Workload monitoring??

The flawed touch of geniuses

1900 words; reading time ~ 9 mins, 30 secs.

…or should that be the touch of flawed geniuses?
An emerging obsession in strength and conditioning has been the challenge of regulating an athletes’ exercise stress and recovery balance. The apparent solution has been to harness science and technology and measure/monitor either workload or the athlete’s responses to workload. Armed with those ‘numbers’ coaching staffs have been able to continue to ‘redline’ athletes, safe in the knowledge that; “we’ve got this – we know what we are doing here!” ‘Redline’ refers to the red marked point on a rev counter that indicates the highest speed that an engine can supposedly be spun without damage (as dictated by the strength of the engine’s moving parts). I’m liking the redline analogy here because it infers that athletes are being trained to a perceived known safety limit: the highest point or degree considered safe. Now I think that this approach is hugely problematic – let me explain why.

workload monitoring dominates the sporting landscape
The rise of workload monitoring within sport has been meteoric. It’s gone from novelty to frequently used tool, to a mandatory part of any serious athlete’s preparation. The most perplexing thing for me has been that despite an absence of demonstrable benefits, workload monitoring has not only endured but has seemingly proliferated. From my sideline perspective, there have been a number of factors that have made this possible.

the evolution of approaches to sports training
Sports like rowing, cycling, and swimming have had long histories of high training workloads and relatively few competitions. Most team sports have either become professional or now mimic professional approaches to fitness preparation with their athletes. In doing so they have adopted and adapted some of the training practices of those aforementioned sports, but they’ve done this in an environment where their athletes have multiple weekly competitive events. To illustrate this, back in 1992 when a colleague and I collaborated on All Black fitness, we asked the players how much time they could commit to fitness work. Remember, this was the pre-professional era and most players had full-time day jobs. We were still taken back though with an average response of ‘around 6 hours per week including practices’. So that left probably around 3 hours/week for any additional fitness work. Rugby became professional in 1996 and soon after that, the line was crossed where conditioning became longer and more arduous than playing games. The (il)logical extension of this is that many contemporary sports performance models either; a) minimise competition exposure to leave a greater window for training or b) attempt to balance a high training volume concurrently with the high demands of competition. The former (a) is just too ridiculous for me to get my head around. Given that the best preparation for playing a sport is playing that sport (one of the first principles of exercise – Specificity), I just don’t get that anyone would contemplate holding an athlete out of competition so that they can get fit for competition!

The rise of the machines
Technology and the blazingly fast innovations that have occurred have also played a major part in making workload monitoring part and parcel of sports performance. The aggressive marketing of these technologies, in combination with the rule changes that have permitted wearable technologies to be used in competition, has meant that suddenly more information could be made available for real-time monitoring and later off- line analysis. And we know some people thrive on information.

The invasion of the nerds
As an off-shoot from sports science, we have had the emergence of performance analysis and performance analysts. This growing profession has taken the lead in providing game analysis, player tracking and monitoring, and has literally changed the face of competitive sport. Hats off to these professionals for all that they do and the insights that they provide (and sorry for that nerd subtitle). So it’s been a perfect storm really – technology, tech-savvy professionals, and sports searching for an edge have opened the door for generating lots of numbers.

On to workload monitoring
I’m not going to take up space and your valuable time by discussing all of the workload monitoring methods in use or proposed (there are hundreds), but rather focus on the challenges. Greenham et al (2018) have a great review that compares various monitoring methods with suggested criteria for effective workload monitoring. So go read their paper – spoiler alert there is no obvious winner.

Led by sports scientists and strength and conditioning practitioners, most of the thrust for workload monitoring has focused on methods for detecting the threshold or advent point at which functional overreaching gives way to non-functional overreaching (NFO), or overtraining syndrome. Strength and conditioning coaches and medical staff are also going to be interested in any relationship between workload and injury occurrence. Greenham et al’s (2018) listed criteria emphasise the need for a biomarker that can associate that ‘threshold point’ with actual performance or health decrements. Of course, that is always going to be very difficult.

We can monitor but….
Workload biomarkers also need to be able to detect with high sensitivity and specificity. Meaning that any monitoring can’t wrongly assume that NFO is occurring, nor can it afford to miss the onset of NFO. False positives are obviously going to be counterproductive (we don’t want to needlessly pull an athlete out of training) and false negatives kind of negate the whole purpose of monitoring. Aside from these criteria, the biggest challenge with workload monitoring is the temporal efficiency of the biomarkers. By this I mean any effective monitoring must be able to detect NFO before it occurs, or at the very least as it is occurring. Unfortunately, most current workload monitoring methods involve a significant time lag between fatigue ensuing and an alarm triggering – they are telling us days and sometimes weeks after it’s happened! While retroactive detection of fatigue thresholds could theoretically be instructive for exercise professionals, in reality, the individual variability of training responses and contextual differences mean that there is often little to be learned other than a global sense that the training load or training block might have been too high for that individual under those circumstances. Workload monitoring also needs to be non-invasive (for obvious reasons) and can’t disrupt any planned training or competition. Given that monitoring needs to be ongoing and repetitive, biomarkers need to be cost-effective and have a high test-retest reliability. So we are really asking a lot of workload monitoring tools!

One of the challenges is that ‘work’ or training load is not necessarily a single, easily identifiable entity. There is the load prescribed or programmed, the load completed (and possibly measured), and the load perceived. Hogarth et al (2014) and others have shown that an individual’s perception of fatigue invariably influences their sense of effort and will cause them to either up- or down- regulate their exercise capacity. So given the role that perception plays with fatigue, if you are not measuring or accounting for fatigue perception in some way, your workload monitoring is really just counting stuff. Session GPS data without any sense of how the athlete found the workout is pretty much meaningless. Exercise professionals need to understand how hard somebody is finding exercise to really get a sense of how appropriate the load actually is, for that person in that situation.

Because we can?
It seems that organisations often decide on workload monitoring as some sort of panacea for performance; a way of seeking improvement without really understanding the complexity of the questions being asked. There needs to be a clear rationale for workload monitoring and a need to be strategic with how workload monitoring is done. I’m talking absolute clarity as to why we are monitoring, what we are measuring (and not measuring), how will we measure and how often? And of course, the really important bit – how will those numbers be analysed, interpreted and reported back to athletes and coaches? Lastly what actions will be taken in response to any apparent triggers?

How can that be a problem?
So why do I see current workload monitoring as problematic? Clearly, you’ve sensed I’m a skeptic! I think that workload monitoring definitely has a place and utility, but not in the places and ways that it is currently being used. I can see the point of monitoring workload to obtain a broad-brush overview of the training stress that your athletes appear to be experiencing. But I think that monitoring is a fairly blunt instrument and should not be something that we trust anywhere near as much as our eyes, ears, and experience. There’s a tendency with numbers to assume that as long as someone falls “within defined limits” that all is well; in that case we might be missing other telling benchmarks. Aside from creating a distraction, I think that numbers can give a false sense of security. It’s a bit like those flotation cushions under airplane seats. Yeah thanks for those, but I’m not convinced you are really protecting me from much! So I’m going to call BS on the ability of workload monitoring to prevent injury, because we know that injuries will still occur. As far as fatigue goes, well who really knows whether performances are being compromised by fatigue? Everyone is pretty much following the same rigorous training schedules, so it’s likely that everyone is redlining. We kind of have no real way of knowing.

Finally, we are not demonstrating great professional competence here. Aside from the ethical implicartions, running a programme based on numbers is not respecting the most basic of exercise principles. We need to care much more about the athlete than that, and we need to remember ‘the sport’. Maybe we need to ask, what does this athlete need rather than what can this athlete manage. We need to remember that success is defined by what happens on the court, not what transpires on the training field or gym. Surely, it’s about playing the sport and performing – how did we ever let it become about the training?

It’s not all bad – I realise that as exercise professionals, we do tend to get caught up in our passion for new training methods and hacks, and with the enthusiasm of our clients. But in the process, we can unwittingly forget to think critically. I’ve suggested that monitoring is a bit of blunt instrument – well that blunt instrument may provide a well-timed alert that things are not proceeding as planned and perhaps we need to ‘button off.’ For an injured athlete preparing to return to training and competition, workload monitoring can provide an objective means of strategically and methodically progressing the load that is applied to the recovering injured body part – so I like it for that! Gazing in on the fitness industry and its various offshoots, I can’t help but think that workload monitoring should be mandatory within gyms and personal training. I’m sure that most competent exercise professionals check on how a client is feeling but maybe this area requires more than cursory attention. Novice exercisers often struggle with understanding the sensations that they should be experiencing with physical activity. So numbers could add another dimension here, and improve gym experiences.

I’ve focused here on some of my concerns about workload monitoring, but I don’t mean for it all to read as gloom and doom. I’m confident that emerging methods and technologies will get us closer to understanding the thresholds for NFO and injury – but eyes, ears, and experience are never going to go out of fashion!

That’s it, I’m exhausted from thinking and writing about fatigue – time for something new.

Best, Phil

Selected references:

  1. Greenham, G., Buckley, J.D., Garrett, J., Eston, R., Norton, K. (2018) Biomarkers of Physiological Responses to Periods of Intensified, Non-Resistance-Based Exercise Training in Well-Trained Male Athletes: A Systematic Review and Meta-Analysis Sports Medicine Published online–018–0969–2
  2. Hogarth, L.W., Burkett, B.J., McKean, M.R. (2014) Understanding the Fatigue-Recovery Cycle in Team Sport Athletes. J Sports Med Doping Stud, 4(5)–0673.1000e1