Mass Research (Volume 4 - Issue 3)
We’ve all experienced daily fluctuations in both energy levels and performance. Sometimes this is due to fatigue from a previous training session and sometimes this is due to other factors (i.e. lack of sleep, stress, anxiety, etc.). In these cases, using a flexible training template allows you to adjust the day’s session volume and/or intensity immediately before training. Although there is some support for flexible templates in the literature (2, 3), not all studies show a benefit (4). One possible reason for the lack of consistent findings among the flexible studies is the lack of uniformity of readiness indicators. In other words, when choosing whether to utilize a heavy, moderate, or light training day within a flexible template, the specific metric used as the readiness indicator to guide the session-type selection probably matters. For example, if heart rate variability (HRV) is not recovered, or a pre-training questionnaire classifies someone as under-recovered, then the athlete may choose the lighter session. However, common metrics such as HRV and simple Likert scales have not always been an accurate reflection of readiness to train (5, 6). Logically, the recovery of squat velocity at submaximal intensities should be a good indicator of 1RM strength recovery; thus, a viable readiness to train indicator. This crossover design study (1), examined the time courses of recovery of 1RM strength, average and peak concentric velocity, and barbell vertical jump peak velocity following a strength session (5 X 5 at 80% of 1RM) and power session (3 X 6 at 60% of 1RM) for up to 96 hours. In brief, the recovery rates of velocity and barbell vertical jump did not mirror that of 1RM strength, which suggests that velocity should not be used as a readiness indicator when implementing a flexible template with strength as the main session goal. Unfortunately, this study – and many readiness studies – have flaws, which we will discuss. Despite the promise of flexible templates, the support for many readiness indicators is thinner than you may think. Therefore, this article will deliver an update on the topic by providing an overview of the evidence for each practical readiness indicator. We will also discuss how to use the findings in your training.
The purpose of this study was to examine if the time courses of recovery for 1RM strength, average and peak velocity, and vertical jump peak velocity mirrored each other following both strength and power training sessions on the squat.
No hypotheses were provided. However, the tone of the author’s introduction suggests that the authors believed changes in velocity and 1RM would mirror each other during the recovery period.
15 men with at least 6 months of training experience and a squat 1RM of ≥1.5 times body mass participated. The available descriptive details of the subjects are in Table 1.
Subjects visited the lab 13 times over 3 weeks to complete the study. There were three sessions during week one, in which subjects were first familiarized with the protocol. Squat 1RM was tested, and then a load-velocity profile was created by squatting at 20, 40, 60, 80, and 90% of 1RM.
Weeks two and three were the same, except the training session was a strength-type session during one of the weeks (5 X 5 at 80% of 1RM) and power-type training (3 X 6 at 60% of 1RM) during the other week. The order of weeks (strength or power) was counterbalanced. For weeks two and three, subjects came into the lab Monday through Friday (five times each week). On Monday, subjects performed either the strength or power training session, then after the training session, average and peak velocity were assessed at 20, 40, 60, 80, and 90% of 1RM before performing an actual 1RM. Vertical jump peak velocity with the barbell was also tested. All of the velocity outcome measures and the 1RM were then tested again at 24, 48, 72, and 96 hours following training to examine time courses of recovery. At each time point, the outcome measures were compared to the established load-velocity profile established during week one to determine the time course of recovery.
Frustratingly, this study did not use typical frequentist statistics to establish p-values in order to evaluate main effects, and then to potentially examine at what specific time points outcome measures may have been significantly different from baseline values. Rather, the researchers only used effect sizes to compare the baseline level of the outcome measure to each individual time point. The researchers also did not examine correlations between the change in velocity outcome measures and the change in 1RM, which would have provided much greater insight into the ability of these metrics to predict strength performance and be used as readiness indicators. There are other limitations mentioned later, but for now, I feel comfortable saying that both the design and statistics were not sufficient to answer the stated research question.
Power Training Week
I chose not to show any tables or figures for the time course of recovery following the power session because there wasn’t any meaningful fatigue, which is not surprising following such a light workout.
Strength Training Week
In brief, velocity at most intensities was lower than baseline according to the effect size values for up to 96 hours. However, when you look at Table 2, you can see these velocity decreases are quite small. It is possible that many of these decreases would not actually be statistically significant. For strength, there was a visual decline at 24 hours (Figure 1); however, this was only noted as a trivial effect (i.e. not a meaningful effect). The authors stated that there were only “trivial to small effect” sizes for decreases in barbell vertical jump velocity, which is visually evident in Figure 2.
Summary of Findings
Maximal squat strength had only a trivial decrease at 24 hours, and its recovery was not mirrored by velocity at submaximal intensities. The training protocol used in this study simply didn’t cause enough fatigue to allow the research question to be answered.
Frustration. That’s the best word to describe my feelings when reading and interpreting this study. The lack of a statistical model for main effects and not examining relationships between changes in velocity and changes in 1RM to truly examine the utility of velocity as a readiness indicator highlight the frustration. However, three more points of frustration also arose. First, the authors concluded that squat velocity was a better indicator of recovery than 1RM. What? How can the metric being used as a proxy for recovery be better than the actual thing that is recovering (i.e. 1RM strength)? Sure, you could argue that 1RM strength isn’t the best recovery metric if you are aiming to find a readiness indicator for a volume- or power-oriented session; however, if that was the case, the authors did not make it clear. Secondly, the training protocols themselves did not meet the standard for a quality study design. Rule No. 1 when you are conducting a study to examine the time course of recovery is to ensure that the training protocol elicits enough muscle damage and/or fatigue. Now, this study does give us practical information that 5X5 at 80% of 1RM, which is about an 8RM load (7), simply doesn’t cause that much fatigue in trained lifters. However, if you want to study whether velocity is a good recovery indicator, then the protocol must create sufficient damage/fatigue so that this analysis can be conducted. Third, the load-velocity profile testing, which served as a baseline, should have been conducted immediately before the training protocol on both weeks 2 and 3. Then, the velocity during the recovery period should have been compared to these pre-training velocities. It isn’t appropriate to compare recovery to a baseline that was done the prior week, especially for velocity, since small fluctuations in velocity can occur from day to day. Since this study was intended to be about “readiness to train,” I have searched the literature for all of the important data on practical readiness to train indicators. We have previously discussed readiness to train here and again here; however, there have been some updates since then. Therefore, you can consider the below a comprehensive update on the practical training readiness literature with some brand-new thoughts and ideas about the topic. Let’s now explore each individual readiness indicator.
Evidence for Each Readiness Indicator
Perceived Recovery Status Scale
This scale, widely known as the “PRS,” is a 0-10 Likert scale assessing recovery and is probably the most commonly cited scale for examining readiness to train. However, little evidence exists showing a relationship between scores on this scale and acute lifting performance. Laurent et al developed this scale in 2011 (8), and found that the ratings on the PRS were inversely related with 30-meter sprint performance in the days following a damaging sprint workout. In other words, as PRS scores went up (more recovery), sprint times went down (athletes ran faster). Scores on the PRS also have a clear relationship to high levels of muscle damage following a resistance training session (9); however, on two different occasions, the PRS has failed to consistently relate to maximal strength performance (6, 10). So, although there are no direct findings showing that recovery on the PRS is directly related to improved acute volume or strength performance, it makes sense that the PRS is sensitive enough to be related to high levels of muscle damage. As we will discuss later in this article, muscle damage and fatigue are only two factors affecting readiness; therefore, although this scale may represent readiness as it pertains to damage, the PRS may not pick up on readiness factors such as sleep deprivation, anxiety, and nervousness.
PRS Takeaway: The PRS is an easy-to-use and practical scale. It will likely be predictive of performance if large amounts of damage are present, but it is not designed to pick up on all factors contributing to readiness.
Daily Analysis of Life Demands (DALDA)
The DALDA is a survey in which the athlete rates the magnitude of daily stress for a specific characteristic (i.e. home life, friends, muscle pains, etc.) as either “a” (worse than normal), “b” (normal), or “c” (better than normal). Scores on the DALDA have been worse during a training period when triathletes have performed high intensity training versus normal training (11). Recovery of DALDA scores following a week of training in handball players has also coincided with the recovery of HRV (12). However, to show that ratings on a scale improve as recovery (i.e. soreness and general fatigue) improves is not the same as showing that the scale is directly related to acute resistance training performance. In fact, Haischer et al observed no relationship between individual DALDA scores and acute 1RM squat strength (6). Further, Dr. Helms’ dissertation did not show a difference in pre-training DALDA scores over an eight-week period between groups that performed autoregulated and percentage-based training (13), which shows that the DALDA may not pick up on small differences in readiness.
DALDA Takeaway: The DALDA may likely pick up on fatigue from intense training; however, there is little to no data to suggest it as a standalone readiness indicator for strength training.
Anxiety and Sleep
I’ve combined these as they are both assessed via questionnaires, and a key study (6) has previously examined both of them together. Anxiety can be assessed as either somatic (physical manifestations) or cognitive (mental). In the literature, the competitive state anxiety inventory-2 scale is commonly used to assess acute anxiety. This is a 1-4 Likert scale where factors such as confidence and concern for the performance task are rated. Interestingly, findings for acute anxiety and performance are conflicting in athletes. Increased cognitive anxiety has been associated with improved strength and power performance in female volleyball players (14); however, increased cognitive anxiety has also been associated with diminished skilled basketball performance (15). This tells us that anxiety could be facilitative for some individuals and tasks and debilitative for others. In the aforementioned Haischer study (6), increased cognitive anxiety was significantly related to performing a better-than-expected 1RM when using a bivariate (i.e. two variables) correlation. However, when entered into a multiple regression analysis with many variables, anxiety was no longer a significant predictor of 1RM; rather, only acute sleep was. In that study, sleep was assessed using the Oviedo Sleep Questionnaire. Specifically, Haischer had subjects predict their 1RM before entering the laboratory and found that those who had more sleep the night before tended to squat more than their prediction. Subjects in Haischer’s study with more sleep also recorded higher RPEs at the 1RM and had slower velocities at a 1RM, which signals those with more sleep were more likely to work to a true 1RM. However, other data have shown that one night of impaired sleep does not affect strength, but prolonged sleep deprivation does (16). In the Haischer study, the average sleep per night according to an acute questionnaire was 6.7 ± 0.8 hours, so it is possible that this relationship was more of an effect of a long-term sleep deficit. While it is hard to be certain, it does seem likely that 7-8 hours of sleep per night over the long-term is beneficial.
Anxiety and Sleep Takeaway: High cognitive anxiety is likely beneficial for some and harmful for others. Although the jury is still out on acute sleep and performance, long-term sleep deficits do seem to negatively affect strength.
Velocity and RPE
Sometimes you get to the gym and feel terrible, but you get the blood flowing during your warm-up and all of sudden you have a pretty good training session. If this sounds like you, then it may be better to start warming up, examine your velocity or RPE, and use that to implement a flexible template. This makes logical sense; however, the supporting evidence is limited. For starters, the presently reviewed study (1), despite its flaws, did not show velocity to be indicative of 1RM recovery. Further, during a case series (10) which had three well-trained lifters max squat for 37 consecutive days, average velocity and RPE were taken every day at 85% of the pre-test 1RM. In the case series, average velocity was significantly related to daily 1RM performance in only one lifter, while RPE at 85% was inversely related to 1RM performance in all three individuals. It may seem a bit surprising that RPE out-performed velocity as a predictor of performance; however, since lifters were max squatting every day, they may have still been finding their groove for the day on the 85% warm-up, which potentially made velocity more variable than RPE. Further, Greg previously reviewed a study showing that the recovery of squat velocity at submaximal intensities (20-90% of 1RM) did not accurately predict the recovery of squat 1RM in the 48 hours following a damaging training session (17). This is not to say that velocity is without any merit as a readiness indicator. Velocity on the first repetition of a pull-up was able to significantly predict the amount of reps performed to failure in a study by Beckham et al (18). Although, one limitation of extrapolating Beckham’s findings to barbell exercises is that the pullup is a bodyweight exercise, so it is likely the subjects were all lifting a different percentage of their respective pullup 1RMs.
Velocity and RPE Takeaway: Both velocity and RPE have some evidence supporting their usage as readiness indicators. Logically, if you work up to a heavy enough load in your warm-up, then the recorded velocity and RPE could be used as the basis for a flexible template. In practice, I would see if these metrics correlate with your acute and weekly sleep. If so, then I think these tools could be pretty safely implemented as readiness indicators.
Heart Rate Variability (HRV)
HRV, which is the variability of time between heart beats, signals fatigue when lowered. In resistance training, the evidence for HRV as a readiness indicator is underwhelming. As we previously reviewed in MASS, Flatt et al (5) did not observe the recovery of HRV to be related to the recovery of velocity, vertical jump, or the PRS scale following a damaging training session on the squat, bench press, and lat pulldown. Further, Dr. Helms previously reviewed a study that showed when subjects performed their next session only when HRV was fully recovered (i.e. used as the readiness indicator to implement a flexible template), the subjects completed 20 total training sessions faster (~5 weeks) than a fixed template group (7 weeks), but did not gain more strength (19). That study (19) was also not designed to answer its own question well. Since we don’t know if recovery of HRV is actually related to recovery of strength, then we don’t know if the extra time subjects took off between workouts in the fixed template group was actually needed. Finally, Thamm et al (20) recently reported that recovery of HRV was not correlated with recovery of strength or creatine kinase (a circulating enzyme used to measure muscle damage) in the days following a damaging leg press session.
HRV Takeaway: Despite the advanced technology and some promise in the realm of endurance training, there are not enough data to warrant the use of HRV as a readiness indicator within a resistance training program.
Peak velocity of the vertical jump was used in the presently reviewed study, but due to both the overall lack of fatigue in this study and lack of correlational analysis, it is difficult to tell if this metric was an effective indicator of readiness. However, on the basis of a study from Watkins et al (21), vertical jump height has some of the strongest support in the literature as a readiness indicator. Specifically, Watkins tested subjects’ vertical jump to establish a baseline, and then the subjects performed four sets to failure at 80% of 1RM. Next, subjects’ vertical jump was tested 48 hours later and subjects again performed four sets to failure at 80% of 1RM. A significant correlation of r = 0.65 was observed between decreases in vertical jump height and decreases in squat volume. In terms of usable numbers, Watkins reported that a 2.5cm decrease in vertical jump height was associated with 5.6 fewer reps performed on the squat. This is relatively high-quality evidence, as the readiness indicator was directly related to performance, which we have not been able to say often in this article. Although these findings are promising, we should keep in mind that vertical jump height was related to volume performance and not maximal strength performance (more on that later); ultimately, we would want to see a long-term study using vertical jump height as the readiness indicator to guide a flexible template versus a fixed template to cement these findings.
Vertical Jump Takeaway: To date, vertical jump height has some of the strongest evidence to be an effective readiness indicator. If vertical jump is decreased by at least 2cm, then it’s a pretty good bet that the ability to perform squat reps over multiple sets will be diminished.
Readiness for What?
We often hear about many of the readiness indicators mentioned above, but only in a generic sense. The most appropriate metric may differ when you are trying to assess readiness for volume training or for heavy training. A previous study we reviewed in MASS from Ferreira et al (22) demonstrated that max strength and volume performance followed different recovery time courses following a high volume bench press session. Specifically, strength was recovered at 72 hours, while volume capabilities had still not fully recovered at 96 hours. Based on this, it seems that readiness markers that are sensitive to muscle damage may be indicative of volume performance. Further, since volume capabilities are diminished longer than strength capabilities, some readiness markers – such as PRS – may not need to be fully recovered for strength to be recovered. However, full recovery on the PRS may be needed if looking to maximize volume performance. The last few sentences are of course speculation, but I think it’s reasonable and helps to explain some of the equivocal findings. In general, I also wonder how fatigued you truly need to be for readiness to matter? Essentially, a very small change in a recovery metric probably isn’t worth worrying about; it’s the large changes that you need to look out for, and then adjust training appropriately.
Since the data in this area leave a lot to be desired and there are not a lot of well-designed studies to truly answer the readiness question, there has been little scrutiny of the studies that do exist. This translates into little insight into the secondary and tertiary questions posed above, such as: Are different readiness indicators better to guide different types of performance?
Needless to say, there’s a long way to go in this area. A study examining the relationship between recovery of any of the above-mentioned metrics and performance following a damaging training session would be a good start. Then, whichever metrics correlate with performance should be used as readiness indicators to guide a flexible template versus a fixed training template in a longitudinal study. Ideally, the training sessions would be pretty damaging in the longitudinal study to make the flexibility matter. Then we could see which indicators actually guide training the best. That would all accomplish a great deal.