Velocity Training with Landyn Hickmott
I would like to start off this article by saying that the Velocity-Based Training Courses (both the VBT Theory Course and the VBT Application Course) are incredibly comprehensive to the powerlifting athlete, the powerlifting coach, and the strength enthusiast from an applied perspective. The format of the VBT Courses enables you to easily grasp the content and apply it directly into your training that same day! However, I’ve had numerous people reach out to me with some slightly more nuanced questions in relation to some of the free slides that I have shared; therefore, I thought I’d share some of the nuanced answers to those questions here. This article is long, but please feel welcome to read each individual question/answer in a separate sitting or navigate to the question(s)/answer(s) that are most applicable to you. Please also feel welcome to reach out to me on my website: landynhickmott.com. I hope you enjoy!
5 Programming Basics Questions
5 Programming Basics Answers
How Do You Suggest Starting with Velocity-Based Training?
I suggest jumping right in and starting! It doesn’t take long to get the hang of velocity-based training (VBT) and it’s certainly a fun and novel strategy to utilize in your training. For the first training block I may recommend that an athlete simply hook up the linear position transducer and perform their normal training as prescribed while recording the LRV on all sets (and other velocity metrics, such as velocity loss (VL) and the velocity of the initial repetition, if it does not detract from the training process for that specific athlete). Upon completion of the training block, the athlete/coach will perform a block review and analyze their individual training metrics to begin understanding the relationship between LRV and RPE, percentage of 1RM, repetitions performed, VL, etc. and other performance (i.e., e1RM) trends. During the Pivot (RTS) or Transition (IAPP) and prior to beginning the next training block, I may have the athlete perform the Chronic Method of Development to formulate their Individualized LRV Model (this is a new unseen chronic method to develop the entire model in a single session, rather than having to ‘waste’ a full training microcycle). Next, I may have the athlete perform the same training block (i.e., a Block Repeated macrocycle design); however, the only block modification is that now the athlete would utilize LRV (and other velocity metrics) as the primary prescription strategy (alongside RPE), rather than RPE alone. After the athlete has completed the training block, we may start to get more creative with velocity and perform some Experimental Blocks with more advanced strategies. Outlined above is simply one very basic approach of various approaches that we may take.
Can I Integrate the VBT Courses into RTS’s Emerging Strategies?
Certainly! I’m not an RTS coach nor am I an RTS athlete and therefore I don’t know everything that they do, as I certainly don’t think one can truly know what exactly each specific athlete or coach does. However, the VBT Courses have largely been inspired by much of what they do. I conceptualize the ‘endless pursuit of optimization’ if you will as a holistic process, and my area of specialization within that holistic process is VBT/LRV via the VBT Courses as illustrated in Slide 1. I conceptualize RTS’s Emerging Strategies as an incredibly comprehensive framework more so on optimizing the ‘macro strategies’, while the VBT Courses focus more so on optimizing the ‘micro strategies’. For example… How can I optimally work up to a top single at an 8 RPE with LRV and what are various sub-strategies and iterations by which I can determine what is best for me? What set and repetition schemes should I select for a specific dosage of relative volume to promote the desired neuromuscular adaptations and hypertrophy adaptations contributing to strength? How can I best autoregulate and monitor my training with velocity? Etc.
I also provide the overarching framework of how I program in VBT Application Course Lesson 11 and Lesson 12 – which has largely been inspired by RTS’s Emerging Strategies – by addressing the scientific method, the 3 primary microcycle types, the 3 primary mesocycle types, the 3 primary mesocycle designs, the 3 primary macrocycle designs, and the 3 primary mesocycle transitions. However, you certainly don’t need to be familiar with RTS’s Emerging Strategies or have prior experience in VBT to enroll in the VBT Courses as I’ve purposefully made them applicable to everyone. For example, I very briefly touch on top-down periodized approaches and address volume autoregulation for those that utilize these tools within their training despite these being less popular with how I typically program because I want it to be applicable to everyone regardless of their training ideologies.
As a final side note, typically individuals into VBT and powerlifting (and even I in a super basic sense) will cite Moran-Navarro et al.  or Odgers et al.  and state that you can take a set to failure to retroactively establish an individualized LRV/RIR profile with a few basic programming suggestions for 1RM prediction, load prescription, velocity progressions, etc. That’s great; however, for those wanting exponentially more information to optimize each ‘micro strategy’, and how you can also integrate that into a more holistic framework, that’s what the VBT Courses provide to you.
If I Don’t Use Velocity-Based Training or Have a Linear Position Transducer are the VBT Courses Still Beneficial?
Definitely! The VBT Courses are of course specifically designed for programming with VBT in powerlifting; however, you can take a considerable amount of information from them and apply it directly into your training (or your athletes’ training) even if you solely use RPE. Although all the strategies are with VBT, nearly all the strategies can also be applied with RPE alone, and I provide some average values and generalized recommendations throughout the VBT Courses for those that may be hesitant about investing in a linear position transducer. Who knows? Maybe I can convince you to turn to start using LRV…
I understand that linear position transducers are not incredibly cheap. However, based on the pieces that go into making up the entire device and the time requirements to build them (they are 3-D printed and primarily built by hand), I think they are well priced, and I don’t see them getting any cheaper in the foreseeable future. If you are interested in VBT for the foreseeable future, it’s not any more expensive than a few pieces of training equipment and considerably cheaper than travel and accommodation for most powerlifting competitions beyond the local level. If you train with a training partner or multiple training partners, I’d suggest possibly investing together in a single device and to share it during your training sessions. Maybe you can even convince your gym owner to invest in multiple devices for some of the combo racks if you train at a powerlifting focused gym. Individuals frequently ask which device I use and suggest. I use the Vitruve encoder since it has been scientifically validated [3, 4], is made from where the lead VBT researchers are (in Spain), and the people behind the company are phenomenal.
Where Did Velocity-Based Training Come From?
VBT certainly isn’t anything that new; arguably dating back to the late 1980s with some of the initial pioneering work by Yuri Verkhoshansky and R.A. Roman. Carmelo Bosco and Bryan Mann also performed some of the pre-liminary work in the mid-1990s and early-2000s. Today, the current lead researchers in velocity-based training are primarily from Spain (i.e., Juan Jose Gonzalez-Badillo, Amador Garcia-Ramos, Fernando Pareja-Blanco… the list goes on). I believe Mike’s been using VBT for powerlifting since 2009. VBT has been commonplace in semi-professional and professional team sports (i.e., hockey, football, etc.) for many years to promote velocity-specific adaptations  and I used it at the end of playing hockey in the Canadian Hockey League and it was certainly beneficial to my training then and is today in powerlifting.
Does Velocity-Based Training Increase or Decrease “Noise”?
I would argue that VBT certainly decreases noise with one small caveat: only once you understand how to use it optimally. Perhaps the largest advantage of VBT is that it enables you to be considerably more precise with programming prescription and monitoring. For example: 1) when estimating RPE/RIR, it enables you to be considerably more precise; 2) when determining e1RM, it also enables you to be considerably more precise. Furthermore, it enables you to make different objective and subjective comparisons during monitoring and block reviews to tease out different training metrics and methodologically identify which components of the training program have the strongest trends with performance (i.e., 1RM changes) from a validity and reliability perspective.
5 Programming Theory Questions
5 Programming Theory Answers
Why do You Use LRV (with RPE) as the Primary Prescription Strategy and not Velocity Loss?
From a scientific perspective, based on the meta-analytic data available to us at this moment as I am writing this article, there does not appear to be a single VL threshold that results in significantly (i.e., p < 0.05) nor meaningfully (i.e., effect size ≥ 0.20) greater strength adaptations than any other VL threshold according to appropriate meta-analytic statistical techniques. Despite this, based on the collated data somewhere around ~20 – 25% VL may be optimal for strength and hypertrophy [6-15], due to a potential minimal VL threshold of ~20% required to optimize hypertrophy (Gantois et al. 2021), and due to shifts towards late rate of force development-oriented force-time profiles [10, 11]. I typically recommend from an allocation standpoint that the greatest percentage distribution be in that 20 – 25% VL range, which is approximately 5 – 6 RPE at 70% of 1RM, 6 – 7 RPE at 75% of 1RM, 7 – 8 RPE at 80% of 1RM, 8 – 9 RPE at 85% of 1RM, and 9 – 10 RPE at 90% of 1RM. However, this certainly isn’t a definitive rule as these allocations and distributions must be individualized. I’ll certainly deviate from these considerably for certain athletes as addressed in the VBT Courses.
From a practical perspective, anybody that has programmed with VL soon discovers the plethora of limitations (there are too many to write down here in this single article) [16, 17]. If VL didn’t have limitations, we could just call it a day and use mutually exclusive VL stops. This is largely why I made that Bonus Seminar video outlining some of the rationale for integrating VL zones into LRV (and RPE) back in May 2020. Since then, there has been an explosion of longitudinal VL studies, and I had a hunch many people would be interested in employing it into their training; however, I sometimes see two sides to the VL literature in practical senses: 1) VL sometimes gets completely disregarded due to its inherent limitations; or 2) VL sometimes gets over hyped as if it contains magical strength promoting powers. I would argue that it certainly has its advantages  for minimizing neuromuscular fatigue [19, 20], maximizing neuromuscular adaptations [10, 11], and promoting skeletal muscle phenotypic adaptations [9, 21], which in turn may have practical implications; however, it should be hierarchized below LRV (and RPE). What I’ve done (based on my research, training, coaching, etc.) is essentially asked the question, “how can I integrate everything advantageous with VBT into some of what RTS has done?” In other words, how can I integrate LRV (and VL and other velocity metrics) to further optimize each ‘micro strategy’.
Do I Need to Make an Individualized LRV Model or Individualized Velocity Profile for Each Competition Lift and Each Lift Variation?
It depends. For each competition lift, I would strongly suggest formulating the LRV Model for endless programming applications as LRV is both individual-specific and lift-specific . For each lift variation, I have two general recommendations depending on the context. One, if you perform a small number of lift variations, I suggest formulating a slightly simpler individualized velocity profile for each lift variation. Two, if you perform a large number of lift variations, I suggest incorporating velocity primarily as a monitoring method (Monitoring Methods are addressed in the VBT Courses).
Is the LRV Corresponding to a Specific RPE Different Depending on the Number of Repetitions Performed?
No. One, based on the scientific literature, regardless of the percentage of 1RM (i.e., regardless of 65, 75, 85% of 1RM), and therefore regardless of the number of repetitions performed, the LRV corresponding to a specific RPE will be the same [1, 2]. However, the velocity at 1RM (V1RM) is slightly slower than the LRV for a 10 RPE during a multi-repetition set . Second, I’ve collected data on the LRV for each repetition and RPE combination for myself, and it is virtually identical regardless of the number of repetitions performed in the set and the load on the bar. However, anecdotally once you get up to sets of ≥~10 repetitions, the LRV at each RPE value may be slightly faster, but powerlifters rarely – if ever – perform sets of greater than 10 repetitions in the competition lifts; therefore, I don’t think it’s that important from a practical perspective.
In the Literature, Is the Smallest Worthwhile Change for Velocity of 0.06 m.s-1 Still Applicable?
Based off data from 2017 [24, 25], the smallest worthwhile change for velocity in relation to the load-velocity relationship was considered to be 0.06 m.s-1; however, based off more recent data from 2019  in relation to the RPE-velocity relationship it was reported that changes of 0.05 m.s-1 can change the RPE value by 2 in the back squat (i.e., a 6 RPE may be ~0.45 m.s-1, whereas an 8 RPE may be ~0.40 m.s-1 for some individuals based off this data ). Anecdotally, I typically find the LRV Decay (change in LRV per change in RPE) to be ~0.025 m.s-1 (~0.02 – 0.03 m.s-1) in the squat, ~0.035 m.s-1 (~0.03 – 0.04 m.s-1) in the bench press, and ~0.015 m.s-1 (~0.01 – 0.02 m.s-1) in the deadlift. However, some athletes will certainly fall outside of these approximate LRV Decay values; hence, why LRV Decay must also be individualized for each athlete and lift. For example, the LRV Decay may be ~0.04 – 0.05 m.s-1 in both the squat and the bench press for some athletes. Larger LRV Decay values can sometimes make autoregulating and monitoring easier, since there is a greater deviation in LRV from RPE-to-RPE. This also provides a small rationale with respect to how the VL zones (i.e., green zone) result in slightly different repetition and RPE combinations for each athlete and each lift. However, the smallest worthwhile change for velocity in relation to the load-velocity relationship and RPE-velocity relationship certainly warrants further investigation to detect what is considered a ‘meaningful change’ in practical contexts.
Should Powerlifters be Minimizing Velocity Loss as Much as Possible (0% Velocity Loss)?
No. Based on the collated VL data, when set volume is equated, there’s no meaningful difference in 1RM strength adaptations between training at 0% VL and other VL thresholds (Gantois et al. 2021). However, perhaps most importantly, based on the alternative set structure meta-analytic data, when relative volume is equated, there’s no difference in strength adaptations between alternative set structures and traditional sets (i.e., maximizing the number of repetitions that have the greatest force when total repetitions and percentage of 1RM are equated does not result in meaningfully different strength outcomes as has sometimes been mis-conceptualized) [26, 27]. Adaptations to promote more force-oriented force-velocity profiles are largely determined by training at high forces via high loads [28-31], whereas adaptations to promote more velocity-oriented force-velocity profiles are largely determined by training at high forces via fast velocities (i.e., low RPE/intensities) [5, 26, 30, 31] (please see Slide 2 for an illustration). Furthermore, training at 0% VL significantly increases early rate of force development , resulting in early rate of force development-oriented force-time profiles. However, powerlifters arguably primarily want more late rate of force development-oriented force-time profiles to optimize that load at 1RM, which is optimized by training at ~25% VL (please see Slide 3 for an illustration) . It may be argued that training all components of the force-velocity curve and force-time curve are important in more main-stream sports that involve all components; however, in powerlifting, training the high force (i.e., high percentages of 1RM) and late rate of force development (i.e., ~25% VL) components are arguably most important. Finally, when sets are equated there may be a minimal VL threshold of ~20% required to result in significantly greater hypertrophy compared to VL thresholds <~20% (Gantois et al. 2021).
To further clarify in practical contexts, it’s “impossible” to maintain 0% VL when performing multi-repetition sets [16, 17]. If it was “possible” to maintain 0% VL when performing multi-repetition sets, the concept of cross-refencing and integrating LRV with RPE/RIR would lack applicability [1, 2].
There are 3 primary scenarios to maintain 0% VL:
Perform singles only training (this is the most obvious).
Train considerably far from failure (there is large inter-individual variability; however, anecdotally at a minimum of ≥10 RIR and ≤70% of 1RM).
Anecdotally, if you perform a double at a low percentage of 1RM, the average concentric velocity of the first two repetitions may be nearly identical (especially in the deadlift); however, they will typically decrease from repetition-to-repetition.
What are the limitations of these 3 scenarios? (starting with scenario 3)
Requires endless sets to accumulate an optimal dosage of volume for most athletes [27, 32]. I don’t think most powerlifting athletes are going to be performing say for example 15 sets of doubles at 70% of 1RM regularly. Plus, who wants training to be that easy as a powerlifter?
On average most athletes are likely going to need some higher relative intensity back-off volume work. I don’t think athletes can solely perform one high peak intensity exposure per microcycle and then the remaining back-off volume work can be at say for example 70% of 1RM for sets of 4 repetitions, since strength adaptations are load-dependent [28, 29].
When training at ≥70% of 1RM, it’s “impossible” to maintain 0% VL with multi-repetition sets.
The training session will likely take longer to perform. The athlete could perform the same amount of relative volume (total repetitions at a specific percentage of 1RM) in considerably less time while still maintaining a low-moderate VL ; thereby, enabling additional training to be performed in the same total amount of training time if additional training is required/beneficial.
This will likely result in shifts towards more velocity-oriented force-velocity profiles .
3) Early Rate of Force Development-Shifting.
This will likely result in shifts towards more early rate of force development-oriented force-time profiles .
4) Rise to the challenge.
I’m not going to expand on this; however, I certainly think there is considerable value in rising to a difficult training session for numerous reasons.
If the athlete is solely performing singles, they will likely get to a point where they will want to do something different with training. To share an experience a while back now, I went through a reasonably long period of daily-maxing on the competition squat, bench press, and deadlift (I performed 6 different iterations total as part of my own ‘case study experiment’; a separate discussion in and of itself). One iteration involved exclusively singles on the back-off work (similar to an inter-repetition rest protocol with slightly longer rest), rather than performing say back-off sets of doubles or triples (which is what is typically performed with daily-max training). For example, this iteration involved working up to a top single at 9.5 – 10 RPE, followed by back-off singles at 6 – 8 RPE (depending on the session). The rationale for singles only was simply to minimize fatigue as much as possible [19, 33], whilst still accumulating the same magnitude of relative volume if I was performing doubles or triples [26, 27]. It was a lot of fun at the time, but afterwards it felt good to do something different with training.
I should address that inter-repetition rest (or subtle iterations) have sometimes been used in powerlifting in the deadlift. I believe Matt Gary has been a proponent of this in the deadlift for some athletes in certain contexts and I have utilized this technique many years ago with success; however, the primary rationale is two-fold. One, deadlifts have no eccentric component; thus, this serves to dissipate the stretch-shortening cycle  between each repetition (hence why sometimes the second repetition is easier than the first repetition if there is no 4 second reset between deadlifts). Two, deadlifts have no un-rack/re-rack component and although the set-up is crucial in all lifts, it is arguably perhaps the most important in the deadlift since one does not have to un-rack the bar to perform the lift (whereas the squat and the bench press have an un-rack component and an eccentric component).
Finally, I think this concept is sometimes confused with maximal intended concentric velocity, which isn’t anything new as it is a basic tenant of VBT dating back to the early 1990s [35-41]. In 2014, Gonzalez-Badillo et al.  demonstrated that 6-weeks of barbell bench press training 3-times per week resulted in significantly greater 1RM strength adaptations for maximal intended concentric velocity versus half-maximal intended concentric velocity (+18.2 vs +9.7%; p < 0.01). However, this is a considerably different concept than minimizing VL as much as possible (i.e., 0% VL), since velocity decreases relatively linearly from repetition-to-repetition [16, 17, 42]. Furthermore, it must also be highlighted that the benefits of maximal intended concentric velocity are primarily due to actually using a linear position transducer for velocity feedback [37, 43, 44] and that having a specific target LRV to aim for results in superior performance than when individuals are simply using RPE and told to “lift as fast as possible” .
5 Programming Application Questions
5 Programming Application Answers
Do You Suggest Using a Linear Position Transducer in a Powerlifting Competition Warm-up Room?
No. Individualized regression equations of submaximal velocity are typically inaccurate at estimating 1RM in barbell lifts in nearly all studies [24, 46-49]; hence, why I provide separate precise 1RM prediction strategies, Top Single Strategies, Base Single Strategies, etc. in the VBT Courses. The velocity of the final warm-up may help with the decision for the first attempt, and I would strongly suggest that you ensure that you have enough time to change your opener if required (keep in mind it’s typically 3-minutes prior to the start of the event). However, obviously I would strongly suggest already having a specific warm-up plan with respect to load, timing, etc. and from final warmup to attempt 1, from attempt 1 to 2, and from attempt 2 to 3, I think the decisions for load selection should be at the athlete/coach discretion, even if a linear position transducer was allowed on the platform.
Ideally you should have a comprehensive game plan for attempt selection and game day execution going into the meet. I would strongly suggest Matt Gary’s information on attempt selection and game day execution; nobody is remotely close to his level with respect to his expertise here. Sometimes, I find warm-up performance for some athletes on competition day can fluctuate and not be entirely indicative of their performance on the platform (i.e., some find the warm-up room a little hectic at certain meets, whereas the platform is the ‘more controlled’ environment where it’s time to execute). Also, I’m sure many lifters in the warm-up room wouldn’t care that much about having a linear position transducer on the bar, but for some lifters, they may not want that on the bar, which is completely understandable; therefore, it is simply respectful to the other lifts not to have it on the bar. Finally, powerlifting is a sport, and I would argue that competition execution is also largely about other personality traits (i.e., compete level, psychological skills, etc.) and competition circumstances (i.e., taking what’s there, pulling for the win, etc.) that a linear position transducer nor any artificial intelligence system simply cannot detect.
Do You Prescribe the Precise LRV Values or LRV Ranges for a Given RPE?
I prefer prescribing the precise LRV values, rather than LRV ranges for a given RPE. For example, let’s say an athlete is performing a top single at an 8 RPE and that they are performing a basic Static Load iteration (i.e., keeping the top single load static at what typically corresponds to ~8 RPE, such as 275 kg for a 302.5 kg squatter for multiple exposures). For example, let’s say the LRV for a 7.5, 8, and 8.5 RPE is 0.22, 0.20, and 0.18 m.s-1, respectively. Let’s say that the LRV for exposure 1, 2, 3, and 4 at 275 kg were 0.18, 0.20, 0.21, and 0.22 m.s-1, respectively. I’d record that these top singles corresponded to RPE values of 8.5, 8, 7.5 – 8 (recording a ‘7.75’ is probably getting a little too specific here), and 7.5 RPE, respectively based on the LRV. I prefer this over suggesting that an LRV of 0.20 ± 0.02 m.s-1 corresponds to an 8 RPE, because technically it doesn’t, since the LRV Decay (i.e., change in LRV per change in RPE) is 0.02 m.s-1 in this particular example. Furthermore, let’s say the athlete didn’t actually record the precise LRV of 0.18, 0.20, 0.21, and 0.22 m.s-1, but rather recorded that the LRV corresponded to an 8, 8, 8, 8 RPE, you wouldn’t necessarily see that progress from exposure 1 – 4 of going from an 8.5 to an 8 to a 7.5 RPE at 275 kg.
Is 1 RPE value decrease for a top single at 275 kg that much meaningful progress in 4 exposures? Who knows, it could just be more so acute fluctuations in performance; however, I find that seeing those LRV values become faster for a given load can boost confidence, which can subsequently result in greater performance just because one believes as if they are making considerably more progress, which I see as a win . For load prescription, one basic sub-strategy may comprise of prescribing an 8 ± 0.5 RPE and recording the precise LRV (cross-referenced with RPE) rather than saying that an LRV of 0.20 ± 0.02 m.s-1 corresponds to an 8 RPE. Essentially it is nearly the ‘identical’ prescription; however, the former involves being slightly more precise with the LRV values. For example, say 5 working sets of tiples were prescribed, I’d prefer knowing whether those LRV values corresponded to say a 7.5 RPE on all 5 sets or an 8.5 RPE on all 5 sets (and everything in between), rather than just saying they were all at an 8 RPE (i.e., highlighting those individual subtleties in LRV Decay).
Do You Hierarchize LRV or RPE?
I typically hierarchize LRV over RPE (but of course use both) for two primary reasons. One, based on the scientific literature, the only study to date to directly compare velocity to RPE demonstrated that velocity resulted in significantly greater improvements in the back squat and the bench press compared to RPE . Two, based on my practical experience, I find LRV-based training to result in slightly superior performance and 1RM strength outcomes compared to using solely RPE-based training for myself and my athletes. However, there may be specific scenarios that you may want to hierarchize RPE over LRV, which is essentially VBT program troubleshooting. For example, in the squat and the bench press, the LRV Decay is typically considerably greater than in the deadlift. In other words, since the LRV does not change considerably from RPE-to-RPE in the deadlift, it can make it difficult to determine what the precise RPE actually is if basing the RPE value from the LRV value. Rather in the deadlift, you may want to hierarchize the subjective RPE value above LRV; however, I always record the LRV on the deadlift since it is still beneficial to know for other purposes (i.e., monitoring, etc.).
How Do You Make LRV and RPE Comparisons?
Great question! I’m not going to explain too much here as this question is addressed extensively in the VBT Courses. However, essentially by comparing that subjective RPE to that objective LRV it can provide various evaluations of stress factors and neurological efficiency among many others.
What is LRV Inflection Training?
Another great question… I can’t reveal all the details here. However, LRV Inflection training involves a special bookmarked top set (i.e., a novel type of top set; not your traditional top set, nor your typical top single at a specific RPE). It also involves subsequent back-off volume work for specific session types (i.e., strength, hypertrophy, neuromuscular) based off that special bookmarked top set depending on the primary goal of the training. I’ve played with this reasonably frequently recently with some good progress.
Since Velocity Loss Stops are Employed in the Scientific Literature,
Should Velocity Loss Stops Also be Employed as the
Primary Prescription Strategy in Powerlifting?
Velocity Loss Zones can be Employed to Conceptualize How to
“Individually Optimize Proximity to Failure” (Individualize Allocation, Distribution, etc.) based on Neuromuscular Fatigue and Neuromuscular Adaptations from the Collated Velocity Loss Data; However,
LRV (with RPE) Should be Employed as the
Primary Prescription Strategy in Powerlifting
A large reason why VL thresholds (VL stops to be more specific) are employed in the scientific literature are two-fold. First, VL stops makes data collection incredibly simple. For example, on the Vitruve encoder you can input the specific VL threshold prior to the set, and the encoder will provide an audible intra-set “beep” once that specific VL threshold has been reached; therefore, informing the participant in a research study to terminate the set. Second, VL may have greater utility in resistance training for more main-stream sports (i.e., hockey, football, etc.) compared to powerlifting. For example, based on the recent systematic review and meta-analysis by Gantois et al. 2021, training at ≤~20% VL on average appears to be beneficial for jump heights, sprint times, velocities at submaximal loads, etc. which may transfer to improved performance in these aforementioned more main-stream sports.
However, mutually exclusive VL prescription has countless limitations in practical powerlifting programming contexts. If mutually exclusive VL prescription didn’t have limitations, then I wouldn’t have released that Bonus Seminar back in May 2020 (although a lot has changed from that now) on the limitations of VL, how to conceptualize VL zones, allocation, distribution, etc., and how to integrate LRV (with RPE) as the primary prescription strategy. The primary limitations of VL are three-fold: 1) based on appropriate systematic and meta-analytic techniques there does not appear to be an optimal VL value for 1RM strength adaptations as I am writing this article (Gantois et al. 2021); 2) there are a considerable number of factors influencing VL [16, 17]; 3) anybody that has trained with VL stops that I have discussed this with (Mike, John, other athletes) typically report multiple limitations: it is annoying to be required to terminate the set once that audible beep is heard; it makes monitoring much more difficult than it needs to be; insert countless other limitations here. Certainly, there are numerous strategies to counter-act these limitations; however, I don’t necessarily agree with those that think VL should be completely dis-regarded. Again, most concepts have advantages and limitations. Training with low-moderate VL appears to possibly have some potential benefit for promoting neuromuscular adaptations [10, 11] and for limiting neuromuscular fatigue [19, 20]; whilst, high VL thresholds (to failure) may cause sub-optimal adaptations [7, 9], and increase time course of recovery [19, 52], but they aren’t inferior for 1RM strength (Gantois et al. 2021), unless concurrent training is performed . Overall, VL provides insight into some potential practical applications.
Set and Repetition Schemes Examples
For example, if 12 total repetitions at 82.5% of 1RM was prescribed, what would be my hierarchized set and repetition prescription for this example LRV Model?
Now, you’re like “whoa whoa whoa… didn’t you previously state that based on the alternative set structure meta-analytic data that it doesn’t make a significant difference for strength adaptations nor hypertrophy adaptations how the set and repetition scheme is distributed.” That’s good… you’ve been paying close attention to what I addressed previously. I’ll state up front that this is certainly correct, and it certainly does not make a considerable difference in accordance with the data from Jukic et al.  and Davies et al. . Strength adaptations would arguably be nearly identical because relative intensity is equated between all examples [26, 27], with some small caveats outlined below. Hypertrophy adaptations would arguably be nearly identical because relative volume is equated between all examples [26, 27], with some small caveats outlined below. However, I still think that there may be a certain magnitude of intra-set fatigue (i.e., certain VL threshold) required to augment/assist/mediate hypertrophy adaptations when relative volume is equated, but this remains to be elucidated in the literature with enough studies worthy of a meta-analysis to investigate this question. You may ask, “why should I care if the strength adaptations and hypertrophy adaptations would be nearly identical?” There are some individual subtleties regarding the rationale for the VL zones with respect to strength, hypertrophy, neuromuscular adaptations, neuromuscular fatigue, time efficiency, etc. which may have some practical implications. I contextualize the specific details with numerous practical examples for you in the VBT Courses (i.e., this hierarchized order of choice may deviate from what is outlined below depending on the athlete and goal of the training).
The example strategy addressed below (The LRV Target Repetition Stop Strategy) is arguably the simplest Strategy and Sub-Strategy of the Strategy to conceptualize its application and provide you a basic understanding of the VL zones. There are several Sub-Strategies of the LRV Target Repetition Stop Strategy and endless other Strategies (i.e., LRV Single Strategies, LRV Load Strategies, LRV Volume Strategies, LRV Decay, LRV Inflection, and much more) addressed in the VBT Courses. Although this is incredibly basic (i.e., no load adjustments based on LRV, no repetition adjustments based on LRV, and other components that I may likely integrate, etc.), I want to provide you with something to conceptualize what we’ve learned thus far from this article (and Article 1), and to understand that there isn’t necessarily a ‘magic formula’. In accordance with one of the three key points addressed at the beginning of the VBT Courses and the theme of “pursuing optimal”, I’ll provide a basic summarized insight into the rationale for my hierarchized order of choice. Also keep in mind that these RPE values are based on that objective LRV with velocity feedback upon conclusion of every set.
1) 4 sets of 3 repetitions at 7 RPE
Marginally superior to examples #2, 3, 4 below? Because of the contributing factors (i.e., hypertrophy, neuromuscular adaptations, etc.).
Similar; however, that 20% possible? minimal VL threshold is reached to optimize hypertrophy? (Gantois et al. 2021) .
Preservation of ‘type II’ phenotypic adaptations [9, 18, 21].
25% VL to significantly increase late rate of force development .
Other reasons outlined previously on some of the potential advantages of ~20 – 25% VL .
≤25% VL, which minimizes fatigue .
Not near ≥35% VL, which causes greater fatigue .
4 sets at moderate RPE.
Should be reasonably time efficient with high quality execution.
2) 6 sets of 2 repetitions at 6 RPE
Similar; however, below that 20% possible? minimal VL threshold to optimize hypertrophy? (Gantois et al. 2021) .
Less hypertrophy of synergists? [9, 53] (Therefore, may need to include some additional hypertrophy work for synergists at the end of the training session).
15% VL; thus, no significant change in early nor late rate of force development ; however, other potential beneficial adaptations likely similar .
≤25% VL, which minimizes fatigue .
Not near ≥35% VL, which causes greater fatigue .
1.5x the number of sets from example #1.
May be able to perform slightly shorter rest periods than example #1; however, likely still going to be longer overall (limiting what training the athlete can perform in the same time period).
3) 3 sets of 4 repetitions at 8 RPE
Similar; however, likely the greatest hypertrophy of synergists of all examples? .
At 40% VL; thus, reducing “type II” phenotypic adaptations [9, 21].
At 40% VL; thus, significant decrease in early rate of force development, but no change in late rate of force development ; however, other potential adaptations may be worse .
More, since ≥35% VL .
But are 3 sets of 4 repetitions at an 8 RPE that fatiguing? I certainly hope not, and I certainly don’t think that it is for most. I also think there’s an advantage of training here to be able to handle more volume at higher RPEs more easily if that is what the athlete responds best to.
Honestly, I make hierarchize this with example #2 in certain instances even though it’s technically in the red zone (i.e., if have greater rest prior to next session, if athlete prefers, etc.).
Only 1 less set than example #1, but may have to rest slightly longer between sets to maintain performance ; therefore, may be similar overall time to example #1.
4) 12 sets of 1 repetition at 5 RPE
Similar; however, I wouldn’t be surprised if this caused a more velocity-oriented force-velocity profile since all these repetitions are at very fast velocities (low RPE) , but it doesn’t necessarily matter that much, since the 1RM strength adaptation would likely be similar [26, 27].
However, for monitoring, I’ve found that this can sometimes over-inflate the e1RM if you’re basing this off top singles at say more lower RPEs (i.e., 6 – 7 RPE) due to this more velocity-oriented shift ; therefore, this is certainly an important caveat to be cognizant of if you have more of a velocity-oriented force-velocity profile from training in this style.
Marginally Lower? Even though relative volume is equated and it’s still reasonably close to failure, I’m not entirely sure, because the intra-set fatigue is literally 0% VL, which I think may play a role to augment hypertrophy?  (But certainly remains to be investigated directly and supported or refuted).
0% VL to significantly increase early rate of force development  (which may sacrifice that late rate of force development for 1RM strength improvements in the long-term?).
0% VL .
Although you could rest very little between sets (i.e., perform a resemblance of an inter-repetition rest) this is still 12 un-racks and re-racks on the squat and the bench press, which isn’t that many but it’s still worth mentioning as it is getting up there.
This may be more appropriate for the deadlift: no racking component, practice the set-up, dissipate the stretch-shortening cycle (since the deadlift has no eccentric component).
Since example #1 is the most time efficient (likely identical to example #3) – if time constraints are something that arise for you – you have more time to devote to other training. For example, even more sets (5 sets of 3 repetitions or 7 sets of 3 repetitions) depending on the individual optimal dosage of volume for you . You have more time to hit those prime movers or synergists with supplementary exercises if so desired/required. You have more time for preparation or reflection, development of psychological skills… whatever you require that is not only going to enable you’re 1RM strength to increase, but also enable you to perform to the highest level possible on the platform, keeping in mind not only the adaptation aspect but also the performance aspect to powerlifting. One could argue these are the same, but I would suggest that these are slightly different. Simply because proxies of 1RM (i.e., e1RM, etc.) or even your ‘gym 1RM’ has increased you actually need to have the skill and performance capabilities to express those increases in 1RM on the platform in a competition. And as a final side note, of course, the athlete may likely perform a top single or top set here (i.e., a top triple if selecting scenario 1) to provide an e1RM, since peak intensity may possibly be more important than average intensity for strength , and for the ensuing back-off volume work (outlined in the 4 examples above).
I want to make it explicitly clear that these are certainly not strict rules for all athletes, rather just some generalized guidelines that are likely applicable to most athletes (I’m not a huge advocate of those with extremist views, such as advocating for <5 RPE or 10 RPE – failure training). Also, this isn’t anything new here, nor deviating from what most are already doing…
– Top sets at 8 – 9 RPE (at higher intensities and lower reps).
– Back-off sets at 6 – 7 RPE (with lower intensities than top set and typically slightly higher repetition work than top set at an individual optimal dosage of relative volume).
– Occasionally going to a 10 RPE and occasionally going to a 5 RPE.
– Say you accidentally fail a bench press far out from competition, is it really that big of a deal? Probably not, at least you now know what a true 10 RPE is since it was to failure.
– Say you accidentally go to a 3 – 4 RPE, is it really that big of a deal? Probably not, at least you now know that you can probably increase the load slightly more and push it slightly more.
– Employ LRV (with RPE) as the primary strategies (with VL and other metrics secondarily)
– Most in the green zone, some in the yellow zone, least in the red zone. However, not only do I individualize these VL zones from the individualized LRV values, but also on what the individual athlete responds best to. For example, maybe an athlete doesn’t respond well to 0 – 25% VL (with most at ~20 – 25% VL); therefore, maybe their green zone isn’t at 0 – 25% VL… Most athletes typically also respond best to certain relative intensity zones, which I don’t think is anything new based on the relationship between load and 1RM strength adaptations [28, 29].
Hockey Resistance Training Example with Velocity Loss and Alternative Set Structures
I purposefully left this for the very end of this section for obvious reasons. Please be aware that obviously the VBT Courses are specifically designed for powerlifting. However, I’ve had multiple people ask and I thought some others may be interested on how to contextualize the application of VL stops (and alternative set structures) in more main-stream sports. Although I almost exclusively provide consulting, coaching, and educational services for powerlifters, I also provide a very small amount for hockey players (primarily Western Hockey League players or WHL prospects). Certainly, there are several other adaptations, but when simply conceptualizing adaptations to the neuromuscular system (recalling that the functional unit is the alpha motor neuron and all the skeletal muscle fibers that it innervates), they are very similar, but they are not identical between strength and ‘power’ athletes. For example, neuromuscular adaptations to strength (force) and speed (velocity) athletes are similar, but these neuromuscular adaptations certainly aren’t identical or else both athletes would be similarly as good at the other sport (i.e., powerlifters would be phenomenal 50-m sprinters and vice versa), but this isn’t the case. Why? Because those neuromuscular adaptations are specific to how the individual trains (and a myriad of other factors) and how those adaptations will hopefully translate to improved performance (i.e., force- and velocity-oriented force-velocity profiles, early rate of force development- and late rate of force development-oriented force-time profiles, etc.).
I can’t comment on other more main-stream sports apart from hockey (and powerlifting). I lack the experience to understand other sports at the high-level required to do a good job as I’ve only competed in hockey at a high-level (and now currently powerlifting); therefore, I’ll contextualize resistance training for hockey. I’m not going to pretend I know exactly everything these players (i.e., WHL players) go through for a full career; however, I think it’s reasonable to say that the “overall demands” is probably above average for many athletes at that age. In-season these players have a considerable amount going on: 72 games across 2000 kilometers in 6 months, bus rides only (no planes), some are competing to dress every game, some are competing for positions, many are seeking to turn professional or hoping to continue playing hockey as a career, they’ve left home at 16 years old, they’re still in high school, playoffs… the list goes on. Although the game schedule is typically provided ahead of the season, there’s still a considerable number of unknowns that arise during the season as well. And you’re like, “why do I need to know all of that?” Because, it’s important to recognize that this situation is perhaps where the utility of volume autoregulation via autoregulating intra-set fatigue (via VL stops) and alternative set structures may have the greatest utility.
Due to the short length of the off-season and due to the transition from playoffs to off-season to pre-season, these athletes may typically follow more of a periodized model  (of course much more specific to their sport), but it is still individualized, autoregulated, specific to their position, specific to what the athlete needs to work on the most that will translate to improve on-ice game performance, and will include bottom-up principles (i.e., if it is an athlete that I’ve worked with for multiple off-seasons or for quite some time). Outlined below is an incredibly basic and incredibly summarized example of what their resistance training may comprise of as the season nears. This example is solely for the resistance training aspect of their overall program, and solely with respect to VL stops (and alternative set structures) for some of the compound lifts (obviously there is exponentially more specifics than what is outlined).
Second Final Phase prior to Training Camp
2nd Strength-focused phase primarily via alternative set structures (primarily cluster sets)
– Primarily autoregulate and monitor via LRV (with RPE; secondarily via VL)
– Volume maintained (still reasonable time out from training camp; on-ice session frequency moderate)
– Intensity moderate-high (when I say “moderate-high”, I mean considerably lower than what “moderate-high” would mean for a powerlifter); however, this phase (or prior phase; 1st strength-focused phase) may also have more “high” intensity training
– Shifts towards more velocity-oriented force-velocity profiles (via alternative set structures) 
– Increased power and velocity with submaximal loads (via alternative set structures) 
– Mimic similar work-to-rest ratio experienced on the ice in game situations (via cluster sets)
Final Phase prior to Training Camp
Neuromuscular-focused (or velocity/speed-focused or traditionally called power-focused) phase primarily via VL stops (very low VL; primarily near 0 – 10% VL; may include inter-repetition rest)
– Primarily autoregulate via VL (secondarily via LRV with RPE) and monitor via LRV (with RPE)
– Volume tapered (on-ice session frequency begins to increase rapidly each microcycle)
– Intensity lower (when I say “lower”, I mean incredibly lower than what “lower” would mean for a powerlifter) to more closely mimic velocities of the athlete on the ice
– Shifts towards more early-rate of force development force-time profiles (via 0% VL) 
– Volume and VL (both primary factors contributing to fatigue) [19, 20, 58] both decrease towards training camp to dissipate fatigue as much as possible whilst maintaining adaptations achieved during the off-season [59-61] so that the athlete heads into the season feeling in great ‘fitness’, but also ‘rejuvenated’ from the previous season and ready to go… the off-season is considerably easier than the actual in-season despite doing two- or three- a day training sessions in the off-season.
Fortunately, most strength & conditioning coaches at this level (i.e, WHL) have considerable experience and education; however, unfortunately, at lower levels, not so much.
Why Potentially VL Stops over LRV (and RPE) In-Season?
There’s certainly instances where I prescribe LRV (less so RPE) if I can (and I typically prefer to prescribe LRV over VL), but I’d say VL is sometimes more prevalent, particularly when the athlete is on their own in a team setting (i.e., doesn’t have an experienced nor knowledgeable strength & conditioning coach to work with) because of two primary reasons:
1) VL stops are easier for the athlete to use on their own In-Season.
Most athletes don’t want to (nor do they necessarily need to) be tracking LRV nor RPE; they want to (and need to) focus primarily on performing to the best of their abilities in games during the season. I’ll prescribe some basic autoregulatory components (comprised of LRV) for them, but typically I’ll have them provide me their velocity data from the App for analysis and ensure that they aren’t deviating from the training prescription for the desired training outcome.
2) Most training is at moderate percentages of 1RM and at moderate RPE to limit In-Season fatigue when game performance is most important.
Typically, I’ll prescribe percentages of 1RM; however, the percentages of 1RM are still autoregulated from set-to-set and based on the LRV of the warm-up and perhaps some other readiness factors (i.e., countermovement jump  for example). Since the LRV does not fluctuate considerably from repetition-to-repetition or from RPE-to-RPE (hint to LRV Decay) when further from failure it’s difficult to determine accurate RPE/RIR values when the athlete is far from failure (i.e., at a 5 RPE/RIR). It’s likely more important what VL they are training at to limit neuromuscular fatigue (i.e., for in-season  and for concurrent training ) and I would argue that training at ≤~20% VL does seem to provide an indication of specific desired neuromuscular adaptations for proxies of performance translatable to hockey (although I would also argue that this has sometimes been slightly over-exaggerated) (Gantois et al. 2021).
Finally, I’ve provided a practical example of an in-season scenario between two different hockey players to contextualize where VL stops may be beneficial. If a team training session is scheduled, Player 1 and Player 2’s training would be considerably different based on their position, upcoming schedule, what they need to improve on, etc. However, from an incredibly basic perspective, based on the information outlined below, they’d certainly autoregulate their volume (i.e., less for Player 1; more for Player 2) and this would likely be via autoregulating intra-set fatigue (i.e., 10% VL stops for Player 1; 20% VL stops for Player 2), since VL stops are a feasible strategy to autoregulate volume and intra-set fatigue in a large team setting (i.e., the set volume is kept the same for each Player which makes session prescription and timing easier when they may have on-ice sessions, meetings, etc.), and based on the collated VL literature [6-15], adaptations can be maintained with considerably low volume via considerably low VL thresholds. Please keep in mind that these athletes are not as concerned with increasing adaptations during the season so much as they are concerned with actually performing (i.e., the off-season is designed to increase those adaptations for improved performance; the in-season is designed for maintaining those adaptations and focusing on actual in-game performance).
1) Player 1 (10% VL stop training following day)
Played game night before – 10 PM (time game ended).
Post-game meal – 10:30 PM.
Rode bus back to home rink to unload equipment – 2 AM.
Drove back home and went to bed – 2:30 AM.
Slept – 2:30 AM to 7 AM.
Up the next day for school – 7 AM.
Slept 4.5 hours night prior.
2) Player 2 (20% VL stop training following day)
Didn’t play game the night before and didn’t travel with the team.
Slept 9 hours night prior.
Reasonably minimal (sometimes no) resistance training is performed (perhaps some active recovery sessions ) depending on the exact playoff schedule (although playoff schedule is unpredictable). The athletes must be rested as much as possible to perform the best to win, which is obviously the ultimate goal. They have already played a 72-game regular season and could end up playing another 28 playoff games maximum. During the playoffs it’s not uncommon for many of them to play through some considerable injuries, play many more minutes, and the schedule is certainly more difficult. However, perhaps the biggest change from the regular season is that the compete level of the games are at an entirely different level. Anyways, I won’t go off on any more of a tangent. Hopefully that provided some context into where VL stops (and alternative set structures) may have some greater practical utility in more main-stream sports such as resistance training program design for hockey for those that have asked and may be interested.
1. Morán-Navarro, R., et al., Movement velocity as a measure of level of effort during resistance exercise. J Strength Cond Res, 2019. 33(6): p. 1496-1504.
2. Odgers, J.B., et al., Rating of perceived exertion and velocity relationships among trained males and females in the front squat and hexagonal bar deadlift. J Strength Cond Res, 2021. 35(Suppl 1): p. S23-s30.
3. Pérez-Castilla, A., et al., Reliability and concurrent validity of seven commercially available devices for the assessment of movement velocity at different intensities during the bench press. J Strength Cond Res, 2019. 33(5): p. 1258-1265.
4. Weakley, J., et al., The validity and reliability of commercially available resistance training monitoring devices: a systematic review. Sports Medicine, 2021. 51(3): p. 443-502.
5. Behm, D.G. and D.G. Sale, Velocity specificity of resistance training. Sports Med, 1993. 15(6): p. 374-88.
6. Galiano, C., et al., Low-velocity loss induces similar strength gains to moderate-velocity loss during resistance training. J Strength Cond Res, 2020.
7. Held, S., et al., Improved strength and recovery after velocity-based training: a randomized controlled trial. Int J Sports Physiol Perform, 2021: p. 1-9.
8. Pareja-Blanco, F., et al., Effects of velocity loss during resistance training on performance in professional soccer players. Int J Sports Physiol Perform, 2017. 12(4): p. 512-519.
9. Pareja-Blanco, F., et al., Effects of velocity loss during resistance training on athletic performance, strength gains and muscle adaptations. Scand J Med Sci Sports, 2017. 27(7): p. 724-735.
10. Pareja-Blanco, F., et al., Velocity loss as a critical variable determining the adaptations to strength training. Med Sci Sports Exerc, 2020. 52(8): p. 1752-1762.
11. Pareja-Blanco, F., et al., Effects of velocity loss in the bench press exercise on strength gains, neuromuscular adaptations and muscle hypertrophy. Scand J Med Sci Sports, 2020.
12. Rodiles-Guerrero, L., F. Pareja-Blanco, and J.A. León-Prados, Effect of velocity loss on strength performance in bench press using a weight stack machine. Int J Sports Med, 2020.
13. Rodríguez-Rosell, D., et al., Velocity-based resistance training: impact of velocity loss in the set on neuromuscular performance and hormonal response. Appl Physiol Nutr Metab, 2020. 45(8): p. 817-828.
14. Rodríguez-Rosell, D., et al., Effect of velocity loss during squat training on neuromuscular performance. Scand J Med Sci Sports, 2021.
15. Sánchez-Moreno, M., et al., Effects of velocity loss during body mass prone-grip pull-up training on strength and endurance performance. J Strength Cond Res, 2020. 34(4): p. 911-917.
16. Rodríguez-Rosell, D., et al., Relationship between velocity loss and repetitions in reserve in the bench press and back squat exercises. J Strength Cond Res, 2019.
17. Beck, M., et al., Decline in unintentional lifting velocity is both load and exercise specific. J Strength Cond Res, 2020.
18. Weakley, J., et al., Velocity-based training: from theory to application. Strength Cond J, 2020.
19. Pareja-Blanco, F., et al., Time course of recovery from resistance exercise with different set configurations. J Strength Cond Res, 2018.
20. Pareja-Blanco, F., et al., Time course of recovery following resistance exercise with different loading magnitudes and velocity loss in the set. Sports (Basel), 2019. 7(3): p. 59.
21. Martinez-Canton, M., et al., Role of CaMKII and sarcolipin in muscle adaptations to strength training with different levels of fatigue in the set. Scand J Med Sci Sports, 2021. 31(1): p. 91-103.
22. Helms, E.R., et al., RPE and velocity relationships for the back squat, bench press, and deadlift in powerlifters. J Strength Cond Res, 2017. 31(2): p. 292-297.
23. García-Ramos, A., et al., Reliability of the velocity achieved during the last repetition of sets to failure and its association with the velocity of the 1-repetition maximum. PeerJ, 2020. 8: p. e8760.
24. Banyard, H.G., K. Nosaka, and G.G. Haff, Reliability and validity of the load-velocity relationship to predict the 1RM back squat. J Strength Cond Res, 2017. 31(7): p. 1897-1904.
25. Banyard, H.G., et al., The reliability of individualized load-velocity profiles. Int J Sports Physiol Perform, 2018. 13(6): p. 763-769.
26. Jukic, I., et al., The effects of set structure manipulation on chronic adaptations to resistance training: a systematic review and meta-analysis. Sports Med, 2021.
27. Davies, T.B., et al., Chronic effects of altering resistance training set configurations using cluster sets: a systematic review and meta-analysis. Sports Med, 2021.
28. Campos, G.E., et al., Muscular adaptations in response to three different resistance-training regimens: specificity of repetition maximum training zones. Eur J Appl Physiol, 2002. 88(1-2): p. 50-60.
29. Schoenfeld, B.J., et al., Strength and hypertrophy adaptations between low- vs. high-load resistance training: a systematic review and meta-analysis. J Strength Cond Res, 2017. 31(12): p. 3508-3523.
30. Turner, A., et al., Developing powerful athletes, part 1: mechanical underpinnings. Strength and Conditioning Journal, 2020. 42: p. 1.
31. Turner, A.N., et al., Developing powerful athletes part 2: practical applications. Strength & Conditioning Journal, 2021. 43(1): p. 23-31.
32. Schoenfeld, B.J., D. Ogborn, and J.W. Krieger, Dose-response relationship between weekly resistance training volume and increases in muscle mass: A systematic review and meta-analysis. J Sports Sci, 2017. 35(11): p. 1073-1082.
33. Jukic, I., et al., Acute effects of cluster and rest redistribution set structures on mechanical, metabolic, and perceptual fatigue during and after resistance training: a systematic review and meta-analysis. Sports Med, 2020.
34. Komi, P.V., Stretch-shortening cycle: a powerful model to study normal and fatigued muscle. J Biomech, 2000. 33(10): p. 1197-206.
35. González-Badillo, J.J., et al., Maximal intended velocity training induces greater gains in bench press performance than deliberately slower half-velocity training. Eur J Sport Sci, 2014. 14(8): p. 772-81.
36. Pareja-Blanco, F., et al., Effect of movement velocity during resistance training on neuromuscular performance. Int J Sports Med, 2014. 35(11): p. 916-24.
37. Weakley, J., et al., The effects of augmented feedback on sprint, jump, and strength adaptations in rugby union players after a 4-week training program. Int J Sports Physiol Perform, 2019: p. 1205-1211.
38. Munn, J., et al., Resistance training for strength: effect of number of sets and contraction speed. Med Sci Sports Exerc, 2005. 37(9): p. 1622-6.
39. Behm, D.G. and D.G. Sale, Intended rather than actual movement velocity determines velocity-specific training response. J Appl Physiol (1985), 1993. 74(1): p. 359-68.
40. Crewther, B., J. Cronin, and J. Keogh, Possible stimuli for strength and power adaptation: acute mechanical responses. Sports Med, 2005. 35(11): p. 967-89.
41. Davies, T.B., et al., Effect of movement velocity during resistance training on dynamic muscular strength: a systematic review and meta-analysis. Sports Med, 2017. 47(8): p. 1603-1617.
42. Sánchez-Medina, L. and J.J. González-Badillo, Velocity loss as an indicator of neuromuscular fatigue during resistance training. Med Sci Sports Exerc, 2011. 43(9): p. 1725-34.
43. Weakley, J.J.S., et al., Visual feedback attenuates mean concentric barbell velocity loss and improves motivation, competitiveness, and perceived workload in male adolescent athletes. J Strength Cond Res, 2019. 33(9): p. 2420-2425.
44. Weakley, J., et al., Show me, tell me, encourage me: the effect of different forms of feedback on resistance training performance. J Strength Cond Res, 2018.
45. Hirsch, S. and D. Frost, Considerations for velocity-based training: the instruction to move “as fast as possible” is less effective than a target velocity. J Strength Cond Res, 2019: p. 1.
46. Hughes, L.J., et al., Using a load-velocity relationship to predict one repetition maximum in free-weight exercise: a comparison of the different methods. J Strength Cond Res, 2019. 33(9): p. 2409-2419.
47. Ruf, L., C. Chéry, and K.L. Taylor, Validity and reliability of the load-velocity relationship to predict the one-repetition maximum in deadlift. J Strength Cond Res, 2018. 32(3): p. 681-689.
48. Benavides-Ubric, A., et al., Analysis of the load-velocity relationship in deadlift exercise. J Sport Sci Med, 2020. 19: p. 452-459.
49. Williams, T.D., et al., Bench press load-velocity profiles and strength after overload and taper microcyles in male powerlifters. J Strength Cond Res, 2020.
50. Turnwald, B.P., et al., Learning one’s genetic risk changes physiology independent of actual genetic risk. Nat Hum Behav, 2019. 3(1): p. 48-56.
51. Shattock, K. and J.C. Tee, Autoregulation in resistance training: a comparison of subjective versus objective methods. J Strength Cond Res, 2020.
52. Morán-Navarro, R., et al., Time course of recovery following resistance training leading or not to failure. Eur J Appl Physiol, 2017. 117(12): p. 2387-2399.
53. van den Tillaar, R., V. Andersen, and A.H. Saeterbakken, Comparison of muscle activation and kinematics during free-weight back squats with different loads. PLoS One, 2019. 14(5): p. e0217044.
54. Simão, R., et al., Acute and long-term comparison of fixed vs. self-selected rest interval between sets on upper-body strength. J Strength Cond Res, 2020.
55. Scarpelli, M.C., et al., Muscle hypertrophy response is affected by previous resistance training volume in trained individuals. J Strength Cond Res, 2020.
56. Lima, B.M., et al., Planned load reduction versus fixed load: a strategy to reduce the perception of effort with similar improvements in hypertrophy and strength. Int J Sports Physiol Perform, 2018. 13(9): p. 1164-1168.
57. Williams, T.D., et al., Comparison of periodized and non-periodized resistance training on maximal strength: a meta-analysis. Sports Med, 2017. 47(10): p. 2083-2100.
58. Bartolomei, S., et al., Comparison of the recovery response from high-intensity and high-volume resistance exercise in trained men. Eur J Appl Physiol, 2017. 117(7): p. 1287-1298.
59. Pritchard, H.J., et al., Tapering practices of New Zealand’s elite raw powerlifters. J Strength Cond Res, 2016. 30(7): p. 1796-804.
60. Grgic, J. and P. Mikulic, Tapering practices of croatian open-class powerlifting champions. J Strength Cond Res, 2017. 31(9): p. 2371-2378.
61. Winwood, P.W., et al., Tapering practices of strongman athletes. J Strength Cond Res, 2018. 32(5): p. 1181-1196.
62. Watkins, C.M., et al., Determination of vertical jump as a measure of neuromuscular readiness and fatigue. J Strength Cond Res, 2017. 31(12): p. 3305-3310.
63. Bartolomei, S., et al., Upper-body resistance exercise reduces time to recover after a high-volume bench press protocol in resistance-trained men. J Strength Cond Res, 2019.
Gantois, P., Nakamura, F. Y., Alcazar, J., de Sousa Fortes, L., Pareja-Blanco, F., & de Souza Fonseca, F. (2021, June 29). The effects of different intra-set velocity loss thresholds on lower-limb adaptations to resistance training in young adults: A systematic review and meta-analysis. https://doi.org/10.31236/osf.io/v3tr9.