or 3rd most interaction of anything I’ve posted in the past year (a post explicitly to sell a product).

3) The post on the business page had more organic reach and more interaction than anything we posted since July of last year (now that I think about it, I should probably boost that post).

4) Similar story on Instagram (it didn’t quite beat out the donut I posted in my last article, but it’s one of my better-performing recent posts).

5) In spite of the fact that we gave the program away for free to everyone who bought the first edition and another ~1500 people on Reddit, more than half as many people bought AtS 2.0 in the past week as had bought AtS 1.0 since it launched 5 years ago.

Here was the thinking behind why we did what we did:

1) First and foremost, I thought it was the right thing to do.  We are still a business, and we still need to make money.  However, MASS has done so well that we don’t need to worry as much about profit maximization on Stronger By Science anymore.  I mean, it’s not a charity, but if we can make high-quality products more accessible, I feel like we should.  I think there’s value in selling it rather than giving it away for free (just because people tend to take things more seriously if they have to pay for them, even if the cost is relatively low), but I don’t want the cost barrier to be excessive for virtually anyone if it doesn’t need to be.  This is especially true for something like a training program where all the work is on the front-end (sort of; more on that later).  I put a high price tag on my time, but if all the work is on the front end, I don’t feel as much of a need to jack the price up when I know I’ll easily recoup the time cost.

2) I had a hunch that there was a pretty big untapped market.  I constantly get tagged in posts and IG stories from people excited that they can afford MASS or Art and Science of Lifting now that they’re out of school and have a real paycheck.  I get a ton of messages from students who want to buy something we sell but who can’t afford it.  I also get a ton of messages from people who live in countries with lower overall incomes who want to buy our products but can’t afford what we charge.  It wasn’t so long ago that I was in college and dead broke (rice, beans, bone-in-skin-on chicken thighs for $1.19/lb, and Wal-Mart brand peanut butter were 90% of my calories for about two years), so I feel that on a personal level.  There were a lot of fitness resources I wanted but couldn’t even conceive of affording.  For those reasons, it mattered to me to be able to make AtS 2.0 accessible to virtually anyone, but from a business perspective, it also struck me that there were probably a lot of people who were really eager and willing to buy a program, but they had been priced out of the entire market.

3) On a personal level, I think the current prices for training programs have gotten absolutely ridiculous.  It wasn’t that long ago that most training programs sold for $20-30, with people who could command a premium sometimes selling programs for $50-75.  Now $50 seems to roughly be the entry point, with lots of people selling programs for $100-150+.  I’m sure there are exceptions, but for the most part, they’re fucking spreadsheets with an accompanying 10-15 page PDF, and maybe some basic accompanying pictures/videos to illustrate some exercises.  I guess that whatever the market is willing to pay is technically the “fair price,” but it just strikes me as ludicrous.

4) Regarding the minimalistic launch, I think people are getting better at immediately recognizing that they’re being sold to, and they’re becoming more likely to be turned off when marketers try to be slick about it.  Maybe this isn’t true, and it’s just my audience.  But we’ve found that a lot of our best-performing messaging is basically just, “We have this product.  Here’s what problem it solves.  Here’s why it’s better than its competitors.  You should consider buying it.  The end.”  People are bombarded with marketing that tries to be sneaky and clever (which is never as sneaky or clever as the marketers think it is), and I think they’re getting wise to it.  A simpler, more straight-forward pitch is almost refreshing.  And like I said, my audience may just be weird (in a good way), but that’s been our experience.

5) Our business is built on long-term trust and relationships.  That’s what was behind the decision to make the updates free to previous buyers.  When you treat people well, they’ll be loyal to you, and we go out of our way to treat everyone who interacts with our content really well, whether they buy our products or not.  If we lost out on some degree of short-term profit (and I’m pretty sure we did lose out on some degree of short-term profit), but we built up even more goodwill, that’s a net win.  Goodwill doesn’t pay the bills, but since we’re paying the bills just fine, goodwill is more valuable.  Maybe that will turn into more income at some point, or maybe it’ll just mean better vibes on a day-to-day basis.  It’s hard to put a price tag on day-to-day good vibes.

5b) [soapbox] I think a lot of people in the fitness industry fail to adequately consider long-term costs and benefits.  The thing that maximizes your profit or market penetration this month may cost you big time in the long run, and the thing that leaves some revenue on the table this month may pay off big in the long run.  If your first thought is, “how much money will this make me?” and not “how will this make people feel about me and my company?” … you done goofed.  People have long memories if you treat them well, and longer memories if you treat them poorly.

6) I’m becoming more interested in only doing projects that have larger potential upside.  AtS 2.0 may end up just being a program that’s really good while also being really cheap, and sell about as well as its predecessor.  However, at its price point, it also stands a chance of becoming really big.  The barrier is low enough that it may just become a near-default plan the same way something like 5/3/1 was a few years back.  Essentially, it’s a high-variance play with huge potential upside and virtually no downside.  Using a more traditional pricing approach, maybe I could guarantee that it would net 10-30% more profit than AtS 1.0.  However, with a lower price, I open up the (small) possibility that it could net 1000% more.  If I’m happy with the possibility of it doing 0% better long-term (and I am), “locking in” 10-30% doesn’t particularly interest me if it takes massive potential upside off the table.

Clarification:  I’m not calling you (or anyone) out

1) I’m not trying to “call out” people who use pushier, bigger, or smoother marketing tactics.  We’ve done it before.  In some cases, we’ll do it again.  Heck, we use scarcity all the time (the last day of a sale is a magical time).  We’re also fairly pushy about getting email addresses.  The main reason we’ve gotten more direct and straightforward with our sales copy is simply that it generally works better, but there are a lot of things we simply won’t do for ethical reasons.  However, it’s a tough industry, especially for people just starting out.  I do think there are some bright lines people shouldn’t cross, but I’m far from “anti-marketing.”  However, I’d recommend you at least try a more straightforward approach in your messaging and sales tactics.  The stuff that was smooth and convincing to naive consumers in 2005 may not be the best thing anymore now that everyone is hip to it.

2) I’m not necessarily trying to “call out” people who sell programs at high price points.  This is especially true for people with smaller audiences who are trying to get their footing in the industry.  We have the luxury of not needing to profit-maximize anymore, but I’m definitely not going to be preachy towards people who do need to do so.  It still doesn’t make a lick of sense to me for people/companies who are already clearly successful, but I’m not going to be moralistic about it.  I don’t understand it, but I’m not trying to say it’s “bad.”  However, I do think it’s worth at least considering having a really cheap product, unless you’re intentionally trying to alienate people with lower incomes.

What’s the plan from here?

Well, for starters, I’m going to be making small tweaks and improvements to the program based on feedback.  We’re not approaching this with the perspective of, “it was only $5, so people should just be happy with what they get.”  We’re approaching it with the perspective of, “if we can blow them away with a $5 product, a) good vibes (very important) and b) they may be more interested in other things we’re selling.”  Second, I was already planning on an unconventional approach to selling the second editions of Art and Science, and this experience has further emboldened me to do so.  Lastly, we’re going to keep treating our readers, listeners, and customers really, really well because it’s the right thing to do.

Also, just to make a couple things clear:

1) I’m not trying to make a play at being a fitbiz guru.  If I ever go down that road, please take me out to the pasture and put me down.  I’ll probably talk about business stuff on this blog from time to time, but I don’t consider myself an expert by any means, and I never plan to monetize the modicum of expertise I have.

2) My wife is the business and marketing whiz behind Stronger By Science and MASS.  I’ve been telling her to start a blog for years (since she’s the one with actual expertise in the area), but since she’s no longer freelancing, it’s not worth her time.  We discuss strategy together, but she’s the one who knows how to implement everything, and when we disagree, I defer to her.

Diet Diaries, Volume 1

Hey, folks.

So, it’s been a hot minute since I wrote something for this site (and by “hot minute,” I mean 2.5 years).  I’d like to knock the dust off, though, and start a new series.  I may also share random thoughts here from time to time as well.  Maybe even recipes.  We’ll just see.  The stuff I write on this blog won’t be as scientific or polished as the stuff I write over at Stronger By Science or MASS.  This is my quasi-stream-of-consciousness-quality-content.

For the series, though, I’m going to loosely chronicle my current cut.  This may be interesting to some people.  It may be interesting to no people.  I’d like to have a record of it that’s less ephemeral than periodic Instagram stories, and it may be useful for people in a similar position.

So, for some background, I’ve “successfully” lost weight exactly twice, and neither instance was particularly sustainable.  When I discovered my love of basketball, I was in middle school, had very few responsibilities, and lost about 30lbs because I was playing basketball 3-5 hours per day.  I don’t currently have enough time in my schedule to make that work anymore.  When I went to college, I dropped about 70lbs in 4 months (from 260 to 190) by barely eating and doing an enormous amount of low-intensity cardio.  When I had to read or study for a class, I’d take my books to the campus gym, get a treadmill going at 2.5 miles per hour up a 5 degree incline, and walk for hours.  I was a history major at the time, and so I had a ton of reading to do.  I was barely eating because I was mildly depressed (that’s a big can of worms for another day), and had basically given up on lifting at the time after years of dealing with back problems that had only gotten worse and worse.  I just decided to aggressively diet the weight off since I didn’t “need” it.  Even though I lost a lot of weight, I never developed good habits around food (“just don’t eat” is, surprisingly, not a very sustainable habit), so I gained the weight back once I started lifting and eating normally again.

Ever since then, I’ve tried to cut several times, mostly unsuccessfully.  10-15lbs will come off, I’ll hit a snag, get frustrated, and quit.  The source of the frustration differs.  Sometimes I start losing strength which messes with my psyche.  Sometimes life just gets really stressful, I turn to food for emotional comfort (with poor decisions when I’m sleep-deprived playing a major role), and just gain the weight back.  Sometimes I just start feeling shitty and way less mentally sharp; since my work requires mental sharpness, I think I perceive that as a threat to my livelihood, even though that’s probably irrational.

So currently, I’m in the midst of my 3rd most successful cut on record.  I’m down a little over 25 pounds, and honestly, things are still going pretty damn well.  For this first post, I just want to talk about some of the problems I’ve run into previously, and discuss how I’m doing a better job of dealing with them this time around.

My first challenge was finding my “why.”  No matter what type of goal you have, it helps to place it on a firm foundation: why do you really want to accomplish this thing you say you want to accomplish?  That way, when you run into challenges, or when you get knocked off course, you can fall back and remember why you’re trying to do whatever it is you want to do in the first place, which helps get you back on track mentally.  And for me, I’ve never had a good “why” for cutting.  I’ve told myself I want to cut to be more competitive in powerlifting, but that honestly doesn’t matter to me too much anymore.  There are still some numbers I want to hit, but I just don’t care about the platform as much as I used to.  I’ve told myself that if I lost weight, it may be good for the business, but the business is doing just fine as-is, so making more money isn’t much of a motivator.  A common “why” for people who want to lose weight is that they simply want to look better.  That’s never resonated with me; I’ve never worried too much about how I present myself and, if anything, prefer to present myself poorly.  I think it helps give me a better assessment of the people around me (if you’d treat someone well because they look well-put-together, and poorly if they don’t present themselves as well, I don’t really want to have anything to do with you).  Even when I’ve been fairly lean in the past, I was still proud to be a slob.

I think I’ve finally found a “why” that resonates with me, though.  Cutting is hard for me, and I like a challenge.  That’s it.  That’s my “why.”  I’m a grossly competitive person, and if something matters to me, even a little bit, I want to be very, very good at it.  I don’t have “casual” hobbies; if I’m not good at something, I am incapable of enjoying it unless I’m actively getting better.  Based on the amount of times I’ve tried to cut in the past, it’s clearly something that matters to me on some level (though I still haven’t psychoanalyzed myself enough to know why), so if I’m going to do it, I may as well treat it like a hobby and try to get good at it.  That shift in mindset has been surprisingly productive.  I’m viewing my current cut not as a “thing I’m doing” but rather, as a “skill I’m mastering.”  It’s been pretty motivating.

When, for example, I get the munchies but resist the urge to grab a snack, instead of it being a neutral act, I see it as evidence that my skill at cutting is improving.  It’s less, “hey, you did what you were supposed to and didn’t mess up,” and more, “get fucked past-Greg who would have gotten a snack.  You suck ass at cutting compared to present-Greg.”  Yes, I’m also competitive with past iterations of myself.  Yes, it’s probably weird.  No, I don’t care if you think it’s weird.  It’s been a very productive shift in mindset.

Another challenge I’ve run into in the past is that I really, really like food.  There’s research indicating that obese people simply find food more pleasurable than naturally lean people.  I don’t think I fully “got” that until I started hanging out with Eric Trexler more.  If you follow the food segments of the Stronger By Science podcast, you know how differently Trex and I approach food and cooking.  I think to him, the stuff I cook seems way over the top.  To me, the stuff he eats seems like an anhedonic nightmare.  On the flip side, though, I can tell that I experience a level of rapture from eating really, really good food that he just wouldn’t reach (from eating something).

This love of food is both a blessing and a curse.  The positive is that, no matter what, delicious food can make me feel really, really good.  I could be having a godawful day, but if I eat a great meal, everything is immediately copacetic.  However, the downside is that, when I consistently eat bland food for every single meal, I start getting the blues pretty fucking bad.  I think that’s just a thing that naturally lean people won’t understand.  And when I eat bland stuff all the time, when I finally have the opportunity to eat really good food, I find it incredibly challenging to not overeat.

In the past, I’ve tried to rein in my urge to eat delicious food.  I’d heard from bodybuilders that eating mostly bland food will make you less likely to overeat.  I’ve tried that (many times), and it just doesn’t work for me.  What’s been working better this time around is simply eating delicious food, but eating less of it.  Yep, moderation baby.  Just as exciting as it sounds.  For me personally, when I’m consistently eating good food, even in smaller quantities, I’m less tempted to overeat when I’m around good food in large quantities.  And if I only cook small quantities of good food, the barrier of needing to cook more food has proven to be larger than the desire to eat more food.

It’s hard to overstate how important this change has been.  Case in point:  a couple nights ago, we had dinner with friends.  I made some donuts.  They were incredibly good donuts.  I had one bite of a jelly-filled donut, and two bites of a cream-filled donut.  That’s it.  It wasn’t particularly hard to keep myself from eating more.  They were good, I got to experience them, and I was perfectly satisfied with that.  If I’d been eating bland food in the days and weeks leading up to those donuts, I definitely would have eaten AT LEAST a whole jelly-filled and a whole cream-filled donut.

Another challenge that’s derailed me in the past, related to the prior issue, was having fixed protein targets.  Protein still has calories, and the foods that both taste good and have a lot of protein (eggs, full-fat dairy, fattier meat) have a lot of calories.  When I would cut the “right way” with a relatively high daily protein target, it would generally either lead to overall over-consumption of calories (if I was eating delicious protein-rich foods), or contribute to the eat-bland-food-then-binge issue (if I was eating less delicious protein-rich foods).  Now, don’t get me wrong, I’m still eating enough protein to make the folks at the USDA blush, but I’m probably eating about 160g per day instead of the 200-300g (0.8-1.2g/lb) I used to aim for.  I still eat protein-rich foods at each meal, but I’m not forcing myself to limit food choices to hit a certain protein goal while staying under a particular calorie goal, or eating extra calorie-dense foods that blow up my caloric deficit.  I still think I’m eating “enough” protein generally, but not focusing on it has made it easier to eat less overall.

I think that’s enough for this entry.  I may write another post in a few days.  I may write another post in 2.5 years.  We shall see.

High vs. Low Load Training NOT to Failure

This is a pretty cool study. It’s the first paper comparing hypertrophy in high rep/low load and low rep/high load training NOT to failure.  This is important because people often claim that muscle growth is the same between high and low load training only if the low load sets are taken to failure.  However, as far as I’m aware, no one had actually investigated that idea.  We know that if sets are taken to failure, hypertrophy is similarly.  However, we don’t know that hypertrophy wouldn’t be similar if the sets stopped near (but not at) failure.  One paper I recently reviewed in MASS came close to investigating this question, but the groups in this study not going to failure still went to what we’d call an RPE 10 (you didn’t fail a rep, but you couldn’t have done one more), which is how most people in the gym conceptualize going to failure anyways.

Briefly:  A group of untrained young men performed knee extensions for 8 weeks.  One group did 3 sets of 8 with 80% of their 1RM (something that should be pretty challenging, but not all the way to failure), while one group did 12 sets of 8 with 30% of their 1RM (a ton of sets, but each individual set should have been pretty easy).

The researchers looked at isometric and dynamic strength increases and thickness of the rectus femoris (assessed via ultrasound).  They took a few other measures, but those are the ones that are most important to us.  1RM tests occured once every two weeks.

They found no statistically significant differences in hypertrophy, but the raw percentage change seemed to favor the group using heavier loads (20.4% for the high load group vs. 11.3% for the low load group), so there may actually be a meaningful difference that couldn’t be detected due to low statistical power.  Furthermore, strength gains were almost identical (40.9% for the low load group and 36.2% for the high load group for 1RM; 24% for the low load group and 25.5% for the high load group for isometric strength).

Let’s unpack this a bit.

I’m personally not a fan of how they went about keeping the high rep group from failure.  There would have been a few “good” options (ordering is just my opinion):

Good:  Match reps per set and relative volume.  In this study, the 30% group did 4x as many sets, leading to a much higher relative volume.  80%×3×8=19.2.  30%×12×8=28.8.  They could have, instead, compared 40% to 80%, and had the 40% group do 6 sets of 8.  40%×6×8=19.2.

Better:  For each individual, have them perform a rep max test with their assigned load, then match the number of sets between groups, and assign reps for each individual based on a given percentage of the maximum number of reps possible with the training load.  For example, if you put that percentage at 75% (doing 75% as many reps as they could do with a rep max test), and someone did 8 reps with 80%, you could have them do 8×0.75=6 reps per set.  If someone did 28 reps with 30%, you could have them do 28×0.75=21 reps per set.  Each set would get progressively closer to failure, but using something like 70-75% of max reps should keep people away from failure over 3 sets.  Loads and reps could be reassessed after every max test.

Best:  Use reps in reserve.  People can accurately assign reps in reserve, even with low loads, within 1-2 reps to failure.  They could have just matched the number of sets and kept people with an RIR of 1-2.

As it was, they didn’t equate any training parameter except for reps per set (which was probably the least important thing to equate), and didn’t even use a protocol that was ecologically valid (I doubt many people do 12 sets of knee extensions).

All of that being said, there was one thing that really interested me about this study. This study, much like the 50% vs. 80% Morton paper last year, included fairly frequent 1RM tests and, like the Morton paper, found similar strength gains in spite of big differences in loading. It would be cool to see a study specifically designed to investigate whether semi-frequent 1RM tests are enough to mitigate the strength advantage of high load over low load training.

Such a study could include 4 groups:

  1. A high load group only testing 1RM pre- and post-training (maybe week 0 and 12)
  2. A low load group only testing 1RM pre- and post-training
  3. A high load group testing 1RM semi-frequently (maybe week 0, 3, 6, 9, and 12), and…
  4. A low load group testing 1RM semi-frequently.

If it turned out that simply hitting a 1RM every 2-4 weeks was enough to ensure a solid rate of progress, that would be very useful to know.  It would allow coaches and athletes a LOT more flexibility in designing training programs, especially in situations where strength is an important goal but not the main goal.

p.s. I plan on doing more of these short study write-ups since my time to write full articles has been severely curtailed with grad school.  Any time I DO have to write is devoted to MASS at this point.

p.p.s. That probably won’t happen, but a boy can dream.

Group Data Don’t Tell You Much About Individuals

I’ve been poking around in the USAPL dataset my last article was based on, and I came across something that’s worth a quick share.

I was interested in seeing whether your current level of strength is predictive of the rate you could expect to make gains in the short-to-medium term.  To investigate, I picked out everyone who showed up in the database multiple times.  Since the date of each competition was reported, I could calculate the rate of strength gain or loss per day between meets using this formula:  (second total – first total)/(first total × days between meets) = rate of strength gains.

For example, if someone totalled 1200 on March 4th, and then totalled 1260 on May 13th of the same year, their rate of strength gains would be (1260 – 1200)/(1200 × 70) = 0.07% stronger per day.

The only people I removed from the dataset were very clear outliers (i.e. z-scores of ±8 or more) who pretty obviously either had a good meet and then got injured in their next meet (so they posted a total way below what they were capable of in the second meet, showing an unrealistic loss in strength), or vice versa (they posted a total way below what they were capable of in the first meet, showing an unrealistic gain in strength).

I used allometrically scaled strength instead of absolute strength to account for body size (i.e. you may expect that someone who weighs 150lbs would struggle to add to a 1500lb total, whereas someone who’s 300lbs would have no problem adding to a 1500lb total).

Here were the results for men:

And here were the results for women:

If you looked at these two graphs and thought to yourself, “hey, the relatively weaker people may have made slightly faster progress, but there’s really not much of a relationship at all here,” you’d be correct.  The r2 value with a simple linear regression was only 0.06 for men, and 0.12 for women, meaning variation in strength only explained 6-12% of the variation in rate of progress.  That’s counterintuitive because we assume that weaker people will predictably make faster gains than stronger people – while that relationship did show up, I’d wager that most people wouldn’t expect initial relative strength to be such a weak predictor

Now, however, let’s look at the data expressed another way.  In the graphs below, I grouped people based on their initial relative strength levels.

Here’s how it looks for men:

And here are the women:

These graphs come from the exact same data, without any sort of underhanded manipulation.  I decided how large to make each range of strength to group people together before analysis, and I didn’t tinker with those ranges or go back and fiddle with any data to get a better fit.  On a group level, rate of progress declines almost perfectly linearly for men as relative strength increases.  For the women, there’s an almost perfect exponential decrease in rate of strength gains as relative strength increases.

However, these very clear group trends mask the tremendous variability between individuals.

This is a challenge we need to deal with when approaching scientific data.  Studies tend to report changes at the group level and differences between groups, but as you can see, there’s a lot of individual variation lurking beneath the surface.

Assuming that the characteristics of a group accurately describe all the individuals in that group is (depending on the circumstance) either a fallacy of division or an ecological fallacy.  They’re easy traps to fall into, even among bright people.  When you discuss the results of a study, I think it’s important to work the phrase “on average” into your discussion pretty liberally when describing group-level results.  As a reader/listener, you should assume those “on average”s are peppered throughout the discussion, even when they’re not explicitly stated.  That will help keep you from falling into this very pervasive and sneaky trap.

Now, don’t get me wrong:  it’s not that there’s anything wrong with knowing/reporting group averages.  They’re extremely valuable as a starting point.  As a coach, knowing that relatively weaker people tend to progress faster than relatively stronger people is worthwhile when setting up a program with a set progression scheme, for example.  You may want to start weaker people off with a faster progression scheme, and stronger people with a slower progression scheme.  However, you need to be aware that the weaker person may need to progress slower, or the stronger person may be able to handle a faster progression scheme – they can be different from the group averages without being particularly abnormal.  The same applies to essentially any training variable, from volume to intensity to frequency to exercise selection, etc.  Group data are great for establishing a starting point, but individual experimentation is needed past that point.

If you’re interested in science and value thorough and honest data analysis, you’ll probably like the research review I’m launching with Eric Helms and Dr. Mike Zourdos.  You can pick up the first copy for free here, or by clicking the image below.

Thanks again to /u/ferruix for curating the data over at OpenPowerlifting, and /u/TechnoAllah for hooking me up with the complete dataset.  Also, thanks to Andrew Vigotsky for inspiring this article.

What Everyone Gets Wrong About FFMI and the “Natty Limit”

I constantly see the claim that an FFMI of 25 is the “natty limit” of muscularity, and that it’s impossible (or at least unbelievably unlikely) that you can get more muscular than that without the use of steroids.

To backtrack a bit for people who feel like they’re stepping into the middle of a conversation, the Fat-Free Mass Index (FFMI) is a measure of muscularity.  You calculate it by dividing lean body mass (in kg) by height (in meters) squared.

FFMI formula

It’s essentially the same formula as Body Mass Index (BMI), but for lean body mass instead of total body mass.  The higher your FFMI, the more jacked you are.

It’s been proposed by several prominent members of the online fitness community that no drug-free lifters can attain an FFMI above 25 – if someone has an FFMI over 25, you know for sure they’re on drugs.  The less extreme view is that one or two rare outliers may be able to attain an FFMI over 25 without drugs, but doing so would be so incredibly unlikely, that you can still be 99% sure someone’s on the sauce if their FFMI exceeds 25.

In this article, I want to explain why that position is probably wrong or, at the very least, why there’s insufficient evidence to make such a statement.

This is a topic I’ve addressed before, but:

  1. It was in a rather dry methodology section in a previous article.  It wouldn’t surprise me if most people simply skipped this discussion to get to the more exciting stuff.
  2. This is a claim I still see all the time (like, seriously at least once or twice a day), so I think it deserves its own article to debunk it once and for all.

The claim that an FFMI of 25 is the “natty limit” can be traced back to this study:  “Fat-Free Mass in Users and Nonusers of Anabolic-Androgenic Steroids” by Kouri, 1995.

To pull a quote from the discussion of this article:  “In an examination of 157 athletes, comprising 83 steroid users and 74 nonusers, we calculated normalized FFMI using height, weight, and body fat based on skinfold measurements.  With this simple measurement, we found that athletes who had not used steroids all had values of <25.0, whereas a large proportion of steroid-using athletes easily exceeded this limit.”

That seems pretty cut and dry, right?  As I’m sure you can surmise from the introduction, I think we need to dig a bit deeper.  I’ll be pulling a lot of direct quotes from the study, but the full text is available for free (and it’s not overly technical), so I’d encourage you to read it for yourself.

What the Researchers Did

From the study:

“One hundred fifty-six men in a large controlled study of athletes recruited at gymnasiums in the Boston and Los Angeles areas, were administered physical examinations as part of a larger study (14).  These physical examinations included determinations of height, body weight, and body fat, the latter computed from the sum of six skinfold measurements using an equation derived from the data of Jackson and Pollock.”

That doesn’t tell you all that much about the people included in the trial, so I tracked down the prior study that expanded upon the inclusion criteria:

“We advertised in four gymnasiums in the Boston, Mass, area and in three gymnasiums in the Santa Monica, Calif, area to recruit subjects.  We offered $60 for a confidential interview to any male aged 16 years or older who had lifted weights for at least 2 years.”

This is our first red flag:  If you’re designing to study to see what the limits of drug-free muscularity are, you’d want to make sure your subjects are actually at least near their own genetic ceilings.  As it is, the only requirements were being at least 16 years old, and lifting weights for at least two years.  I hope we can all agree that a) most gym-goers don’t train particularly effectively and b) most people aren’t closing in on their genetic limits after just 2 years of training.

Now, it’s likely that there were a few subjects who were actually pretty close to their muscular limits. 1  However, odds are very good that most of the participants were just typical gym-goers – not the population you want to study if you’re interested in the limits of drug-free muscularity.  At the very least, there was an incentive for anyone to participate (getting paid $60), and no methods in place to specifically screen for people who were nearing their limits.

It’s not uncommon to re-analyze data that had been collected for a separate study.  However, it’s important to make sure the data are equipped to answer the research question proposed in the new study.  In this case, they aren’t.

The next few paragraphs discuss how some of the men didn’t have skinfold measurements and couldn’t be included in the analysis, and how an extra batch of subjects from a study in progress were added, leaving them with a pool of 157 subjects.  “Of these, 74 (47%) had never used steroids (henceforth called ‘nonusers’) and 83 (53%) had used steroids (‘users’).”

This is our second red flag:  If you’re designing a study to assess the limits of any human trait, you’d better make sure your sample size is larger than 74 individuals.  Even if you have a sample of 74 exceptionally tall people, you’re probably not going to find any 8′ people (the world record is 8’11.1″).  Even if you have a sample of 74 fast people, you’re probably not going to find anyone who runs a 9.8s 100m (the world record is 9.58s).  Even if you have a sample of 74 exceptionally strong people, you’re probably not going to find any 600lb benchers (the world record is 738.5lbs).  People who are 8′ tall, run a 9.8s 100m, and bench press 600lbs are freaks, but not particularly close to the highest level of human attainments in those domains.

In short, if you want to know how jacked someone can possibly get without drugs, you’re going to need more than 74 subjects, regardless of who those subjects are.

To the researchers’ credit, they acknowledge this.  From the conclusion:

“Admittedly, one cannot definitively diagnose steroid use simply on the basis of the FFMI, much as one cannot make a definitive diagnosis of alcohol intoxication in a man who displayes ataxia and dysarithria upon getting out of his automobile.  In the latter case, however, the individual may be required for forensic reasons to produce a breath or urine sample.  Perhaps we could ultimately follow an analogous procedure in forensic situations with individuals displaying an abnormally elevated FFMI.”

The researchers knew that their data weren’t sufficient to assume anyone with an FFMI of 25+ was automatically on steroids.  They proposed that FFMI should work as nothing more than an initial screen.  i.e. if someone has a really high FFMI, that just means there may be sufficient reason to do a blood or urine test for steroids.

I think we can all agree that’s reasonable.  There’s a higher chance that super jacked people are on steroids than less jacked people.  However, labeling an FFMI of 25 as a hard limit for non-users was a subsequent invention of the internet.  It’s not something proposed by this study, and it’s not something the researchers themselves would agree with.

Next, the researchers plotted the FFMIs of users and nonusers and discussed their data (lengthy quote incoming):

“Figure 1 shows a plot of FFMI versus height in meters for all of the subjects in the study.  The nonusers extended up to a well-defined limit, shown as a diagonal line in the figure; many nonusers were just below this line, but non exceeded it.  On the other hand, users extended well beyond the line with 37 (45%) of the users attaining levels of FFMI beyond the uppermost of the nonusers.

The ‘cuttoff’ line has a positive slow rather than a zero slope in the figure, perhaps because the factor of height-2 in the FFMI calculation does not fully account for the fact that human beings are three-dimensional rather than two-dimensional objects.  In other words, the tallest athletes were not only taller, but also wider and thicker than the shorter athletes of apparently comparable muscularity; thus, the tallest athletes scored somewhat higher on the FFMI calculation.  Our clinical impressions supported this speculation.  During the preparation of this article, we called in the shortest nonuser (height 1.59m) and one of the tallest nonusers (height 1.93m) and remeasured both of them.  The shortest athlete displayed an FFMI (without normalization) of 23.5, whereas the tall one scored 25.4.  however, on visual inspection, the short athlete appeared more muscular than did the tall one.

To generate an approximate correction for this apparent effect of height, we calculated the slope of a regression line drawn through a plot of all the ‘elite’ nonuser athletes with FFMI scores of 22 or above. (We limited the regression calculation to this subgroup because we felt that the distribution of the elite group would more closely reflect the dictates of physiology and not be confounded by lack of achievement, as in the less muscular subjects.) This calculation yielded a slope of 6.1kg/m2.  We then used this value to calculate a ‘normalized’ FFMI, in which the FFMI was normalized to that of a 1.8-m athlete (the mean height of the nonusers):

Normalized FFMI = FFMI + 6.1 x (1.8 – h)

where h is height in meters.

Using normalized FFMI, we obtained the plot shown in Fig. 2.  Again, it can be seen that the nonusers ‘stop’ abruptly at a maximum value of 25.0, whereas many users extend well beyond this limit.”

First, let’s take a look at the data they’re referring to:

Next, let’s unpack these paragraphs:

1)  The authors acknowledge that FFMI itself may not be a great way to assess muscularity in the first place. 2

Something like a version of the corpulence index (CI) applied to lean mass may work better.  While BMI is mass divided by height squared, CI is mass divided by height cubed (to account for the fact that humans are three-dimensional).  The FFMI formula is the same as the BMI formula, except that it only deals with lean mass instead of total mass; lean mass divided by height cubed (similar to the CI) may work better.

On the other hand, other work has shown that there’s actually a negative relationship between BMI and height, suggesting that you should instead raise height to a power smaller than 2 to accurately scale body mass to height.  The same may apply to lean mass as well.

TL;DR:  scaling is tricky, and it’s not even clear that FFMI is actually a valid, meaningful measure to compare human muscularity.

2) Going by raw FFMI values, there was actually at least one individual in the nonusers group who had an FFMI above 25.

One guy was 1.93m tall (6’3”) with an FFMI of 25.4, meaning he had about 94.6kg (208.5lbs) of lean mass.  I shouldn’t need to tell you this, but that’s pretty damn big.  For context, that means he’d step on a bodybuilding stage at 7% body fat at around 102kg (225lbs).  The FFMI “cutoff” of 25 doesn’t arise until the researchers applied a “correction” to their data.

3) The correction they applied 3 was post-hoc and fairly arbitrary.

In the methods section of the paper, the authors state that their intention was simply to calculate FFMIs of the athletes using the typical FFMI formula (lean mass divided by height squared).4  They didn’t decide to make any adjustments until they’d already collected their data.  That’s not necessarily a “bad” thing, but results you only get after doing some post-hoc fiddling with your data aren’t supposed to be heralded as the main finding of a study; they typically just get a brief mention in the discussion.

You can look at the scatterplot itself to see that correction they applied probably wasn’t necessary.  If there was an overall positive trend between FFMI and height, a correction may be warranted.  In this case, it’s pretty clear that the relationship between FFMI and height is either weak or nonexistent.  The line drawn through the data isn’t a trendline; it’s just an arbitrary line on which the drug-free people with the 1st, 3rd, 6th, and 13th highest FFMIs in the study fell.

To calculate the correction (which they admit is an “approximate” correction), they picked a subgroup of the nonusers and looked at the relationship between height and FFMI.  Importantly, they didn’t report a correlation coefficient to tell us the strength of the relationship; if it wasn’t a strong relationship in the first place, it would seem odd to use it to calculate the correction.

TL;DR:  without a correction, there were one or two people in a random sample of 74 gym rats with an FFMI over 25.  The authors’ justification for applying a correction is pretty flimsy, and the correction was a post-hoc addition in the first place.

4) The authors themselves don’t even think the correction “worked.”

This is pretty easy to miss if you’re not paying attention, but the authors state:

“During the preparation of this article, we called in the shortest nonuser (height 1.59m) and one of the tallest nonusers (height 1.93m) and remeasured both of them.  The shortest athlete displayed an FFMI (without normalization) of 23.5, whereas the tall one scored 25.4.  however, on visual inspection, the short athlete appeared more muscular than did the tall one.”

Here are those two individuals:

FFMI Kouri Scatterplot 2

We know enough about them to calculate their “normalized” FFMIs.  It’s 24.78 for the short guy, and 24.6 for the tall guy – virtually identical.  The 0.18 point difference is effectively meaningless (around .5kg/1lb of lean mass).

The authors themselves say they thought the shorter guy seemed more muscular than the taller guy, but their formula says they’re equally jacked.  However, if they applied a larger correction to reflect that, it would mean pushing the short guy over the “magic” FFMI threshold of 25.

Next, the study goes from “okay, this isn’t great, but if we overlook some flaws, we can still probably learn something,” to “holy crap, how the heck did this even get published”:

“To further test the limits of FFMI, we obtained the heights, weights, and ages, at the time of competition, of all Mr. America winners from 1939 to 1959.  Because anabolic steroids were not available in gymnasiums during this era (Todd T, personal communication, July 1994), these athletes likely represented the maximum FFMI attainable without drugs.  The second author (H.G.P.) estimated the body fat of each athlete from contemporaneous photographs in bodybuilding magazines of the era, averaging the estimates from several photographs of each athlete. [Dr. Pope based these estimates on having performed body fat measurements with calipers on >200 men in the course of previous studies, thus giving him substantial experience in estimating fat from a subject’s appearance.]  The athlete’s face and written identifying information were obscured during this exercise to render all estimates blind.  Adequate photographs could not be found for two Mr. America winners (Park, 1952; and Schaefer, 1956).  The estimated normalized FFMIs for the other 20 athletes are shown in Table 2 and charted on the left-hand side of Fig. 3.  It will be seen that the presteroid Mr. America winners displayed a mean (+/- SD) normalized FFMI of 25.4 +/- 1.5, with only three having values of >27.0.”

Mr. America FFMI

Let’s just take this point by point.

  1. “We obtained the heights, weights, and ages, at the time of competition, of all Mr. America winners from 1939 to 1959.”  How do they know the information was accurate?  I have a copy of the book they cited as a source (The Super Athletes by Willoughby), but the book doesn’t cite a source to verify the numbers.  Right off the bat, it’s entirely possible that the reported heights and weights were wrong.
  2. “Because anabolic steroids were not available in gymnasiums during this era…”  Eric Helms has done a great job of documenting the history of steroid creation and dissemination in this article, but in short, it’s not true that steroids weren’t available all the way up to 1959.  We can be 99.9% sure that all winners before 1944 were truly drug-free, and quite confident that all winners before 1954 were drug-free (the first corroborated reports of testosterone use in US bodybuilding circles comes from the early 50s).  However, there’s a decent chance that a fair amount of the bodybuilders in the late 50s had dabbled with steroids.  This isn’t a major issue, but you’d expect more due diligence in a journal article.
  3. “…these athletes likely represented the maximum FFMI attainable without drugs.”  That’s a HUGE reach.  Bodybuilding was a tiny sport in the 1940s and 1950s, so to assume the bodybuilders of that day attained the absolute peak of drug-free human muscularity is absurd.  Compare the best athletes from the 40s and 50s to the best athletes in essentially any sport today – almost without exception, the top pros of yesteryear would be middling amateurs today as talent pools have grown.  There were even several drug-free lifters in the Kouri study with FFMIs higher than several of the Mr. America winners of this era!  I’m not going to argue that Grimek (FFMI of 26.9 in 1942), Stanko (FFMI of 27.3 in 1944), Eiferman (FFMI of 27.7 in 1948) and Delinger (FFMI of 28.0 in 1949) weren’t super jacked.  However, it’s asinine to assume they represented the absolute peak of drug-free muscularity.  In fact, we don’t even know that they were at their all-time best when they won the Mr. America.  After the organizers feared that Grimek was unbeatable in 1942, they instituted a rule saying that you were only allowed to win the contest once – all four of these men may very well have gotten more muscular after winning the contest, but they weren’t allowed to compete again.
  4. “The second author (H.G.P.) estimated the body fat of each athlete from contemporaneous photographs in bodybuilding magazines of the era, averaging the estimates from several photographs of each athlete.”  This is where I nearly spat out my coffee.  Visually estimating body fat percentages?  Based on images from bodybuilding magazines that very well may have been edited?  Is this a journal article or a bodybuilding.com thread?

You’d be totally entitled to disregard this section of the study entirely, as it doesn’t live up to literally any reasonable scientific standards.  However, I think we can take one thing away from it – unless the cited heights and weights were way off, and unless the body fat estimations were way off, this section kills the notion that an FFMI of 25 is a hard limit.

To use Stanko as an example (FFMI of 27.3 in an era where we can be 99.99% sure he was truly drug-free) – he was 2.3 FFMI points over the “natty limit” of 25.  Stanko was apparently 5’11.5” (1.816m) and weighted 223lbs (101.15kg).  An FFMI of 27.3 means he had 199.2lbs (90.37kg) of lean body mass, putting his estimated body fat percentage at 10.67%.

To have an FFMI of only 25, he could have at most 182.49lbs (82.78kg) of lean body mass, putting his body fat percentage at 18.16%.  In other words, either his reported weight was way off, one of the authors estimated he was a pretty lean 10% body fat when he was actually closer to 20%, or his FFMI was considerably higher than 25 in an era where we can be almost 100% certain he was truly drug-free.

Let’s move on to the discussion:

“These findings must be regarded as preliminary and subject to several possible methodological limitations.”

Good starting point.

First limitation:  some users may have slipped into the nonuser group.  “However, athletes were recruited under circumstances for which they had no particular motivation to lie about steroid use nor anything to gain from doing so.  Furthermore, all 74 nonusers produced urine samples negative for all steroids.  Finally, even if an occasional self-described nonuser had in fact used steroids, this phenomenon would not affect our estimates of a maximum FFMI in the region of 25 because many nonusers clustered just below 25, and it is impossible that all of the individuals in this cluster were lying.”  Fair, and reasonable.

Second limitation:  “Our sample size of 74 nonusers might not have been large enough to exhibit fully the upper limits of muscularity naturally attainable.”  You don’t say.

They go on to explain that the data from Mr. America winners were supposed to help mitigate this limitation.  The average FFMI of the Mr. America winners from 1939 to 1959 was 25.4.  Of the 20, 13 had FFMIs above 25, 8 had FFMIs above 26, and 3 had FFMIs above 27, with a peak of 28.0.  And again, it’s ludicrous to assume that one of a handful of bodybuilders before bodybuilding was even a major sport just happened to reach the absolute peak of drug-free human muscularity.  I’m sure there are errors in this data set, but those errors would need to be systematic, correlated, and huge to not completely destroy the notion that it’s impossible for any drug-free lifters to achieve an FFMI above 25.

Third limitation:  “our calculations of body fat are based on skinfold measurements taken by a single investigator, and our calculations for the Mr. America winners are based on body fat estimates from blinded examination of several photographs of the individual.  These methods are certainly prone to a degree of error.”

That’s an understatement.

“However, calculations from skinfold measurements, using the above equation, display a standard error of 3.4% of body fat and thus are sufficiently accurate for our purposes.  For example, a 1.8-m, 90kg (71-inch, 198-pound) athlete, measured at 10% body fat would have a normalized FFMI of 25.0.  If this body fat measurement were off my 3%, and true body fat were 13%, the FFMI would still be 24.2, a difference of only 0.8 units.”

Of course, the error could go in the other direction, and that same 3% error could yield an FFMI of 25.8 with an overestimation of body fat percentage.  With 9 people in the non-users group having FFMIs between 24.0 and 24.9, it’s very unlikely that at least one didn’t have a normalized FFMI above 25 that was masked by a body fat estimation error.

Fourth limitation:  “our formula may not be satisfactory for fat individuals.  Because a gain in the fat component of the body is consistently accompanied by some gain in the lean component, it is possible that fat individuals might be able to exceed substantially an FFMI of 25 without steroids.”  This is very valid.

What do they mean by “fat?”  The nonuser group had an average body fat percentage of 12.5 ± 5.5%, so it should apply to people down to at least 7% body fat, and up to people with at least 18% body fat.  I often see people say that the FFMI “limit” only applies to very lean people (i.e. sub-10% body fat), but that’s not something that can be taken away from this study.

Fifth limitation:  FFMI may not be a useful screening tool for endurance athletes because endurance athletes can take gear and still be scrawny.  Well, yeah.  That’s obvious.

Wrapping this sucker up

The idea that an FFMI of 25 is any sort of “natty limit” could only come from a really bad interpretation of one really bad study.

The study itself was not set up to investigate the limits of drug-free human muscularity.  Its sample was too small, and its inclusion criteria were way too lax.  The raw data themselves don’t support an FFMI “limit” of 25.0 (as one or two subjects out of just 74 had FFMIs above 25) – that came about only after a fairly arbitrary post-hoc “correction.” Furthermore, with the error inherent in estimating body fat percentages via calipers and the cluster of people with FFMIs just below 25 after “correction,” it’s very likely that at least one or two people out of 74 had normalized FFMIs above 25.0 that were masked by body fat misestimations.

Furthermore, the presented FFMIs of Mr. America winners pre-1960 should either destroy any notion that an FFMI of 25 is a “limit,” really shake your confidence in the study as a whole (again – visual body fat estimations?  Seriously?), or both.

Finally, the authors themselves say that their findings should be regarded as preliminary, and that an FFMI cutoff of 25 should only be used as an initial screening tool.  They don’t propose that everyone with an FFMI over 25 is on steroids.  They just think that an FFMI over 25 should be a red flag to warrant actual drug screening.

Make no mistakes – this study is an example of very bad science.  It’s so flawed in so many ways that I’m really not sure how it got published.

However, the subsequent interpretations of this study have been even worse.  Anyone using this paper to argue that no drug-free lifter can attain an FFMI of 25 without drugs either doesn’t know how to critically appraise and interpret research, they’re purposefully misrepresenting it to make an invalid point, or they’re just parroting the idea from some other source without actually reading the paper in the first place.

It’s baffling to me that the notion of a FFMI “natty limit” of 25.0 ever got started in the first place.  If you’re using this paper as a guide, a more accurate interpretation is just that you’re pretty unlikely to find any or many drug-free bros in a random gym with an FFMI over 25.  But by no means does it support the notion that an FFMI of 25 is impossible or nearly impossible to achieve with good genetics and years of hard work.  If you take the data at face value, they say that not all that many people will pass an FFMI of 25 without steroids, but that people with great genetics can achieve FFMIs of 26-27+.

In fact, I think proposing a “limit” is wrongheaded in the first place, since human traits tend to be normally distributed.  That’s why I’ve always addressed this question probabilistically instead of using black-and-white terms.  Probability assessment isn’t as exciting as simplistic (and wrong) black-and-white thinking, but it’s the more rigorous and intellectually honest way to approach this question.

So in summation:  stop talking about the “natty limit.” Just stop it.  Odds are very low someone hit it before the advent of steroids, and now that steroids exist and drug tests are imperfect, we’ll never know for sure what it is (or even if it exists as any sort of hard limit in the first place).  As such, the entire concept is a silly construct that’s unproven and likely unprovable, and if it exists in the first place, no one has any earthly idea where it is.

p.s. I know I said in my last article that I’m done talking about steroids for a long time.  I stand by that.  This article just discusses a specific claim I wanted to address since I see it parroted so often.  As such, I’m filing it under “general myth-busting” and “critical appraisal of research.”

p.p.s. There’s a study being published soon that’s going to blow the idea of an FFMI of 25 as the “natty limit” out of the water.  This is just an examination of why the idea was almost fractally wrong in the first place.  Edit:  the study is up now/


  1. “the nonusers included many dedicated bodybuilders.  Several had competed successfully in ‘natural’ bodybuilding contests, two held world records in strength events, and many others were recognized by their associates as highly successful weightlifters”

  2. “…perhaps because the factor of height-2 in the FFMI calculation does not fully account for the fact that human beings are three-dimensional rather than two-dimensional objects.  In other words, the tallest athletes were not only taller, but also wider and thicker than the shorter athletes of apparently comparable muscularity; thus, the tallest athletes scored somewhat higher on the FFMI calculation.”

  3. Normalized FFMI = FFMI + 6.1 x (1.8 – h)

  4. “After calculating percentage bodyfat for all of the subjects, fat-free mass was calculated using the following formula:

    fat-free mass = body weight x [1 – (% body fat / 100)]

    FFMI was then calculated as follows:

    FFMI = fat-free mass x height-2

    where weight was measured in kilograms and height in meters.