according to the academics?
hemoglobin level?
HR variability?
something else?
waste of time measuring biometrics?
The best predictor of performance is performance itself.
Whether or not I can beat my friends.
Gauging Peak Fitness and Overtraining:
Hands down: BIOENERGETIC POWER AND AVAILABILITY OF EACH ATHLETE IS THE BEST METRIC for gauging peak fitness and overtraining!!! Measuring, tracking, and understanding energy balance in each athlete is KEY to performance optimization.
Over the past 18 years I have tested over 100,000 athlete samples (mainly Div I track athletes) via physiological profile testing (metrics including Heart Rate, velocity, bioenergetic power and availability) 4-6 x per year over the course of 4 years or more. Most academic studies published are short term, observational, and descriptive which do not yield big picture of what is truly going on with an athlete at any one point in time. I tend to stear away from the term “overtraining†as most instances of poor performance or other symptoms of “overtraining†are due to chronic under-fueling, under-recovery and improper execution of training intensity rather than too much prescribed training load. The athletes’ bioenergetic balance is simply off. Using common metrics to monitoring how an athlete is responding to training load such as; HRV, RHR, Hct, RBC, Hg, cortisol, testosterone, etc are very much latent responses to chronic inappropriate training load. When standard “stress†(HRV, RHR, Hct, RBC, Hg, cortisol, testosterone) metrics are not “normal†it is already too late, you are at least 2-3 months in a bioenergetic hole and have lost 3-4 energy systems which typically equates to a 18-32% decrease in velocity or power output across any event. BEPS testing can detect acute changes in bioenergetic availability within 7-10 days if an athletes is putting out more than they are putting in. Training load and/or nutritional adjustments can be made immediately to prevent long-term issues where the body can not return to homeostasis where latent response markers are off. Frequent, BEPS testing will give immediate insight as well as specific training parameters (HRs, velocity, volume, frequency) to athletes and/or coaches at any point in a training or competitive cycle so a positive training adaptation can be made.
As far as metrics to gauge “PEAK†fitness, that is a very dynamic and complex questions as in the real world performances many athletes can achieve the same or similar peak performances from one year to the next achieving different physiological metrics. So for instance, one year an athlete can run their best 5k by doing more aerobic training and the next year an athlete can run their best 5k by doing more speed work. BEPS testing will also give you indication on what energy system or area of physiology an athlete needs to improve at any point in time in order to make gains in performance.
http://www.systembasedtraining.com/bioenergetics-the-power-that-will-make-or-break-performances/
Walked into that one, didn’t you?
i didn’t think it worth answering, because i can’t make any sense out of what you wrote. i’m asking people what metrics they value when trying to determine peak fitness, approaching peak fitness, or evidence of overtraining. are there new metrics that people are using? your answer made no sense to me.
what you seem to say, as well as i can tell, is that you know when you’re fit if you race well. that’s great. but it’s kind of late if in retrospect you hit your peak 5 weeks earlier and you’ve spent 2 more weeks digging yourself into a hole before you began your taper.
you’re going luddite on me in the last 2 threads you participated in. you like stryd. we know that. i think you still like bicycle power meters. otherwise, it seems to me it’s train and race according to how you feel. which, if that’s what you believe, great. i just don’t think everybody is going to stipulate to that. guys were racing kona in the 8-teens and 8-aughts depending on their HR monitors 25 years ago, it seems to me they might not agree with you that they’d have been better off with no device at all.
Can you cite research that support your claims? How do you decide your identified markers are meaningful and not surrogate data?
according to the academics?
hemoglobin level?
HR variability?
something else?
waste of time measuring biometrics?
RPE and other qualitative self-assessments. There was recently a relatively large meta analysis done of this: http://bjsm.bmj.com/content/early/2015/09/09/bjsports-2015-094758
“Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review”
The title pretty much says it all.
As a useful corollary, “objective” measurement often undermines the very thing it intends to measure: https://www.rush.edu/news/sleep-trackers-can-prompt-sleep-problems
This has been my own experience with both sleep tracking and HRV. The anxiety I had over measuring both things caused me a ton of stress that more than undid any benefit I received by measuring them.
HRV in particular is, basically, bullshit. I can dig up a bunch of the papers that use way too many words to say this. But they all say it. AT BEST, these measures correlate favorably with subjective self-assessment measures. At worst, they just suck.
There’s a sign at the door of the USOC that says, “have you filled out your RPE score for the day?” That’s because that is what actually works…
Dr. Coggan nailed it with the very first reply. It’s like your oft-used comment, “they don’t give away podium spots for lowness.” The guy who wins the race is the guy who crosses the finish line first, not the guy with the lowest CdA.
Dan,
FWIW I think it’s important to define what you mean by overtraining, do you mean overreaching (which?) or overtraining?..
• Short term overreaching is not overtraining in spite of the associated insufficient metabolic recovery.
– Fatigue is typically a day to day occurrence but can be a few days to recover from
– Functional overreaching typically takes a 1-2 weeks to recover from, generally deliberate e.g. training camp
– Non-functional overreaching typically takes several weeks if not months to recover from typically NOT deliberate
– Overtraining can take many many months to recover from
• Overtraining occurs when persistent overreaching results in the hypothalamus failing to cope with the total stress present.
• Clinically overtraining is considered to present itself in two forms…
–Parasympathetic (Addisonoid)
–Sympathetic (Basedowian)
•Sympathetic, is characterised by an increased resting heart rate, delayed heart rate recovery to basal levels, decreased appetite, fatigue, weight loss, emotional susceptibility and disturbed sleep patterns.
•Parasympathetic, is characterised by early fatigue, a low resting heart rate, rapid post-exercise heart recovery to basal levels, no changes in weight or appetite, evidence of depression and hypersomnia.
Budgett, R. (1998). Fatigue and underperformance in athletes: the overtraining syndrome. British Journal of Sports Medicine, 32(2), 107–110.
Halson, S. L., & Jeukendrup, A. E. (2004). Does Overtraining Exist? Sports Medicine, 34(14), 967–981. Kuipers, H. (1998). Training and Overtraining: An Introduction. Medicine & Science in Sports & Exercise, 30(7), 1137–1139.
with respect to the two of you, i asked a question. you gave your answer. andy gave his. is it okay with you if others reply?
RPE is the way we all gauged our level of fitness. everybody. and for the last 25 or so years that i’ve really been paying attention the thing i’ve noted about two-thirds of everybody routinely overtrained once they got near the pointy end of their abilities. have you ever known anyone to race, only to find that in retrospect they were ready a month before the race? i’ve seen that happen a lot.
hence my asking the question. is it okay if i keep the thread open? just in case others might have a different view? not that their view is necessarily going to be right, nevertheless i’m interested in hearing what they may have to say.
“FWIW I think it’s important to define what you mean by overtraining, do you mean overreaching (which?) or overtraining?”
i’m not interested in transient fatigue. as i wrote to jordan’s post, what i have seen routinely in the sport is that many of the best athletes tend to get themselves ready too quickly. they don’t know until the A race is in the rear view mirror that they were ready weeks earlier than they expected. insidiously, it’s the best athletes who are the most prone to this.
i’m therefore interested in any theories are about gauging or measuring or calculating anything pursuant to this that i don’t know about.
based on the responses it seems i’ve stepped in a pile of something just by asking the question.
RPE and other qualitative self-assessments. There was recently a relatively large meta analysis done of this: http://bjsm.bmj.com/...bjsports-2015-094758
“Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review”
The title pretty much says it all.
As a useful corollary, “objective” measurement often undermines the very thing it intends to measure: https://www.rush.edu/...rompt-sleep-problems
This has been my own experience with both sleep tracking and HRV. The anxiety I had over measuring both things caused me a ton of stress that more than undid any benefit I received by measuring them.
HRV in particular is, basically, bullshit. I can dig up a bunch of the papers that use way too many words to say this. But they all say it. AT BEST, these measures correlate favorably with subjective self-assessment measures. At worst, they just suck.
There’s a sign at the door of the USOC that says, “have you filled out your RPE score for the day?” That’s because that is what actually works…
Dr. Coggan nailed it with the very first reply. It’s like your oft-used comment, “they don’t give away podium spots for lowness.” The guy who wins the race is the guy who crosses the finish line first, not the guy with the lowest CdA.
x2
I see all these qualitative measures as “road signs” on a map and the subjective measures like “contours” on the map.
I’ve used quantitative measures to analyse and predict future performance very successfully in the past but what those types of approaches don’t account for is the cognitive load / stress.
The answer, IMHO, can be multifactorial and it can be utterly singular…depends on the athlete.
i’m therefore interested in any theories are about gauging or measuring or calculating anything pursuant to this that i don’t know about.
Sort of hard to answer that, isn’t it, since we don’t know what you don’t know?
Anyway, before going any further I do think that it would be useful to distinguish between peaking prematurely (which seems to be what you’re describing), and overtraining (which in my experience is actually rather rare).
No I don’t think you have this makes things a lot clearer.
There’s plenty of tools, which am sure you are aware of, that one can use for trend analysis some simple, some complex. Some freak athletes out measuring and some athletes live a “quantified self” lifestyle quite happily. Horses for courses.
Am I aware of one over-arching singular panacea solution? … No.
Tired all the time, high HR at wake up… diarrhea
i think my interest is in peaking prematurely. or, for bonus points, not ever reaching your peak. but when i write it out it starts to smell and taste a little bit like i’m writing about overtraining, as in, digging oneself into a deep state of endemic fatigue.
in the early years of ironman nobody knew what was possible. i remember the first time anybody broke 9 hours. so then you keep going. 8:45, 8:30, 8:20 and so forth (for the men). i promise you those guys were training like sons-a-bitches and were going 8:45.
but they were going a half hour slower than they could have gone, which we know because eventually they did go that half-hour faster. and then many or most of the very same guys (and ladies), not knowing what was possible, found out the hard way what the limit of (their) human bodies were, and the only way they found that out was by training right past their peaks.
most of these folks have a pretty good idea what they need to do to get ready, it isn’t that they do too much volume or intensity in a week or a month, i suspect they just train more weeks and months than they should for a given race.
i talk to a lot of people in the course of my business who advance new ideas, metrics, devices that purport to more accurately gauge an athletes approaching (or declining) peak. hence my question for the group.
“FWIW I think it’s important to define what you mean by overtraining, do you mean overreaching (which?) or overtraining?”
i’m not interested in transient fatigue. as i wrote to jordan’s post, what i have seen routinely in the sport is that many of the best athletes tend to get themselves ready too quickly. they don’t know until the A race is in the rear view mirror that they were ready weeks earlier than they expected. insidiously, it’s the best athletes who are the most prone to this.
i’m therefore interested in any theories are about gauging or measuring or calculating anything pursuant to this that i don’t know about.
based on the responses it seems i’ve stepped in a pile of something just by asking the question.
In that case, sure, longitudinal RPE tracking. There’s a difference between simply saying, “how do I feel today on a scale of 1-10?” and tracking RPE over time. If you start assigning RPE scores to workouts, then you can start using subjective data in a very objective manner. Especially if you assign some level of predictive values to workouts. I.e., if a workout that should be a 3 is a 5, that says something. And if a workout that should be a 5 is a 3 that also says something. Especially if you start to see workouts being easier than they should be (fitness is high) or harder than the should be (fatigue is high).
So in that sense, my answer doesn’t change - still RPE. But I sense there’s a more useful answer that you were looking for. I.e., RPE tracking software.
There was a big study done on rugby players that looked at ATL:CTL ratio for injury prediction. Basically when ATL exceeds 150% of CTL, that’s a red flag. But this study used RPE - http://journals.humankinetics.com/doi/abs/10.1123/ijspp.2016-0326?journalCode=ijspp& - to determine ATL & CTL.
So that’s an advancement in terms of how RPE data is collected and used. http://journals.humankinetics.com/doi/abs/10.1123/ijspp.2016-0326?journalCode=ijspp&
So, to give you perhaps a more “useful” (?) answer to your question, any tool that allows for longitudinal RPE tracking is the “state of the art.” Tools that combine RPE with some sort of time constant to give you a value for “training load” are valuable. Paulo Sousa does this with a spreadsheet of his own creation, and I know there are other tools - such as those outlined in the Human Kinetics article above - that allow you to use RPE to calculate training load.
Coggan or Tilburs would probably have a much better grasp of what software packages exist that allow for calculation of an RPE-TL.
Hi, the core scientific principles used are applied physiology, biochemistry, ex phys which are well documented in 1000s of academic studies. Much of what I am doing in this area of physiology dates back to the early work of Alois Mader, however, over the course of 18 years of field work, I have expanded on his and similar models. By consulting 100s of coaches and testing 1000s of athletes, my evaluation methods and applications of the data as a training load monitoring tool for applying appropriate training load at any point in time to stimulate positive, measurable, and predictable responses -not only in repeat testing but also performances. We extensively compared our metrics against the commonly used metrics and found the differences that I explained in my initial post, namely being, that our metrics will give you insight immediately as well as our providing a clear individualized solution to the given physiological scenario.
Armando, is that you? 
There was a big study done on rugby players that looked at ATL:CTL ratio for injury prediction. Basically when ATL exceeds 150% of CTL, that’s a red flag.
More recently, Gabbett and colleagues have shown that - wait for it! - exponentially-weighted moving averages of training load are a better predictor of injury risk than straight averages:
At this rate, I figure that it should only take another 10 y or so to catch up to where cyclists and coaches using powermeters were a decade ago…