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Autoregulation and fatigue monitoring with Velocity based training

Have you ever mapped out a beautiful multi-week training block for an athlete and had them actually hit the target load and reps in week six or seven? I cannot recall a singe example when an athlete managed to make it through an entire block without some variable from real-life rearing its ugly head and messing with my perfect plan!

The facts of human physiology and psychology impose variables on programming that can’t be mapped in advance, no matter how sophisticated the spreadsheet. As coaches, we need simultaneously build great plans but still remain adaptable to the unexpected that can occur along the way.

Whether it is at the individual or population level, optimisation of training is a constant adaptive process, tweaking volume, intensity, etc to refine a program, find the best stimulus and make progress.

To make this process even trickier, training plans also need to consider human variables - fatigue, stress, sleep, motivation, nutrition, hydration, time-of-day - factors that can have a dramatic effect on our performance on an hourly, or daily basis.

Fluctuating performance levels are broadly encompassed by the concept readiness to train (also just readiness), and the adjustment of training in response to these factors is known as autoregulation. Velocity tracking has a lot to offer as a method for managing readiness and applying autoregulation in training.

Optimising training

Hard work is rewarded in the world of training, putting in the time and the effort pays dividends when it comes to building strength, power or shifting body composition. Without stress and work the body will not adapt and we will fail to make meaningful gains.

But hard work must also be strategic. We must find the optimal workload to stimulate adaptations, while avoiding the kind of overworking that can exhaust our systems in the long term or interfere with subsequent sessions in the short term. Overworking (or under recovering) results in an unhelpful accumulation of fatigue, leading to a gradual decrease in performance, lower adaptation, or even increased injury risk.

Overtraining & overreaching

Training that truly pushes an athletes limits can be incredibly productive when programmed appropriately and in small doses (say a single set or a single exercise within a training block). But consistently working at this point of failure (say RPE-9.5 and above, above 35% velocity loss) becomes counterproductive for both short term readiness and long term performance gains. if mismanaged.⁠

The effects of training close to the point of failure is well-documented; Even a single hard session that has an athlete reach their failure point reduces short term power performance and delays recovery (image 1). While programs that push an athlete repeatedly to their failure point inhibits long term strength and power gains compared to more submaximal programs that utilise lower training volumes (graph 2 & 3).

Images: Three separate studies all highlighting results were training closer to failure lead to inferior short and long term training adaptations.

Proximity to failure is a variable you have the power to manipulate in your training.
Repeated exposure to maximal training is likely to have a negative effect on your short and long term performance, but strategic exposures to maximal effort with adequate rest are also likely to be essential for high performance.

The poison is in the dosage.

Creating dynamic training plans

With the negative effects of over and under training in mind, it is clear we need to tailor our program (and even individual sessions) based on readiness and individual rates of adaptation. Predetermining every single loading decision with fixed percentages is a fools errand and is ill-suited to the dynamic needs of modern strength athletes or strength and conditioning environments.

There is a growing body of research that shows autoregulation and individualisation of programming leads to superior training outcomes compared to percentage based approaches.

Enter modern, adaptive and flexible approaches to programming. Most will be familiar with RPE based systems as pioneered by Mike T at Reactive Strength Systems, and in this chapter I will introduce some complimentary approaches using velocity.

Checkout my appearance on the RTS podcast for a look at how RPE and VBT can work together →

Understanding Readiness

Readiness is our ability to perform a given task at a given moment. Sound asleep in the middle of the night our readiness to do any physical task is a 0/10. But trigger the burglar alarm and seconds later we jump into action, with heightened arousal and a nervous system fully charged to deal with the intruder.

Readiness is not only influenced by time of day but is also task specific, readiness doesn’t have to be super high for taking the dog for a walk! In general terms, the more intense an activity the more arousal is needed to complete the activity and therefore the more important readiness will be to our performance.

Readiness is constantly changing subtly, with variations in performance seen between morning or afternoon training schedules (afternoon is best).

Power and jump performance for morning and afternoon training sessions in College athletes - afternoon training favoured higher expressions of power

When it comes to performance in the weight room, readiness (as measured by strength or power output) also fluctuates on a daily and weekly basis. A great case study highlighting this is illustrated in the graph below (Zourdos et al), three experienced powerlifters completed a genuine 1RM squat attempt every day for 36 consecutive days. The graph shows the actual maximum load lifted each day which fluctuated by as much as 10%, along with the overall trend of increasing strength levels across the experiment.

Simply put, readiness influences the quality of our training, serving as report card for our recovery from previous sessions. Understand that readiness is reflective of accumulated fatigue, motivation, as well as outside factors like sleep, stress and nutrition.

Velocity is a specific measure of lifting readiness

Velocity is a brilliant tool to measure training readiness for two reasons.

First, speed of movement is more sensitive to changing readiness than the load we lift or even the RPE of a set. While you might be able to lift the same load when fatigued, it will be more of a grind (closer to failure), this makes velocity a great early detection system to highlight days of low or high readiness.

Second, movement velocity for a given exercise is highly task specific, given it is in fact measuring the exact task you are planning to perform that day! Unlike general readiness indicators like questionnaires, hydration status, grip strength, or HRV, the velocity on your warm-up sets - when compared relative to recent performance - is a highly specific indicator of your ability to perform that movement on that day. Plus it requires no additional testing or work to be done at the start of the session in order to gain this readiness data - simply log best rep velocity on each warm-up set to see how you are performing as the load increases.

How to determine low or high readiness: The 6-week average

Velocity on a single set cannot determine readiness in isolation, it’s only when this is compared with an individuals training history that we can paint a picture of readiness status from velocity.

The most effective way to do this is by comparing today’s best-rep velocity with an average from the past 6-weeks for that given exercise and load. A 6-week average creates a relevant and stable baseline to compare against for your recent training performance.

Lifters tend to use consistent progressive warm-up weights (Eg. 60, 100, 140 is common ramp up if you work with 20kg plates), so it is quite easy to accumulate large amounts of relevant average data from performing those sets each session.

An example of high and low readiness using the traffic light system.

I have created an automatic traffic light system for comparing today’s session with the 6-week average. This creates a simple indication of how today’s session is shaping up: green for high readiness, yellow for slight fatigue, and red light for low readiness.

I particularly like using multiple sets across a range of loads to help me determine readiness.
A single “red light” set means very little if the rest of my sets are green, it could just be a mis-groove or low intent.

You shouldn’t use readiness testing as an excuse to do less but instead be aiming for green lights so you can stick to the plan as best as possible!


Knowing your readiness status is only part of the battle. The critical step is to take action on this intel by applying autoregulation.

Autoregulation is the process of making programming responsive and flexible, taking into account specific markers of readiness such as velocity, power output, or ROM variance. Autoregulation is a tool for coaches and athletes to adjust training in real-time should the need arise.

Sometimes adjustments are pre-planned and automatic, hence the auto in autoregulation. For example, a new velocity PR on your work set may automatically mean you increase load by 5kg on the subsequent set.

Alternatively adjustments can be determined in-the-moment after considering a variety of readiness inputs both subjective and objective.

Typically, the more experienced a lifter is, the less pre-planned their decisions are and the more they can use self-awareness to be responsive in the moment. A more impulsive and “number-hungry” lifter might choose to pre-plan their autoregulation decisions, taking the emotion and adrenaline out of the equation.

A key misunderstanding in applying autoregulation is that low readiness means you have to drastically change your planned session, skipping the workout entirely, or cutting volume and intensity by huge amounts. This is simply not the case; most of the time autoregulation will provide a slight nudge to a planned training session. When velocity data (or any indicator of readiness) does show you are in a low performance state, this is not an excuse to skip the rest of the session. Cutting a few reps or dropping the weight just a little (2-5%) is all it takes to calibrate a session, avoid the grind and accelerate recovery.

Autoregulation is much more subtle than most people imagine, a huge deviation away from the planned training should be incredibly rare.

Autoregulation Strategies

There are dozens of specific practical ways to apply autoregulation and readiness assessment strategies into your training, here are just a few.

Determining reps with intra-set velocity loss

Using velocity loss to adaptively determine changes in reps is one of the simplest ways to autoregulate training. It can be done in real-time and requires no data storage or training history.

In this method we place a threshold (also called a cut-off) on how much velocity loss can be accumulated across repetitions before ending the set. It is therefore possible to control the proximity to failure and volume for each set. The greater the velocity loss allowed the more fatiguing and closer to RPE-10 a set will typically be.

  • 40% velocity loss is usually considered very close to the point of failure which is logically quite fatiguing,
  • 20-25% seems to be an optimal amount of exertion for developing strength without the accumulation of too much fatigue, and
  • 10-15% fatigue would be used during a taper, in-season training, or for specific power dedicated training exercises (olympic lifts and jumps).

Working to fixed velocity zones

The velocity zones are a whole thing that I have covered in a previous blog, and mostly they are poorly utilised in training. One way you can use them effectively is to prescribe a fixed velocity zone as a way to autoregulate both load selection and rep count during training.

To do this, give an athlete an upper velocity limit that triggers the transition from warm up sets to work sets. The athlete warms up, adding load to the bar until the best rep for a set falls below a pre-determined velocity, say 0.45m/s. At that load the athlete has now begun their work sets, completing the prescribed sets and reps at the load they first lifted when they crossed the 0.45m/s threshold. The lower this starting velocity the heavier the load and closer to 1RM the session will go.

This is a form of load autoregulation, the load was determined by velocity during the warm-up sets, which itself is a product of readiness on a given day.

Once working sets commence, we can add a velocity loss threshold to autoregulate the rep count within each set. Taking the example above, the work set load was determined when the athlete reached 0.45m/s, each work set then ends when they reach a 25% velocity loss across the set (ending around 0.34m/s in this example).

The larger the velocity loss allowed the more reps are completed and the close to the failure a set is taken.

This autoregulated zoning of training is a great way to apply both progressive overload and autoregulation simultaneously. We can build intensity in training by lowering the velocity threshold with each 4-week training block, for example: 0.45 → 0.4 → 0.35 → 0.3. This would lead to a progressive increase in load used for the work sets.

Simultaneously we could have a step-wise reduction in volume via a tightening velocity loss calculation 25% → 20% → 15% for example. This would lead to a reduction in the training volume.

This is just one example of this strategy at play, it can be utilised in a number of ways and combinations to suit your goals.

Traffic-light progression with the 6-week average

By far my favourite autoregulation strategy is to take a 6-week average of all your warm-up sets and compare todays best-rep velocity with this 6-week average.

Take for example a bench press session with a 40/60/80/90kg warm-up progression.

Calculating the percentage difference from today’s best rep velocity on each warm-up set with the 6-week average for these loads gives us four data points to create a contextual picture of today’s bar speeds specific to the bench press. By using multiple sets, and a 6-week average we can effectively smooth out any outlier data points creating a reliable picture of readiness.

Screenshots from the Metric VBT app showing the performance tracking and velocity based training features.
Readiness in action. Screenshot 1 shows a positive Trend score for the Trapbar Deadlift, image 2 shows a comparison between load velocity profiles on the back squat while image 3 shows best rep and set average velocity over the past 6-weeks for the Trapbar Deadlift

Several red and yellow flags might suggest a low readiness day, leading to a lower volume prescription for the days work sets. Still doing some work, but not going as hard as initially planned to allow more space for recovery.

A high readiness day by comparison would be marked with green flags. The pictured example shows green cells whenever velocity is above 97.5% of the 6-week average for that load. This green light suggests today’s readiness is in a great place to push hard for the work sets!

Why 97.5% and not 100%?
Near enough is good enough for readiness in this system, a 100% threshold is too strict and would result in too many sessions with a taper or deload, leading to detraining.

We don’t need perfect readiness to continue with a full planned session, we just have to be close enough - training hard is still the goal here! As athletes and lifters we want to NOT apply autoregulation in the gym, squeeze out green lights and follow the planned session.

But it is handy to be able to objectively assess those times when readiness is genuinely low.

This traffic light strategy requires a system to store your velocity training history with the ability to easily access this in real-time. This feature is built directly into the Metric VBT app with the Trends analysis feature.

Want more autoregulation applications?

These are just some examples of how we can use velocity to determine readiness and make modifications to training with autoregulation. Many more detailed practical examples can be found in the resources available when you sign up for my newsletter (linked below).

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References and resources

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