JPS Education Preface:In an attempt to diversify the content and ideas that readers of our blog are exposed to, we have contacted a number of individuals within the industry who we respect and admire, and asked them if they will contribute content to our blog so that our dedicated readers can be benefit from what…

JPS Education Preface:In an attempt to diversify the content and ideas that readers of our blog are exposed to, we have contacted a number of individuals within the industry who we respect and admire, and asked them if they will contribute content to our blog so that our dedicated readers can be benefit from what they know. While all the coaches at JPS and contributors to our education platform are extremely knowledgeable, we are all obviously limited to the experiences and education that we have had. By reaching out to other individuals in the industry who we consider to be exceptional in one way or another, we hope to bring to you an even greater amount of knowledge and information than we could achieve on our own. Many of these articles will be written by “competitors,” although we don’t consider them as such. These are all people who we believe embody our ‘Raising The Standard’ motto and therefore we feel privileged to give them a voice on our platform. This is the second instalment of that process.



About The Author:Jake is a natural bodybuilding and powerlifting enthusiast, he holds a Bachelors (with Honors) in Exercise Science, and is a USAPL Club Coach and NAMS Certified Nutrition Coach. He will also soon have his Masters and CSCS accreditation. And if all this wasn’t enough, Jake is also conducting research looking at RPE/RIR in resistance training, which is why we wanted to reach out and get his thoughts on the matter. You can follow Jake and all his anime antics on Instagram @jakeremmert.

A Case For RIR

In recent years, it’s gotten popular for coaches to program training using RIR (repetitions in reserve), where lifters are instructed to perform sets to a certain point short of muscular failure (i.e. 3 sets of 12 reps with 2RIR). This has all stemmed from the lifting-specific RPE scale put forth by Mike Tuchscherer in his 2008 Reactive Training Manual, where a 10RPE corresponded to a maximum effort, a 9RPE meant one more rep could have been completed, and so on. Quick note: for the rest of this article, I’ll just refer to this method as “using RIR,” since that’s easier to type and it’s how the method is colloquially known anyway.

So, why is using RIR so popular and does it actually have evidence to back it up?

For the first half of that question, it’s pretty simple. We need some way to quantify training effort, and many bodybuilders and recreational lifters find it more intuitive to simply rate RIR, rather than rate RPE based on RIR. I think part of this is that bodybuilders are typically more prone to care about how a set feels, not so much about the weight they’re using like powerlifters do. Mike T’s RPE scale includes ratings such as 9.5RPE (meaning no more repetitions could be done, but a little more load could be), which is incredibly useful in strength training but isn’t as applicable to hypertrophy training. Because of that, I think the RIR-based RPE scale is the way to go for powerlifting (or velocity-based training, but that’s outside the scope of this article), but rating raw RIR is probably easier for bodybuilding purposes.

Also, it’s pretty clear now that a wide range of intensity can bring about similar growth (6,7,11), so as long as you pay attention to relative intensity (proximity to failure), and make an effort to add load to the bar over time via whatever progression method you prefer, you’ll have the intensity piece of the hypertrophy equation taken care of. Using RIR suits this purpose perfectly; although the ratings you give are subjective, the scale is still a source of objectivity in your training to modulate relative intensity.

RIR has some other benefits to offer as well. For one, it standardizes set-to-set training effort, making fatigue accumulation more predictable and allowing you to see trends in the effort/fatigue/adaptation relationship and troubleshoot your program. One could argue that training to failure standardizes things just as well, but it also increases time course of recovery (8)and could sabotage micro- and mesocycle volume accumulation (10)… not the best trade-off. Instead, it probably makes sense to stay shy of failure on most sets, and what better way to plan when exactly to stop a set than by using RIR? Lastly, it encourages you to be more mindful during your sets, improving your mind-muscle connection, which has been shown to augment muscle growth (12).

Right now, you may be thinking, “why would I not use RIR? It sounds perfect!” Well, not so fast. All of this hinges entirely on your ability to rate RIR accurately. For some insight into this, we have to fire up Old Faithful (AKA PubMed) and start digging.

Existing Scientific Evidence

There have been two main laboratories fighting the good fight with the power of science to formalize and validate RIR in the literature. Hackett el al. kicked it off in 2012, having pretty highly trained male bodybuilders attempt to rate their “estimated repetitions to failure” at the completion of 10 reps in the squat and bench press, then continue to failure to assess their accuracy. After 5 sets of each exercise like this, the subjects were found to be able to accurately rate their RIR, especially in later sets (3). In 2017, Hackett’s lab repeated the same protocol with a much larger sample of both sexes, this time using the machine chest press and leg press, finding more accurate ratings when given while closer to failure and when given during the chest press as compared to the leg press, and ratings were accurate within 1 rep when given within 3-5 reps from failure. Interestingly, there was no difference based on training experience (1). More evidence the following year agreed with their initial study that accuracy improves across multiple sets and hinted at the possibility that accuracy could improve across multiple sessions of practice (2). Finally, just last year they published their most recent effort (4), suggesting that the actual number of repetitions done in a set seems to be the strongest correlate with RIR accuracy – the higher the reps, the harder it is to accurately judge.

The second group generating a lot of literature in this area is Zourdos et al., focusing more directly on Mike T’s RPE scale. In 2016, they validated RIR-based RPE alongside bar velocity and %1RM, showing its use as a method to prescribe intensity (15). A few years later, they tested RIR-based RPE accuracy directly, having subjects do a set of squats to failure with 70%1RM, calling out when they felt they reached a 5RPE, a 7RPE, and a 9RPE(14). They showed that rating accuracy improved when closer to failure and when fewer reps were done in a set (agreeing with Hackett). They also found a potential relationship with more training experience (disagreeing with Hackett), but no relationship between accuracy and experience using the actual RPE scale. Some other studies out of Dr. Zourdos’ lab from Ormsbee and Sousa have shown similar results with bench press (9)and deadlift (13), and found that ratings given during bench press were more accurate than during squat or deadlift – harkening back to Hackett once again. During his PhD research, Dr. Eric Helms also showed that trained lifters could use RIR-based RPE to accurately choose loads to reach a target number of reps at a certain RPE (i.e. a set of 8 at 8RPE) (5).

Let’s take a step back and see what sort of picture the research is painting. In general, RIR ratings are pretty accurate when within 3-5 reps from failure, accuracy improves across multiple sets, and the lower the total reps in a set, the easier it is to judge RIR accurately. There also appears to be a trend where accuracy is better either in exercises using smaller muscle groups, or using the upper body versus the lower body. And now with the disagreement between the Zourdos and Hackett studies, the door is left open for training experience to be a factor.

That’s all well and good, but we have to acknowledge the limitations too. First and most notably, only the chest press, leg press, squat, bench press, and deadlift have been tested; it’s possible that other exercises (especially single-joint) would lead to different results. Also, the way Hackett et al. had their subjects rate RIR isn’t how lifters in the real world do it. I don’t know about you, but I certainly don’t do 10 reps, pause for 5 seconds to rate my RIR, then continue to failure. Zourdos, Ormsbee, and Sousa used multiple ratings, which is great because lifters don’t only have a single shot to judge their RIR. But, the two or three ratings given by subjects here still isn’t quite how people actually do this in practice. Instead, lifters are able to “feel out” a set, and judge their RIR on a rep-by-rep basis, and I think that makes a difference in how accurate one can be. Also, the subjects in these studies rated RIR-based RPE, not RIR directly. That’s notable because many people find it more intuitive to simply rate RIR, rather than go through the effort to think about their RIR, subtract that number from 10, and give the corresponding RPE. I’d also love to get more clarity on if accuracy improves across multiple sessions. The 2018 Hackett study only included two sessions with pretty neutral results, but I’d love to see a longer study on this. That way, we could see if people who start off being super inaccurate get the hang of it eventually, and about how long it takes for that to happen – or, if some people simply aren’t in tune with the RIR gods, maybe based on personality traits or something like that. Lastly and interestingly, no study looking at RIR accuracy to date has used untrained subjects – it almost feels like blasphemy to mention a benefit of using untrained subjects, but in this case it could be very helpful to determine 1) if training experience is a factor, and 2) if prescribing load via RIR targets is a viable strategy for beginners, or if they simply couldn’t hit water if they fell out of a boat (RIP Patches O’Houlihan).

So… that’s where I stepped in.

I’m currently in my final year of undergrad and lined up an opportunity to do a thesis project where I could design and conduct original research. While I can’t say much in detail about the study yet, my advisers and I designed it to engage with several of the aforementioned points that are missing in the RIR literature. By having both trained and untrained subjects perform both single- and multi-joint exercise while giving multiple raw RIR ratings, we hope to gather data that will start to fill in the remaining gaps in the evidence. Once we can sit down and analyze the data (soon) and publish it (less soon, but not too far off) I’ll be very excited to share the results of a study that I believe is an important addition to the literature and can shed some light on the less- or never-explored aspects of RIR.

Application

Despite the limitations of the existing data, I think it’s still a safe bet to program with RIR. I have a hard time believing that accuracy during exercises other than those tested already would be drastically different. If anything, I would hypothesize that single joint movements would lend themselves to even more accurate ratings due to the trend of better accuracy when using smaller muscle groups (chest vs legs), and because there is less central fatigue present to disguise the local fatigue in the muscle, impacting your ability to rate RIR accurately.

Plus, let’s be realistic here. Is it really necessary to be able to rate RIR with perfect granularity? The main thing we’re going for is staying away from failure, without being too far away of course. Do we honestly think it matters if you rate a set at 2RIR and it was actually 3? Or even if you rate a 3RIR and it was actually 5? I personally don’t think that. You’ll still land within the effective range, and isn’t that about all we can do with all training parameters, after all? With volume, you can’t ever know the perfect number of sets for you to do, so you have to settle with getting into the ballpark that the literature provides, and then monitoring and adjusting from there. Same thing with relative intensity – as long as you’re rating pretty low RIR’s, any inaccuracy will sort itself out as you monitor and add load/reps over time. “Close enough” only counts in horseshoes and hand grenades…and RIR.

For example, say on Mondays you do bench press for sets of 12 (because what else would you do on Mondays?) and rate a certain set as 3RIR. Even if you’re off a little bit, it’s not a big deal – it’s still making you grow, because you’re probably not going to be off by 10RIR – and as you add reps or load over the weeks, you’ll naturally get closer to failure anyway, it just might take a couple more weeks than originally planned. That being said, it might make more sense to program using a small range (i.e. 3 sets of 10 at 1-2RIR) to allow for some more wiggle room and account for any small inaccuracy that could be present. Along those same lines, it might make more sense to allow a wider range for very high rep sets. Not only do we already know it’s harder to gauge RIR with higher reps, but when you get into 20-30 rep territory, there are other factors disguising the local muscular fatigue (metabolite buildup, pain, psychological trauma, a desire to be done with this stupid set already) that will make it even more difficult. Maybe give yourself more wiggle room, and just trust the process that as you overload across the mesocycle, true muscular failure will come and find you at some point.

As a final thought, another cool thing you can do is progress RIR over a mesocycle, something like:

Week 1: 3-4RIR

Week 2: 2-3RIR

Week 3: 1-2RIR

Week 4: 0-1RIR

Week 5: 4-5RIR (Deload)

This not only provides another form of progressive overload, but also offers an opportunity to train to failure at a time in the mesocycle when that fatigue trade-off makes the most sense (right before a deload), allowing you to cash in on any potential benefit that failure training might offer. As a bonus, that exposure to failure training gives you a chance to audit your RIR ratings to see if you’re actually as accurate as you thought, and use that feedback to improve your accuracy over time. When doing one of those failure sets, mentally take note of your RIR while continuing to failure, and see if your rating was accurate.

TLDR & Wrap Up

Well, I hope you enjoyed this foray into the realm of RIR. There’s a reasonable amount of evidence backing its validity for use in practice, but still quite a bit less than would be ideal. However, I think this is one of those cases when we don’t really need tons of research to feel comfortable in a method’s utility. Like I mentioned before, even if your RIR ratings aren’t quite spot-on, the whole point is just to stay a bit away from failure, while having a more defined stopping point than “eh, just stop when it feels pretty tough.” RIR ticks that box, and anecdotally it seems like people can be accurate enough (especially if they use occasional audits) to use the system effectively. So go forth, train hard, and pay attention to your RIR, because even if you’re a little off, you’re probably still close enough and overload will take care of the rest.

References

1. Hackett, DA, Cobley, SP, Davies, TB, Michael, SW, and Halaki, M. Accuracy in Estimating Repetitions to Failure During Resistance Exercise. J Strength Cond Res31: 2162–2168, 2017.

2. Hackett, DA, Cobley, SP, and Halaki, M. Estimation of Repetitions to Failure for Monitoring Resistance Exercise Intensity: Building a Case for Application. J Strength Cond Res32: 1352–1359, 2018.

3. Hackett, DA, Johnson, NA, Halaki, M, and Chow, C-M. A novel scale to assess resistance-exercise effort. J Sports Sci30: 1405–1413, 2012.

4. Hackett, DA, Selvanayagam, VS, Halaki, M, and Cobley, SP. Associations between Perceptual Fatigue and Accuracy of Estimated Repetitions to Failure during Resistance Exercises. J Funct Morphol Kinesiol4: 56, 2019.

5. Helms, ER, Brown, SR, Cross, MR, Storey, A, Cronin, J, and Zourdos, MC. Self-Rated Accuracy of Rating of Perceived Exertion-Based Load Prescription in Powerlifters.J Strength Cond Res31: 2938–2943, 2017.

6. Lasevicius, T, Ugrinowitsch, C, Schoenfeld, BJ, Roschel, H, Tavares, LD, De Souza, EO, et al. Effects of different intensities of resistance training with equated volume load on muscle strength and hypertrophy. Eur J Sport Sci18: 772–780, 2018.

7. Lim, C, Kim, HJ, Morton, RW, Harris, R, Phillips, SM, Jeong, TS, et al. Resistance Exercise–induced Changes in Muscle Phenotype Are Load Dependent: Med Sci Sports Exerc51: 2578–2585, 2019.

8. Morán-Navarro, R, Pérez, CE, Mora-Rodríguez, R, de la Cruz-Sánchez, E, González-Badillo, JJ, Sánchez-Medina, L, et al. Time course of recovery following resistance training leading or not to failure. Eur J Appl Physiol117: 2387–2399, 2017.

9. Ormsbee, MJ, Carzoli, JP, Klemp, A, Allman, BR, Zourdos, MC, Kim, J-S, et al. Efficacy of the Repetitions in Reserve-Based Rating of Perceived Exertion for the Bench Press in Experienced and Novice Benchers. J Strength Cond Res33: 337–345, 2019.

10. Pareja-Blanco, F, Rodríguez-Rosell, D, Aagaard, P, Sánchez-Medina, L, Ribas-Serna, J, Mora-Custodio, R, et al. Time Course of Recovery From Resistance Exercise With Different Set Configurations. J Strength Cond Res, 2018.

11. Schoenfeld, BJ, Grgic, J, Ogborn, D, and Krieger, JW. Strength and Hypertrophy Adaptations Between Low- vs. High-Load Resistance Training: A Systematic Review and Meta-analysis. J Strength Cond Res31: 3508–3523, 2017.

12. Schoenfeld, BJ, Vigotsky, A, Contreras, B, Golden, S, Alto, A, Larson, R, et al. Differential effects of attentional focus strategies during long-term resistance training. Eur J Sport Sci18: 705–712, 2018.

13. Sousa, CA. Assessment of Accuracy of Intra-set Rating of Perceived Exertion in the Squat, Bench Press, and Deadlift (Doctoral dissertation, Florida Atlantic University).

14. Zourdos, MC, Goldsmith, JA, Helms, ER, Trepeck, C, Halle, JL, Mendez, KM, et al. Proximity to Failure and Total Repetitions Performed in a Set Influences Accuracy of Intraset Repetitions in Reserve-Based Rating of Perceived Exertion.J Strength Cond Res, 2019.

15. Zourdos, MC, Klemp, A, Dolan, C, Quiles, JM, Schau, KA, Jo, E, et al. Novel Resistance Training-Specific Rating of Perceived Exertion Scale Measuring Repetitions in Reserve. J Strength Cond Res30: 267–275, 2016.