by Carl Valle

After reading several blogs on HRV and physiological monitoring with athletes, I wanted to respond publicly on what I consider practical monitoring in applied sport science. I currently question if real data is being collected longitudinally, or are coaches overreacting to a few acute responses over a short period of time?

Heart rate variability (HRV), specifically in the form of mobile solutions such as ithlete, has been a valuable solution for monitoring athletes for nearly four years. Athletes of all levels understand that their bodies are their business, and evidence based coaching is growing, especially on the data driven approaches. Athletes are not ignorant to the latest developments, and want to work with coaches who have experience providing the current best practices in recovery and planning. In this article, I will share what I consider the three pillars to monitoring and how anyone can create a high end solution for athletes ranging from weekend warriors to Olympic athletes.


Who has your Athlete’s Data?

With organizations in professional sports being slow, many athletes simply go to individual private coaches or agile facilities to manage their training. This is perhaps the least discussed component of elite sport, nobody wants to talk about the fact that the private coaches are sometimes influencing games more than the team conditioning coach or medical staff. The reason is that the collective bargaining agreements, or CBA, limit athletes in training and pressure them to get back quickly after injuries. The combination usually results in more injuries and performance decreases in team sport. Even Olympic sports are now affected by the new economy of professional athletes.

The problem of athletes wanting to safeguard their careers leads to freelancing of both medical care and training. An individual coach placing nearly 100% of their efforts into one athlete without the constraints of bureaucracy places them ahead of the curve of everyone else and athlete appreciate this. Some athletes are even self-educating themselves and skipping the middleman and elect to do their own training and guiding their own medical decisions by using third party medical solutions. Athletes want cut and dry answers that are unbiased and objective, and if evidence in the form of data is not there, those who have the right data and present in a clear way will get the respect and attention of the elite athlete. Team coaches are feeling the pressures since the inability to get data will, at times, reduce their abilities and undermine them. No matter how progressive a team is, they will be two to three generations behind the smaller entities. Nothing is more nerve wracking than sitting down with a general manager who has already had a “discussion” with a private coach and is sitting in the office awaiting your “explanation” when he is fully equipped with data you don’t have.

Sports Analytics – Can’t analyze data if you don’t’ collect it first

One major problem is the absence of relative data because of the huge influx of junk data. It’s far more convenient to show sensor data yet the most useful data sets are absent because of inconvenience. The trends of consumer level products is solving the problems of active capture (individual effort of data acquisition) to passive or service style capture (outsourced solution). No matter how great the algorithm or Business Intelligence solution is, the lack of data will cripple any sport science or medical athlete management system.

Companies are realizing that additional data sets are overwhelming coaches and medical staff, so many teams and facilities are outsourcing the data collection and even analysis with software or consultants. Web or mobile options are making data collection easier, but real world challenges and business models are changing the rules of the game at paces many find just not worth doing internally.

I have spent 15 years coaching Olympic sports and nearly the same amount of time in technology, and I can say that even I have a hard time keeping up with the evolution of what is going on now. If teams address the fundamental needs and master the basics, the next innovation will be appropriate instead of a lot of window dressing.

Monitoring the ABCs

I consider the primary pillars for monitoring to be activity, blood, and cardiology or the ABCs. While I do incorporate more now since DNA testing and other more detailed options exist from the Quantified Self movement, the primary branches are still the same.

  • Activity is what the athlete is doing or not doing, so while sleep is not active, it’s just as essential as the sprints and weights an athlete will do in track and field.
  • Blood analysis is not just lactate, but the use of quarterly blood analysis to get objective indicators of nutritional compliance and changes to the training.
  • Finally, a good heart rate monitor or other sensor can get simple data such as the recovery rate after active rest sessions and now HRV and resting HR in the morning, to reflect the previous day’s load in sort of an objective RPE.

Those three indices are part of my KPIs in training and I have found they work together seamlessly when programs like iTrimp, InsideTracker, and ithlete are integrated. All three are virtually cloud based sport science solutions for clients ranging from small teams to major gym clubs looking to provide precise monitoring of their clients, be it the corporate professional or the elite athlete.

Building your own Algorithm

Coaches and medical professionals are working more collaboratively as delineation or segregation of roles are now more fused and cooperative.  Decisions are being debated over and over again because the general process of making choices are often not written down, never mind the data of what helps drive decision making. Having a decision making tree or mind map are crude ways to build an algorithm for groups of organizations looking to be on the same page. My training algorithm is not elaborate, as the perfect model is too inflexible to make decisions. In fact a good algorithm is a set of small simple and clear calculations that help summarize the problem and make actionable choices.

Training Load Score + Recovery Estimate = Change

Obviously the above algorithm is not useful unless the details of training are present and some sort of objective recovery data is available. Many times coaches are frustrated with beautiful programs rendered useless by athletes not doing their job with the rest and nutritional needs, so they are forced to compromise their programs.  The universal challenge of monitoring the “other 22 hours” in the day is difficult because while we can train athletes, we are not present to see what they are eating and what hours they are keeping in the sleep department. Recent advancements in sleep devices are helpful, but nutrition is hard to monitor since unlike other systems of the body that sensors can help with, no current stomach sensor exists to get precise nutritional information outside a DEXA scan or weight scale. While sleep and nutrition data help show the support streams, their interaction with the training load needs a measurement to gage how those variables help drive adaptation after the training load is administered.

Daily, Weekly, Quarterly- The rhythms of collection and analysis

No rules exist on the frequency and timing for data concerning blood, HRV, and activity, but here are some insights I have found to be useful. Obviously the more frequent the data sampling the more clarity and confidence one has, but from a practical manner, the rhythm of data collection must not interrupt the day to day needs to actually get things done.

No rules exist on the frequency and timing for data concerning blood, HRV, and activity, but here are some insights I have found to be useful. Obviously the more frequent the data sampling the more clarity and confidence one has, but from a practical manner, the rhythm of data collection must not interrupt the day to day needs to actually get things done.



The strain of training and the absence of it (rest) is the most obvious data collected. Coaches are rather good in writing workouts and finding ways to stress an athlete, but the effects of the stress are not as well analyzed since internal physiology use to be limited to research or lab settings. Now the research bottleneck of getting data at near lab quality is no longer a barrier with the new technologies and cloud analysis tools. Sport Scientists are finding themselves being replaced by software since much of the process of evaluating an athlete in testing was the job of the sport scientist years ago, now the PHDs are reinventing their positions as advisors as they do more than provide suggestions after a few lab tests.

Training loads are easier for more linear sports such as endurance cycling, but chaotic sports like Mixed Martial Arts are not as easy to estimate work since even the best sensors are poor solutions as of today. The skyrocketing use of GPS for team sports recently was exposed for severe errors in estimation with Martin Buchheit’s latest study.  While the improvements in player tracking are getting better, they are not accurate enough to see the complex interaction of gravity and anatomy. Screening in the form of portable motion capture and pressure mapping is solving the known risks with biomechanics, but GPS is more of a raw output with interventions that can’t be specific enough to address more than simple rest choices. I like a weekly microcycle set-up to see how the organization can be manipulated to get a good response instead of looking for the one magical workout.

Blood Analysis

Athletes can use samples of urine, saliva, tears, and sweat to get indicators of internal chemistry, but blood is the king for those looking to solve simple and complex problems in the body. A simple routine blood test can identify vitamin and mineral status, the chronic changes over months with metabolism and even profile hormonal changes from training. Countless times a blood test is used when all else has failed to work and very obvious information surfaces such as iron status being poor or the athlete is struggling with chronically low testosterone.

I have tested athletes since the late 1990s and am shocked how few people take advantage of the data one can get from a small sample. Nutrition is the hardest area to measure since even photo logs are not precise or valid to see what is going inside the athlete. Using a blood panel that covers a wide range of biomarkers four or more times a year can really share what happens over the course of a season or training year. Nothing creates more accountability than a combination of physiological and power tests over the season with blood testing. Subtle problems like energy during workouts can be cross validated with fasting glucose levels, blood lip problems and body composition changes which can indicate better food choices, and immune markers and low hemoglobin can warn if an athlete is being driven into a hole. Blood analysis does requires interpretation, but after three tests a trend is created, and coaches can audit the training program as well as the lifestyle of the athlete to see what is working or not.


Clearly HRV is not new, but the digital age of mobile devices and wireless networks HRV is now mainstream with athletes. After the 2000 Olympics a few of my athletes shared their experiences with fatigue monitoring. CNS and ANS measures were now available, but only the select few that had glutinous budgets, the top coaches and sport scientists at that time. Fast forward 13 years we have a way to get countless athletes simultaneously capturing their autonomic state and resting heart rate, and sending that data to a team system in the cloud. Coaches are now getting real time data up to the minute while being provided trends and the ability to send a SMS based on the data aggregated from the mobile devices. HRV summarizes many of the body systems, and using ithlete creates a major cultural change for myself and my athletes. Each day the athlete can invest just a mere 90 seconds to not only capture HRV, but input subjective indicators that help add more insight to the readings.

Athletes knowing that one is using the data daily will be compliant. Knowing the information is part of the training process and delivering a more accurate workout or training session will act as motivation alone. Daily HRV and daily resting heart rate is enough to warn one from getting to deep into overreaching from the use of the indicator lights with ithlete. It’s ok to allow for overreaching, as the team system allows you to review one month, three months or more for analysis of the day to day decisions. In addition to HRV, the use of recovery workouts are great ways to show fitness without straining the body beyond what it needs to maintain fitness.

Now that we understand the three primary pillars to physiological monitoring, in part 2 I will share in a specific case study on how to combine contemporary training and the ABCs into simple interventions. Included in the second article is ways in which we can use HRV as a lifeline, and how we can better estimate the training load with clever training and nutrition. I will include tables on blood analysis and share my experiences using different technologies to get precise loading of the athlete such as power devices and electronic timing.