While social media buzz has rekindled the old concept of training monotony, I believe we should stop using training monotony as a way to summarize a program and start focusing on modeling with the assistance of classical evaluation using strain indices and workload variability.
Training monotony is an important element to making an athlete’s season successful. As coaches improve the ways they use biological modeling, we can expect training monotony to rapidly evolve to accommodate the new innovations in coaching science. Total load and type of load stress will develop as finer metrics of adaptation, and coaches will need to consider how the body responds to types of stress, not just totals and accumulation.
New research shows that spikes in workloads are clearly factors in non-contact injuries. At the same time, the slow boil of low variability in training with moderate loads warns us that the stimulus is too conservative, and the rest is not deep enough to restore athletes.
Loading the body will never truly be represented by bar charts because our bodies are more complicated than one summary on a graph. These simple visualizations and scoring, however, provide a good start to estimate work. The combination of acute total daily loading, weekly, or microcycle training monotony, and the interaction in a strain score helps safeguard against overtraining and injury.
In this article, I’ll define training monotony and explain its value to coaches and how to improve it without compromising training goals.
What is Training Monotony Scientifically?
It’s easy to mistake training monotony as the repetition of doing the same thing over and over until boredom sets in. Instead, it’s actually a metric that evaluates loading fluctuations. An athlete can become mentally bored with a training program that still physically promotes improvement.Training monotony is a metric that evaluates loading fluctuations rather than exercise repetition. Click To Tweet
Training monotony audits the variability of the load but doesn’t promise adaptation or even improvement. The challenge with sports training is to make sure that biological loading is effective while motivation, or willingness to train, continues with physical improvement.
Sports performance training concerns acute loading and changes in loading over time. Strain refers to how hard someone is working based on the accumulation of work done over time, usually the week.
Many sport scientists are currently researching how daily load, periodic monotony, and the resulting strain from the relationship of the two affect performance.
This concept was used decades ago as a training tool to reduce poor performance in horseracing. In the article, “Monitoring Training in Athletes with Reference to Overtraining Syndrome” (Medicine & Science in Sports & Exercise, July 1988), Carl Foster stated:
“When training, conducted on a ‘hard day-easy day’ basis, was incremented by increasing the magnitude of training on the ‘hard’ day, the horses responded appropriately and improved their performance in response to the increased training load through several progressive increases in the training load. However, when the training load on the ‘easy’ day was increased, the horses decompensated rapidly, developing symptoms consistent with the equine equivalent of overtraining syndrome.”
During the 1990s, progress was made estimating workload and loading variation (training monotony). Many of the calculations, however, involved arbitrary units from rate of perceived exertion (RPE) and heart rate (HR) data that provided TRIMP scores.
Yes, this can help estimate load, but lack of variation is simply not an issue of boredom. It’s an issue of chronic overloading.Lack of variation is an issue of chronic overloading. Click To Tweet
A great overview of loading, training monotony, and strain can be found in the article, “Applications of the Session Rating of Perceived Exertion System in Professional Rugby Union,” written by Dr. Tom Comyns and Dr. Eamonn Flanagan (Strength and Conditioning Journal, December 2013). The article illustrates the interplay of how these three variables look using example data in the graph below.
The article shows how the calculation of loading can help coaches who are learning how to monitor core variables.
What can coaches do to evaluate both subjective and objective data along with measures provided by sensors and other instruments? Imagine looking at GPS, blood biomarkers, heart rate variability (HRV), heart rate data, and weight room power values. It’s very messy and unexplored by most sport science research.
New science will come from analytics produced by athlete monitoring systems that gather all the inputs. We will no longer use systems that focus on one data set. Sport science will be more applied, faster, and far more flexible.
With strain scores, coaches can estimate workload totals and trends that may show the risk of overtraining. Training monotony is about the variation, and a better way to look at variation is to consider the rest density of work and absolute loads. These factors must be included to create perspective.A better way to look at variation is to consider the rest density of work and absolute loads. Click To Tweet
In the future, we’ll be modeling biological factors and moving away from a singular focus on arbitrary units. Coaches will benefit from looking at data summarizing estimated daily workloads, monotony of the week, and strain scores over multiple weeks.
For those with small budgets, simple RPE and TRIMP scores are great starting points. But as athlete values increase so should the resolution of data detail and width of the data type.
Here are simple suggestions to help coaches see clear data come to life.
- Subjective Questionnaires and Micrologging: The value of psychological feedback and short descriptive communication reflecting the athlete’s state of mind is golden. It takes only one minute a day. As smartphones use video to capture short clips, facial coding and transcripts will soon enter the sports performance world. We can expect the cost to go down and convenience to go up to help deliver more data to the right people. The goal is to create better human-to-human interaction.
- Heart Rate Recovery and Daily HRV: TRIMP scores, restoration trends from weekly recovery sessions, and daily HRV indices combine to create a great composite metric for physiological loading. Breathing rates and other data points also add value. As the market becomes more embedded, we’ll see interest in simple HR information rise.
- GPS and Player Tracking: Currently, player motion data mostly shows center of mass displacement and deceleration and reacceleration. As foot sensors and smart fabric evolve, we can expect output from the ground, field, and court to be more usable.
- Weight Room Management: Bar tracking is evolving. In the weight room, simple jump profiling and increased precision with outputs provide information about neuromuscular strain and response. Coaches can isolate and extract pure weight room data and compare it to the other data groups or make one giant daily score. I find composite data tricky, so superimposed line plots are a good start.
In the Real World, Does Training Monotony Matter?
A strong focus on training in Olympic sport is more important than team sport; professional competitions are entertainment. Because team sport has so little time available for training, in general, it’s fair to ask if it’s worth worrying about small factors like training variability.
There is no black or white answer. I argue that the better prepared the athlete, the more training monotony matters.
Baseball season, for example, has an enormous number of games, and the season can be very grinding and difficult to manage. Simple strategies to decrease reps and sets and focus on increasing intensity may be scoffed as too primitive, but several teams have succeeded with this approach.
Variability without compromising purpose is necessary for athletic performance. Burnout occurs when athletes are always on “on” over a period of time. Confusion exists when the variation of monotony is mistaken for variation of modalities or environments. I argue that they have distinct differences but can also overlap.
Real World Considerations:
Stimulus Variation: Stimulus variation refers to the type and product (intensity and duration) of a modality over time. Frequent alternation usually reduces mental and physical overtraining and pattern overload. Classic periodization literature addresses the need to vary the stimulus to break plateaus.
Variability of Load: Variability of load refers to reducing a static pattern of monotony found with Foster’s research. Low variability combined with a low load is a monotony problem. Heavy loading without change (most likely rest), though, is a bigger concern because of absolute work performed repeatedly. Density is very similar to training monotony, but we shouldn’t confuse the two.
It’s important to know the difference between burnout and staleness. An athlete can be stale and overtrained at the same time, but many who athletes are stale are not overtrained. Training monotony is a very crude way to look at density and lack of rest.Training monotony is a very crude way to look at density and lack of rest. Click To Tweet
How Modeling Can Improve Training Monotony Scores
As we stare more and more at numbers, our observations of people may blur. Subjective information from athlete or coaching feedback is popular because it’s non-invasive and readily available. While convenient, sometimes perception becomes deception, and we must be careful not to completely depend only on reported feelings.
Periodization is experiencing a paradigm shift away from theoretical ideas to biological modeling. When we evaluate the training calendar and the human body by resorting to crude statistical analysis rather than monitoring outputs and inputs, we’ll always have athletes who slip through the cracks.Periodization is experiencing a paradigm shift away from theoretical ideas to biological modeling. Click To Tweet
As coaches, we try to give athletes a series of “recipes” or biological inputs to drive change. How the athlete responds varies because readiness and fitness are moving targets. What improves our aim is better vision (microscope and sensors) and experience working with people.
We need to improve the precision of the inputs and outputs (workout design and measurements) while finding a way to understand how much training hits the sweet spot.
I’ve summarized simple factors regarding modeling here.
- Appropriate Dose: The magnitude of loading and the intelligence of selection based on feedback and analysis.
- Management of Dose Types: How all of the various systems in a plan are responding to each other. Management is highly coordinated by feedback about readiness that’s expected from the projected responses, so a good management rating is actually a reflection of precise modeling.
- Recovery Rates: The time it takes for the biologic system to restore and repair after training.
- Adaptation Rates: Accepted periods of time that create a meaningful improvement to the body.
- Detraining Rates: The decay slope of the body’s biological systems, specifically when compromises are made and training has ceased.
In other words, we should design training based on biology and time, not on a guru’s periodization scheme using esoteric block phases that tout alluring and near fantastical potential.
How to Plan to Improve Training Monotony
The solution to training monotony includes the diagnostics of a program state, such as overtraining or tapering effect, and the strength of interventions. Measurements create an objective standard everyone can understand. Coaching is about raising and breaking those numbers for better performance.
Interventions are more complicated than Hi/Lo or easy/hard programs, but moving too far away from loading and resting cycles is unnecessary. The guidelines below rely heavily on planning before transitioning to monitoring and modeling.
To improve outcomes with planning, the first step is to keep records of best performances using simple and standardized testing and then to augment those scores with backward planning based on the calendar. Biomotor scores such as speed, stamina, suppleness, skill, and strength generally must improve, or transfer becomes a “wait and hope” approach.
After getting concrete standards of performances, the second step is to see how much time the athlete has available and their current readiness. An athlete with less time and a low starting point simply has less favorable factors for improvement. Modern sport involves managing the end of season “brain drain” caused by travel and intense competition and the need to rehab when the mind is saying “get away.”
The third step is to break down goals into realistic benchmarks. This is the hardest part. Making predictions and projections aren’t easy when working with different athletes and their individual schedules and readiness. It’s hard to map out a plan when an athlete walks in out of shape with a lingering injury. The sliding point of when an athlete is able to perform and likely to perform well is why I consider coaching science a dark art.
How to Monitor to Improve Training Monotony
Reactionary approaches to modern monitoring in sport are a fool’s errand. But because professionalism doesn’t always match utopian performance goals, sometimes one has to compromise and rest more and train less.
One way to counter the “read and react” approach is to anticipate issues in advance based on experience.
Below are common problems and uncommon effective solutions I’ve seen used by teams and coaches to get better results by reducing unnecessary strain and to improve monotony scores when competition and training are heavy.
American Football Practices
Training density must be decreased, and volume must be managed carefully. Head and position coaches who focus on the needs of play calling may not see the fatigue in their athletes.
Bill Walsh hinted about fatigue management, which means shifting to virtual reality brain work to spare the legs and reduce the impact of practices. Performance coaches need to understand how much work can be removed to allow time for lifts and how much time to include to facilitate recovery.
Because high lactate levels usually correlate with elevated cortisol, time and bout ratios can reduce mental errors. Impairments in cognitive function occur when fatigue increases acutely and chronically. This means it’s important not only to rest athletes physically but also to avoid mentally overloading them with meetings.It’s important to rest athletes physically and to avoid mentally overloading them with meetings. Click To Tweet
Coaches can learn to personalize practices with the improved use of video simulations and planning to allow athletes to practice when legs are fresh. It’s possible to have athletes perform the same number of snaps over time by distributing snap practices based on biology. This will keep team coaches happy while providing pedagogical rest for the athletes.
Coaches can create a utopian weekly program by resting more on Thursdays, leading to fresher Wednesdays and Fridays, and prescribing small doses to avoid flattening the athletes for Sunday.
Soccer Weight Training
Many elite-level teams barely strength train their athletes because competition becomes too tight for intense work. I believe that, since NBA starters lift consistently, soccer teams who compete once or twice a week can do better.
The solution is not to make adjustments in weight training. Instead, players should have more total time away from field work and have their rest day replaced with pool training and circuit work. Days off should be sparse. Low-intensity pool sessions facilitate fitness and support the analgesic responses to brain chemistry.
Pool work on off days can reduce the volume of small-sided games. Unlike American football, soccer can be manipulated with field size. Lifting twice a week with very small volume and high intensity can occur before or after games, like they do in baseball. I have not seen any research that shows lifting on recovery days to be less effective than other off-day options.
Distance Running Base Work
Overuse injuries doom seasons more often than failings of the cardiovascular system. Distance running tends to have volume and variability problems. Because speed is static during base work, most programs are based on mileage. A better solution is to infuse rest that is based on HRV indices and to examine hematological parameters.
Weight training and lower speed, high volume running is commonly used. Speed, however, is a skill, and running technique and higher velocity runs should be introduced early.
With base work, most of the risks related to training monotony are orthopedic (overuse problems) and the depletion of iron stores. Cross training may help decrease the risks. Even so, running long causes constant strain and should be introduced incrementally and precisely to remove stagnation and possible URTI (illness).
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