Project Momentum 17-1 Results
By Mike Tuchscherer

Project Momentum 17-1 Post Project Analysis

I’ve often heard people suggest that the number of reps you can do with 80% loads is indicative both of fiber type distribution and how you should train to see the most progress.  The fiber type distribution claim wasn’t so interesting to me as a coach, but the training claim was.  More specifically, the claim as I came across it was something like this:

Lifters who can do low reps with 80% of 1RM are fast-twitch dominant and therefore should train with low reps per set.  That will allow them to progress the fastest.

I am aware of some studies looking at whether reps-at-a-given-percentage correlate to a fiber type distribution, but again, I’m much more interested in performance.  And I wasn’t able to find anything that tested the claim underlined above.  So we sought to test it in a practical setting.

What did we find?
First, a bit about the basic setup….  We began training with a testing week where lifters tested 1RMs and max reps with 80% on all three competition lifts.  Lifters were then broken into four groups based on reps with 80%.  Special effort was made to balance for gender, wilks score, and training age.
Group A scored lower-than-average reps with 80% and were placed on a lower rep / higher intensity program.  Group B scored low reps with 80% and were placed on a higher rep / lower intensity program.  Group C scored higher-than-average reps with 80% and were placed on a low rep / high intensity program (same as group A).  Group D scored high reps with 80% and was placed on a high rep / low intensity program (same as Group B).

Reps @80% Program Intensity
Group A: Low High
Group B: Low Low
Group C: High High
Group D: High Low


There were three main findings.

  1. Lifters seem to make better progress from doing what they are bad at. This was the opposite of what I had originally heard.  But the effect was far from dramatic.  In fact, I’d say it only gives you a nudge as to which direction you should take your experimentation.
  2. Injured lifters were much more likely to have a low training age (especially when combined with higher calendar ages), and lower prior training volumes as well. In short, their work capacity was not prepared to handle the training and injuries were higher as a result.
  3. Those who felt recovered and enjoyed their training did better overall. Spending effort on improving recovery and doing training that you enjoy seems to be effort well spent.  It’s not clear that it’s causal as this experiment wasn’t intended to answer that question, but it almost certainly isn’t harmful.  It also wasn’t clear which modalities were most effective for improving recovery.  So the recommendation here is to do those things which help you feel better.

The Program
The RTS coaches and I discussed the programs quite a bit before the project began.  The programs are very similar, but with some key differences.

Both programs used four training sessions per week with training sessions that combined upper body and lower body training.  Required equipment was kept to a minimum so exercise substitutions could be minimized.  Exercise selection, number of working sets, and RPE was identical for the two programs.  Squat was trained 2x weekly with additional leg training 1x weekly (lunges, etc).  Bench was trained 4x per week.  Deadlift was trained 2x per week.  In the second half of the program, an additional session of Snatch Grip SLDL was added (~8 reps per set).

Both programs utilized singles at 8RPE throughout the program both for competition lifts and assistance lifts.  This was done partly because I feel that it creates a positive training effect and partly to reduce any chance that the low intensity group would suffer from a lack of familiarity with heavier weights.

The key difference between the low rep program and the high rep program comes with the back-off sets.




As you can see, two reps per set separated the two programs.  The reps for the supplemental work was the same.

Two reps per set isn’t a lot.  This was something we discussed before the project.  We could have made the difference between groups greater, but we ultimately decided that we didn’t want to issue training that would be in some way unrealistic from what we would issue in a real life one-on-one coaching scenario.

The two-rep difference in the rep sets did drive a difference in the overall NL and tonnage of each program.  But this was necessary as we felt it was more relevant to control number of working sets and RPE.  There’s no way to keep working sets, RPE, and NL the same without it being essentially the same program.

We had many, many more lifters that signed up for this year’s project.  There were more hoops for them to jump through as well. By the end of the project, we had 193 respondents – nearly double what we had last year.

RCO_5309The average lifter was an 88kg male lifter, 29 years old with a training age of 5.7 years and a starting wilks of 337.  The average gain on the total across all groups was +20.5kg (+8kg Squat, +5kg Bench, +7.5kg Deadlift).  The average wilks gain was +14 wilks points.  Bodyweights ranged from 46.3kg to 153kg.  Ages ranged from 18 to 61 years old.  Training ages ranged from 6 months to 55 years.  Wilks scores ranged from 215 to 492.  There were 177 men and 16 women.  Lifters were required to provide feedback via questionnaire and also by using the free RTS apps (Training Log and TRAC primarily).

Compared to last year’s project (which was already quite well trained, in my opinion), this project had lifters who were more experienced, stronger, and spanned a wider range of ages, body weights, and time under the bar.

A quick word on average reps with 80%…
At initial testing, the average participant scored 8.6 reps with 80% of their 1RM in a given lift.  Bench was the fewest with an average of 8.2 reps.  Deadlift was the most with an average of 8.8 reps.  Squat averaged 8.7 reps.  This number was used as the dividing line between “low reps @80%” and “high reps @80%”.

Who did best with the High Intensity Program?
Groups A and C performed the High Intensity program.  Group A scored low reps with 80%.  Group C scored high reps with 80%.



Reps @80% Program Intensity Avg total gain (kg) Median Gain Participants Men/women Avg Wilks
Gr A: Low High 23.1 21.8 24 20/4 331
Gr C: High High 25.9 27.6 62 58/4 361


Note:  The y-axis of the above graph is a percentage rather than a number of respondents because of the difference in group sizes.  There were simply fewer participants who scored lower on the 80% rep test than scored higher.

Most people did quite well on the program, which may make it more difficult to see the effects we want to see.  Simply too many gains!  But there does seem to be a small indication that lifters who scored high reps on the 80% rep test fared better on the high intensity program.

Who did the best with the Low Intensity program?
Groups B and D performed the Low Intensity program.  Group B scored low reps with 80%.  Group D scored high reps with 80%.



Reps @80% Program Intensity Avg total gain (kg) Median Gain Participants Men/women Avg Wilks
Gr B: Low Low 31.9 25 11 11/0 340
Gr D: High Low 22.3 22.5 63 58/5 359


Again, most lifters did quite well.  This is really important to note, but it does make it a bit harder to see differences between groups.  This program was confounded a bit by the small number of lifters who fit into Group B.  But with that said, Group B (low reps @80%) fared a bit better on the low intensity program.

I score X reps with 80%.  How should I train?
If you complete seven reps or fewer with 80%, then you would be in the “Low reps @80%” group.  If you complete eight reps or more with 80%, you would be in the “high reps @80%” group.  Most people (61%) scored either 7 or 8 reps on their 80% rep test.


Reps @80% Program Intensity Avg total gain (kg) Median Gain Participants Men/women Avg Wilks
Gr A: Low High 23.1 21.8 24 20/4 331
Gr B: Low Low 31.9 25 11 11/0 340



Reps @80% Program Intensity Avg total gain (kg) Median Gain Participants Men/women Avg Wilks
Gr C: High High 25.9 27.6 62 58/4 361
Gr D: High Low 22.3 22.5 63 58/5 359


As to the question posed in this section – how should you train – the data only gives us a nudge as to which direction to carry out your experimentation.  It seems that for most people, doing what you’re bad at is a solid strategy that can lead to some slightly better gains on your total.  But this is not always the case as there are certainly some lifters who do very well on the opposite strategy.

At this time, I think it’s important to note what the data is NOT saying.  There were only two programs tested, so the magnitude of the change in rep ranges cannot be commented on.  That is to say, if you score very low reps at 80% (perhaps four), this data is NOT saying that you’ll respond better to ever-lower intensities in your programming.  That could be true, but it very well might not be.  We just don’t know that yet.

Perhaps the most surprising result of the project was in the injury data.  Of the 193 respondents, 16 said that they suffered injuries that forced them to stop the program (8%).  No other data was collected about their injuries, so it’s unknown if these injuries forced a stop in training, if they required medical treatment or physical therapy, etc.  From reading through the comments, at least three of the injuries were not training related, which lowers the overall injury rate to not-more-than 6.7%.

So who was likely to get injured during this project?

Project-wide average Injured cohort
Age 29.5 years 31.2 years
Training Age 5.8 years 3.2 years
Squat Freq 2.5 2.2
Bench Freq 2.8 2.3
Dead Freq 1.7 1.3
Reps @80% 8.6 8.3
Starting Wilks 337 331


I don’t think the difference in age between the injured lifters and everyone else is significant.  However, the difference in training age IS significant.  Together with the other data points, it paints a picture that those more likely to be injured on this program were those who were just as strong, but with quite a bit less experience training with high workloads.

There was no effective change in injury rate between groups.

Reps @80% Program Intensity Participants Injured Injury Percentage
Gr A: Low High 32 2 6.3%
Gr B: Low Low 20 1 5.0%
Gr C: High High 74 5 6.8%
Gr D: High Low 76 5 6.6%


The injury rates between groups are remarkably close, especially when you consider the group size itself.  I don’t think any training group was shown to be more prone to injury than any other group to a notable degree.

Overall, I think this data points to the importance of doing training appropriately for your capability.  Pushing into significantly higher training volumes when you’re not prepared for it is not a good idea.  Not everyone should do “the advanced program”.  We all seem to know that, but I think data like this puts an exclamation point on it.

Heaven and Hell
You might ask what made the difference between those who had a great response to training and those who had a poor response.  Unfortunately, the data available can only paint a fairly low resolution picture of the difference, but I do feel it’s worth looking at.  For this analysis, I looked at the top 5% and bottom 5% of all respondents.

Top 5% Bottom 5%
Gain on TOT (kg) 73 -35
Age 30.7 31
Training Age 4.65 5.45
Reps @80% 8.5 8.5
Starting Wilks 322 358
Ending Wilks 367 334
Training Freq 2.5 2.5
Sleep (hr/night) 7.9 7.3
Recovery Perception 3.4 2
Recovery Efforts 1.2 1.5
% Bulking 50% 0%
% Cutting 10% 40%
% Training weaknesses 50% 40%
% Training strengths 50% 60%
Impressions 9.3 7.6
Enjoyment 8.3 7.4
Compliance 3.3 1.7


***Recovery Perception.  A value of 3.4 correlates to the following statement:  “I generally felt fairly rested / a little stressed, but overall I felt quite good.”  A value of 2 correlates to “I generally felt quite beat up during the program — more than normal.”
***Impressions.  Participants were asked to rate Project Momentum on a 1-10 scale where 1 is poor and 10 is awesome.
***Enjoyment.  Participants were asked to rate their overall enjoyment of the training sessions where 1 is “Abject Misery” and 10 is “Everyday is a Celebration”.
***Compliance was a self-report of the athlete’s compliance with the programming.  A value of 3.3 indicates that the participants only changed the programming a few times during the project (less than once per week).  A value of 1.7 indicates that these participants modified the program more than once per week.

LAM_4871Surprisingly enough, Top 5% and Bottom 5% were quite similar across most dimensions.  Top performers got a marginal amount more sleep.  Bottom 5% lifters actually did a bit MORE additional recovery work than top 5% performers.  Roughly 50% of top performers were “training their weakness”, meaning that if they performed low reps with 80%, their training was low intensity / high rep training and vice versa.  Slightly fewer of the bottom 5% were training their weakness, but again, I hardly think that’s enough to make a big impact.

Enjoyment and compliance turned out to be notably different between the Top 5% and Bottom 5%, but these aren’t easily attributable to causal factors.  Perhaps the Top 5% fared better because they enjoyed their training, but it’s also possible that they enjoyed it because it was going better.  Compliance is equally tricky – perhaps the bottom 5% would have had better results if they were more compliant with the training, or perhaps the modifications they made to the training were an attempt to keep things from going further off the rails.  There’s no way to tell from this data, but it does seem to be reasonable to suggest that lifters should put themselves in situations where they can be compliant with the program and take some enjoyment from it too while still having good recovery.  It may not be the biggest thing that matters, but it probably doesn’t hurt.

From there, I wanted to see if the kinds of recovery efforts seemed to make any difference to the athlete’s perception of recovery.

Top 5% Bottom 5%
Recovery Perception 3.4 2
Recovery Efforts 1.2 1.5
Sleep (hr/night) 7.9 7.3
Naps 4 3
Manual Therapy (ART, massage, Chiro, etc) 3 3
Extra effort on nutrition 3 5
Did nothing extra 3 3


Very little seemed to make any impact at all in the general sense.  The top 5% got a bit more sleep and more of them took naps (although we have no data on frequency or duration).  But this tiny difference surely doesn’t account for the large difference in perceived recovery or gain in Total.

The only remaining explanations for the difference in recovery is simply work capacity.  Either that or the data we have is too low resolution to spot any differences (which is certainly possible).  My hunch is that top performers had better work capacity and the little things they did were enough to keep them well recovered and adapting.  Conversely, I suspect bottom performers had worse work capacity and the stuff they were doing to recover was helpful, but ultimately not enough.

One small disclaimer about recovery methods…  While no one recovery method stood out as making a dramatic difference to the recovery of athletes, this project was not designed to detect such differences.  So the only way it would show up in an analysis like this is if the effect was overwhelming, which we know it isn’t.  So if a recovery method makes an impact on you as a lifter, use it.  Even a small improvement in your perceived recovery can yield a nice reward at the end of your training cycle.

When I stand back and look at the Heaven-Hell analysis as a whole, it looks to me like maximizing your results from any one program can be summed up as follows:

  1. Get plenty of sleep. And then get a little bit more.
  2. Eat enough food.
  3. Do things that make you feel recovered.
  4. Train your weaknesses.
  5. Organize your training in a way that allows you to enjoy it and be compliant with it.

None of these things is likely a make-or-break item, but hitting these wickets will ensure you are maximizing the benefit from any training program.

Just as with previous projects, this is not intended to be a scientific study.  This is a practical observation.  Data was collected via self-report and spot-checked via training log analysis using the free RTS apps.  We pulled out any obviously incorrect data points.  This project was limited to eight training weeks, which places it as fairly short term.  The results may be different if the length was, say, 16 weeks instead.

RCO_6306The differences in response are noteworthy considering the similarity in the programs.  It is possible that programs with a greater difference in rep range would result in more disparate results.  It’s also possible that more strata should be included – separating those at the more extreme ends of the 80% rep test from those more toward the middle.  Further, perhaps training those at the further ends of the 80% rep test spectrum with programming that is modified to a greater extent would be more beneficial.  At this point we simply do not know.  It would be interesting to test, but as mentioned elsewhere, the goal for the project was to test programming options that might realistically be used for our athletes.

There are also limitations based on the resolution of our data.  Specifically data on recovery modalities could be improved in future projects.  Perhaps it could show us something if the resolution was higher.

Volume (as measured by NL or total tonnage) was not matched in this program.  Number of working sets (which by the way is a measure of training volume) was matched.  It’s worth naming this as a potential limitation, but I don’t think it’s a consequential one.  If total tonnage was a driving factor, we would not expect the results that we got with the “high reps @80%” group (groups C and D).

If I haven’t made it clear already, I’ll say it again.  This information shouldn’t “direct” your training.  It can suggest to you something to try next.  While your own training is a n=1 situation that can’t really be generalized to everyone else, n=1 is also the only “n” that most of you care about.  So the results of your own experimentation should not be ignored.  However, if you don’t have that information, this experiment can give you a nudge as to where to take your future training.

With that out of the way, here are what I feel are the relevant take-aways from PM17-1:

  1. The number of reps you can do with 80% of your 1RM can be an indicator for which way you should take your training. If you get few reps with 80% (seven or less), then you may get a better return on your 1RM by including some higher rep work in your training.  If you get a lot of reps with 80% (eight or more), then you might want to test out some lower-rep training using heavier weights.
  2. Train in a way that is appropriate for your level to avoid injury. Avoid dramatic increases in training volume and/or frequency.  Build your work capacity over time (years).
  3. Spend the effort on good recovery. It’s not clear what makes the difference (although eating a lot probably helps).  But if you can find something that makes your body feel better, then do it.  Train in a way that allows you to do the things you need to do (compliance) and be happy about it (enjoyment).

(especially #2 and #3 are recurring themes from past projects, so pay attention)

There is a lot more information that could be discussed with this year’s project, so feel free to ask if you have questions.  Special thanks to all those who took the time to participate and provide results.  I hope very much that you got strong doing this project and in the future we’ll incorporate what we learned to continue making things better. Also special thanks to Mike Zourdos and all the RTS coaches who helped me think through all this data.

Before anyone asks, yes, we will be doing another project.  I’m not sure when, but stay connected to RTS in some way and we’ll make sure you know about it.
Thanks for reading!

About the Author
Mike Tuchscherer is the owner and head coach at RTS. He has been powerlifting since 2001 and since has traveled all over the world for competitions. In 2009, he was the first man from USA powerlifting to win a gold medal at the World Games – the highest possible achievement in powerlifting. He has coached over a dozen competitors at the world championships, a score of national champions, and multiple world record holders.