Tag Archives: monitoring

How effective is pre-planned training?

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I was about 4 weeks out from Canadian Raw Nationals 2011 (powerlifting). I was on pace to hit personal records in all 3 lifts at a lighter bodyweight. I took a scheduled deload and when I started my last training cycle before the meet, the weights felt like a million pounds. I couldn’t fix whatever the problem was and ended up pulling out of the meet. This was a huge disappointment. I thought to myself that there had to have been a way to prevent this or at least see it coming so I could make adjustments in time to avoid such a disaster. I knew about HRV and considered using it before but held off. It was this meet prep disaster that inspired me to purchase the iThlete to determine how useful it is for strength athletes (see my post here for an explanation of what the iThlete is and how it works). It’s now been 8 months since I’ve been using this device and it has changed my whole outlook on managing the training process.

In this post from a couple of months ago I wrote about my observations with HRV. I also gave a vague explanation of how I was then going to use HRV to guide my training. At this point I’d like to share what I’ve learned from measuring my HRV since then.

  • I have not taken a deload week since late January. Typically I would deload after every 3 week cycle. The purpose of the deload was to allow my joints a break from the heavy loading, allow my CNS to recover from the heavy lifting and allow for optimal recovery so I return at a higher level of strength (supercompensation). I was pretty surprised to see that in nearly 2 months of training I have not felt the need to deload. Instead I have simply chosen to take a deload day only when my HRV score was low. I have squatted heavy every week during this experiment because my HRV was always at baseline or above on Mondays (Squat day). I have had to deload on only 3 occasions. All of these occurred on a Wednesday (Bench Day). I continue to make progress every week and therefore will continue with not taking a planned deload week. On my deload days I simply work up to the heaviest weight I can handle with zero strain or struggle for the same amount of reps I would’ve done anyway.

    For example, on Bench day when I needed to deload I was supposed to work up to 3 sets of 3 with a 4 rep max or RPE of 9. However since my HRV was low and I had to deload I simply worked up to 1 set of 3 with a weight that I felt if I added any more weight too, would cause me to strain. For the assistance and accessory work I simply cut the volume in half. The take home message (atleast so far) is that deloading should occur when your body will not tolerate intense training. HRV provides this information. What’s the point of taking a whole week to deload if your ability to adapt to stress returns to a good level within only a few days?

    I will experiment with planned overreaching in the future where I will purposely train heavy as my HRV declines and follow it up with a planned deload. This is more similar to how athletes are training. My concern with this method is the potential heightened risk of injury from training when HRV is low. See this post for further discussion on HRV and injury.

  • This past week was my spring break. I went to Cincinnati to visit my family. If you know me personally you are aware that I’m pretty strict with my eating. I eat a lot, but I stick to whole foods and avoid processed/junk foods. I also eat fairly low carb. Well, in Cincinnati I allowed myself to eat whatever I wanted all week. I was crushing home-made oatmeal butterscotch cookies, ice cream, nacho’s and guacamole, Cheesecake Factory dinners and desserts, the famous Cincinnati Chilli, pub food, etc. It was a disaster. Apart from the binge eating I felt very well rested, slept well and enjoyed some unseasonably warm weather.

    Cincinnati Chili

    It’s fair to say that the only thing out of the ordinary that would have been stressful to my body was my terrible eating. Well, my HRV declined after the second day and it got worse each day after. It only climbed back up again since I returned and resumed my usual eating habits. You can see in the screen shot below that my HRV steadily decreased the longer I ate poorly and started to climb back up on Saturday (returned to PA on Friday evening). Although we’re all well aware that nutrition plays a vital role in how we recover from training and perform, it was pretty eye opening to see just how important nutrition is. Such a simple way to improve performance and adaptation to training is to just eat well. How much time are we wasting busting our ass in the gym if we go home every day and eat terribly?

  • Lately, whenever my HRV is low I feel weaker. I found it interesting that on many squat workouts in the past 6 or 7 weeks I felt that I was fighting the bar, not finding my groove, etc, yet was still squatting heavy. When my HRV has been low (3 low days on Bench days) the weight would feel much heavier. 315×5 is a walk in the park for me typically. However, on a deload day it was a major grind. I really shouldn’t have gone that heavy on a deload. This leads me to believe that performance will be worse when HRV is low (consistent with research that I discuss here.) Since I’ve been able to squat heavy even when my technique felt shaky when HRV was high, it leads me to believe that performance will likely be better when HRV is high. I’ll be doing some research in the near future on collegiate football players to see if I observe the same thing.

My experience with HRV and the research I’ve read thus far has lead me to believe that pre-planned training for collegiate athletes is not optimal. It is common for strength coaches to program around Christmas holidays, spring break and so on. Keep in mind that holiday’s and breaks are usually planned deloading periods that mark the end of a given cycle/phase and will mark the beginning of a new one upon return. This may work if the athlete’s all lived the exact same lives and had the same genes as one another.

A common example of pre-planned periodization that I found on google images

Allow me to illustrate for you an example of how ineffective this method is not because the theory is incorrect (a debate for another time), but because it fails to account for the behaviour of the athletes. I’m going to provide 4 scenario’s of what many athlete’s on the same team may do over the break that will effect there adaptation to the previous cycle and readiness for the next cycle.

Scenario 1: The athlete heads to Florida for spring break and drinks alcohol every day, all day on the beach, parties all night and eats cheap restaurant food.

Scenario 2: The athlete goes home and although doesn’t drink or party all night, he eats terribly.

Scenario 3: The athlete goes home and rests all week and eats perfectly.

Scenario 4: The athlete goes home and trains at his own gym and therefore doesn’t get much rest.

Many football teams have over 100 players. This creates 100 different scenarios. It’s quite obvious that not every athlete will be prepared for the same training loads. Any strength coach is already aware of this and unfortunately has to do their best with what they’ve got. However, since HRV is sensitive to any stress that our body experiences, we now have a more accurate way to determine who is ready and who is not. This can prevent you from overtraining certain athletes, undertraining other athletes and most importantly reducing the likelihood of injury. If you so desired, you can investigate further into the personal lives of the athletes to determine why they are experiencing so much stress when the training isn’t the cause.

I realize that monitoring the HRV of all your athletes may seem impossible but the new apps that are available make it extremely easy and affordable. The biggest challenge becomes how you will handle providing different workouts on a day to day basis according to everyone’s HRV score. I’ll share my thoughts on potential ways to accommodate this in a future post, but I believe it can be done without too much burden.

Today’s post paints a picture of what my current thought process is based on my experience and the literature. I am really excited to get the research started on the football players. In my next post I will give an update of exactly what I’ll be doing, why, my hypothesis and all that good stuff.

Thanks for reading.

If you’re not assessing (the ANS), you’re guessing

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“If you’re not assessing, you’re guessing” is a phrase often used by strength and conditioning professionals to explain the importance of movement assessment prior to exercise prescription. Prescribing a program that doesn’t consider the athlete’s movement ability (or lack thereof) can end up causing problems.Essentially, you would be guessing that your exercise prescription is helpful when in fact it could be exacerbating a problem. I wholeheartedly agree with this. However this article has nothing to do with movement assessment. This was just my way of illustrating what my next point is.

I am going to apply the same logic we use for why we assess movement (to influence program design) with monitoring the function of the autonomic nervous system (ANS); if you’re not assessing the ANS, you’re guessing.

If you’re unfamiliar with what the ANS is and why it’s important I suggest you read this. In a nutshell the ANS governs “rest and digest” and “fight or flight” responses in the body. This is done without our conscious control. The two components of the ANS are the parasympathetic branch and sympathetic branch. Sympathetic activity is elevated in response to stress be it physical, or mental. Adrenaline is secreted and catabolic activity (the breakdown of structures) ensues. Parasympathetic activity is elevated in the absence of stress and functions to heal and repair the body.

We can monitor our ANS status non-invasively and inexpensively through heart rate variability (HRV). I explain how you can do this here.

HRV as an indicator of autonomic function can tell you a tremendous amount about your athlete’s responsiveness to training. I shared plenty of research in this post that lends support to HRV as an effective tool for; reflecting recovery status, showing better adaptation to training and even predicting performance. In a separate post I shared my thoughts on HRV as a predictor for injury.

Let me summarize what I shared in my initial research review post;

HRV reflects recovery status in elite Olympic weightlifters (Chen et al 2011), national level rowers (Iellamo et al 2004) and untrained athletes (Pichot et al 2002).

Cipryan et al (2007) showed that hockey players performed better when HRV was high while performance was rated lower when HRV was low.

Endurance athletes who improved vo2 max had consistently high HRV while athletes who did not improve vo2 max had low HRV (Hedelin et al 2001).

Endurance athletes who trained using HRV to determine their training loads had a significantly higher maximum running velocity compared to athletes in a pre planned training group (Kiviniemi et al 2007, Kiviniemi et al 2010).

Female athletes who used HRV to guide their training increased their fitness levels to the same level as females in a pre planned training group but the HRV group had fewer high intensity training days (Kiviniemi et al 2010).

(references for the above articles can be found in my original post here.

I’d now like to show some more research that lends support to the usefulness of HRV in monitoring athletes.

Mourot, L (2004) saw decreased HRV in overtrained aerobic athletes. Uusitalo et al (2000) also saw decreased HRV in overtrained female aerobic athletes.

Huovinen et al (2009) measured HRV and testosterone to cortisol (T-C) ratio in army recruits during their first week of basic training. The training was class room based (not physical) and therefore all stress can be considered mental. The authors found that HRV declined in several soldiers, though not all. This demonstrates that, what can be interpreted as stress is highly variable and dependent on the individual. The authors used the terms “high responders” and “low responders” to describe the differences among soldiers. Immediately I thought about the differences among athletes and how their bodies perceive stress. You can’t assume everyone is responding in kind to a training program. What is stressful for one athlete may not be as stressful to another.

All soldiers that showed decreases in HRV also showed lower T-C ratios. In contrast, soldiers with higher HRV had higher T-C ratio’s. Baseline T-C levels were not recorded so we shouldn’t draw any concrete conclusions however it appears that low HRV (increased sympathetic activity with parasympathetic withdrawl) is associated with a reduced T-C ratio.

Hellard et al. (2011) found that in national level swimmers, as HRV dropped (sympathetic predominance) there was an increased risk of illness. The drops in HRV that lead to illness were preceded by a sudden increase in parasympathetic activity the week prior to illness. The authors speculated that the preceding increase in HRV (parasympathetic/vagal activity) was a reflection of the body experiencing the first incubation period and that an increase in vagal activity was a protective response trying to modulate the magnitude of early immune responses to inflammatory stimuli. The subsequent increase in sympathetic activity and decrease in HRV occurs during the symptomatic phase of the illness.

In humans, increased sympathetic activity is generally associated with inflammatory responses while parasympathetic predominance actually inhibits inflammation. At this point in time I will not elaborate on this for the simple fact that I don’t fully understand it. However, we can speculate that if we’re seeing consistently low HRV scores in ourselves or our athletes there is probably an increase in inflammation occurring. Check out Thayer (2009) for more information regarding HRV and inflammation. Simon from iThlete sent me that paper and I’m still processing it.

When dealing with a team or if we train multiple athletes at the same time we need to be aware of how they are adapting and recovering from training. Work by Hautala et al (2001) shows that athletes will recover from exercise at different rates according to fitness levels (obviously). Basically, fit individuals recover faster and show less HRV fluctuation compared to less fit individuals. In a team setting, some individuals who are highly fit may not be getting a sufficient training stimulus while other athletes who are less fit can be overworked.

Kiviniemi et al (2010) found that females take longer to recover from aerobic training than males. This needs to be considered if you are training a mixed gender group.

Buchheit et al (2009) and Manzi et al (2009) both found HRV to be a predictor of aerobic performance.

I’m well aware that the development of athletes has been taking place without the use of HRV monitoring. There are many great coaches and trainers who have their own systems and methods of monitoring recovery in their athletes that work well.

HRV is a tool to use within your own systems. I have thoughts about how I would implement this in a team setting that I will share another time.

To truly autoregulate the training of ourselves or of athletes, we need as much information about present physiologic status as possible. Based on the research and my own personal experience with HRV, this technology takes much of the guesswork out of load/volume manipulation and training prescription. Training hard when HRV is low can be counterproductive and delay recovery. Training hard when HRV is chronically low can lead to illness, injury, overtraining syndrome and suppressed testosterone. Alternatively, increasing load/volume on days when HRV is high can lead to more favourable adaptation. HRV can tell us how stressful the training was for our athletes based on how long it takes HRV to reach baseline in subsequent days. HRV can indicate how much stress your athlete is experiencing outside of training. There are several indications one can take from a simple HRV measurement. Further research will reveal more correlation between HRV and sports performance.

I believe that to train an athlete optimally, we need to be assessing the state of the autonomic nervous system… otherwise we’re guessing.

References:

Buchheit, M. et al (2009) Monitoring endurance running performance using cardiac parasympathetic function. European Journal of Applied Physiology, DOI 10.1007/s00421-009-1317-x

Hellard, P., et al. (2011) Modeling the Association between HR Variability and Illness in Elite Swimmers. Medicine & Science in Sports & Exercise, 43(6): 1063-1070

Huovinen, J. et al. (2009) Relationship between heart rate variability and the serum testosterone-to-cortisol ratio during military service. European Journal of Sports Science, 9(5): 277-284

Kiviniemi, A.M., Hautala A.J., Kinnunen, H., Nissila, J., Virtanen, P., Karjalainen, J., & Tulppo, M.P. (2010) Daily exercise prescription on the basis of HR variability among men and women. Medicine & Science in Sport & Exercise, 42(7): 1355-1363.

Manzi, V. et al (2009) Dose-response relationship of autonomic nervous system responses to individualized training impulse in marathon runners. American Journal of Physiology, 296(6): 1733-40

Mourot, L. et al (2004) Decrease in heart rate variability with overtraining: assessment by the Poincare plot analysis. Clinical Physiology & Functional Imaging, 24(1):10-8.

Thayer, J. (2009) Vagal tone and the inflammatory reflex. Cleveland Clinic Journal of Medicine, 76(2): 523-526

Uusitalo, A.L.T., et al (2000) Heart rate and blood pressure variability during heavy training and overtraining in the female athlete. International Journal of Sports Medicine, 21(1): 45-53