Is the Oura 3 worth it? A coach roundtable with Stephanie Howe PhD, Corrine Malcolm and Ryne Anderson | Koopcast Episode 102

trail and ultra runners what is going on what's happening welcome to another episode of the KoopCast as always i'm your humble host coach Jason Koop and on this episode of the podcast is all about the new aura ring three which is just about ready to hit the marketplace and if you have not had your social media feed inundated with advertisements and influencers trying to pedal this ring on you you certainly will after listening to this podcast because somehow they're going to track it back to you and your interest has been perked they're really good at that by the way because right when i started researching this ring i started getting all kinds of advertisements all over twitter and all over instagram this episode of the podcast was inspired by a number of people who reached out to me on social media and asked is this type of technology worth it can i incorporate it into my training and if i choose to do so how and so i got together with a crack team of our coaches stephanie howe corinne malcolm and ryan anderson all who have been on this podcast before to discuss this from a very practical point of view just like we would in our own coaching groups and just like we would with our own athletes that we worked with i learned a lot out of doing the

research on this and throughout the course of this conversation i hope everybody out there does as well so here we go i'm going to get right out of the way here's my conversation with stephanie howe corinne malcolm and ryan anderson all about the aura three the reason i wanted to bring y'all on to talk about this is not because any of us are sleep experts or wearable experts or technology experts or anything like that but we're all obviously coaches and i don't know about you guys but i've been flooded like the last week specifically with the question is the new aura ring worth it question mark and the worth it piece is is valuable to discuss because it's 300 bucks and now they've got a new you know revenue model for that for being able to view and uh view and have access to certain parts of your data and athletes are always kind of making this like value proposition like do i get a new pair of shoes or do i get this wearable or do i go to an altitude camp or whatever and they're and it's kind of getting thrown at i'm left right and center so anyway that's the genesis of this is i'm getting a lot of questions and i wanted us to discuss it kind of from a coaching perspective uh given the fact that there is a new device out there but we can kind of broaden it out to a lot of the other wearables so before we start out does anybody have

any effort ryan we're gonna start with you because you're in the upper left of my screen so i'm gonna go in that order does anybody have any efforts of full disclosure are you sponsored by any of these wearables have you gotten any of them for free and if you are currently like personally using any of them i think we should answer those three right off the bat no on all those accounts steph i am not sponsored by any of them and i do not personally use any of the devices corinne yeah i'm the weirdo in the room um i've used whoop um via adidas as part of their research out of the lab in portland um don't currently use it i find it's got some of its own bugs and they are also launching a new product i think too and then um i'm going to be testing out the third generation of the aura ring um for free but no their compensation in the coming months where they like are they going to lease it to you i mean they probably they probably should no um long time red bull manager um aaron lucey is has moved over to be one of their managers at aura ring and so just kind of like the friends and family discount sure okay yeah i'm not sponsored or paid by any of these i don't even accept them for free even when they ask me to um if i want to use them i any of these i'd pay for them out of my own pocket i use them and see if they're see if they're worth anything i currently am not using anything as a activity tracker other than my trusty garmin which i paid for full price and they're expensive i can't wait till the garmin 7 comes out um that's neither here nor

there so i was coming up with a way to set this up and literally at the last minute for whatever reason i came up with the simplest analogy for people to kind of properly understand this value proposition that people inevitably have when they're evaluating technology and it comes down to the power meter in the early 2000s which we've talked about as a coaching group is a lot but i think the analogy really holds true here so in the early 2000s cycling based power was widely recognized as something that was valuable for athletes to evaluate we could look at it out on the field or in a lab and we could take those numbers and make sense out of them and use them in a really practical and powerful way to improve athletic performance but at the time the limiting factor was kind of twofold is one the power meters really there's there was one of them srm they have a service center based here in colorado uh colorado springs which just started to it actually was just getting booted up when i moved out here um uh but the first the first limiting factor was they were just clunky they're big they're heavy nobody wanted to ride them in the pro peloton because they were just they were just too heavy and the second thing is they're super expensive they're probably about four or five grand at the time and this was in the early 2000s so based on inflation that's like 10 grand now or something like that they were really cost prohibitive for your normal everyday athlete to to to to kind of get a hold up but we recognized it as the and this is the important part we recognized it as the gold

standard of measuring power and we recognized that that was important so fast forward a few years and all these other players started coming out on the marketplace we want to remove these these these barriers to entry we're going to make them more affordable and lighter in in order to increase mass adoption and so you saw power tap come into the marketplace and instead of measuring power at the level of the crank arm they were measuring power at the hub it was smaller more cost effective and and then you had polar come along and they took a completely different approach for measuring power they put a little sensor on the chain stay which is the part of the bike frame that's just below the chain and they measured the speed and vibration of the chain and somehow correlated that to power and the effort of all of these things was to take this gold standard that SRM had created which is measuring power and all power is is force and velocity so we know that the torque that's being applied to the crank arms and we know the velocity of the crank arms force times the velocity is power that's you know simple physics and they're trying to they're trying to come up with different ways to measure and capture that gold standard what we're seeing with a lot of the wearables is very similar in particular regards to the sleep staging which is i think what's going to dominate a lot of our conversation where a lot of

these wearable companies are taking what is the gold standard of measuring sleep which is polysomography which is probably an order of magnitude more complicated to actually measure than power if power is measured by a strain gauge and the velocity of the crank arms sleep staging takes four or five different physiological measurements and combines them into you're going to sleep here light sleep deep sleep and you're coming awake here and so it gets more it gets more complicated because of those four different types of uh those four four different types of measurements but what the wearable companies are trying to do is akin to what power tap and polar were doing in the early 2000s is they were taking this gold standard of polysomography where the which is widely recognized as the gold standard for scoring or staging sleep and they're trying to make it more affordable than going into a sleep lab and getting your sleep measured in a poly with polysomography and they're trying to make it more accessible for everybody to do as opposed to having all these devices on you and trying to go to sleep they're trying to put it in the form factor of a ring or something that wraps around your wrist inherently when you're doing that when you're taking a gold standard and you're trying to move it over into a different kind of data acquisition method it becomes problematic and that's what what aura is trying to work through right now and i can remember when their stage two ring came out and that's what we're going to kind of start with right now it was they had their

own validation study and everybody said oh it's scientifically validated which all that means is it's had a study that has validated it it doesn't say it's been validated to be good or good for half the people or not good for anybody those are all quote-unquote validated all those answers would be validated and so when you when you dug into the actual study the synopsis of it is and i'm going to really trivialize this for the sake of time is that it was pretty good at determining the borders of sleep when you went to sleep and when you woke up and it was horrific in actually determining the different stages of sleep and what i mean by horrific it's a coin flip right you go look at the data it's a coin flip if you want to say you know you're in REM sleep for 20 minutes you could really or if the aura ring was telling you you're in REM sleep for 20 minutes you could either be in REM sleep for 40 minutes or no minutes like it literally was that like those were the those were kind of the borders of that initial of that initial study so we fast forward now to the aura ring three which is coming out on all the influencers fingers that we're seeing on instagram and one of the claims is that the sleep stage scoring is more accurate and they have another validation study to quote unquote quote unquote prove that and kudos to marco what the heck is his last name i gotta go find the study on here right now altini marco altini who is the founder of uh

heart rate what's the name of the company heart rate for athletes hrv for athletes i'm gonna put the link i'm gonna put the link in the show notes but he's been in the heart rate variability game for a for a really really long time and he's a consultant with aura so you always have to take the validation study that's produced by the manufacturer with a little bit of a grain of salt but they are taking a new approach to the problem where they're using a combination of of temperate body temperature a tagraphy which is just body which is just body movement and heart rate and heart rate variability combined with machine learning and this is kind of the new piece of it in order to stage the sleep and so they had this validation study with over a hundred uh with over a hundred subjects where they're comparing polysomography which is the gold standard to these new ways and the study actually took a few different like section or a few different flavors or a few different combinations of all these different ways and the the goal of it was to see which one of the combinations of all of these different other ways that we can approximate sleep stages is going to give us the best result and so i'm going to start to open up to you guys because you guys have read the paper and i've got my own

conclusions but i'm not going to bias the just the the discussion here so on this first question of is the aura ring worth it with specific regards to the sleep staging component which is only which is only one area of it what do you guys have to say can i just first like just one method methodological thing that i think is really interesting between the first two studies the first one was pretty small it was slightly more men than women and it was for one night in a laboratory setting the new study first quote quote-unquote validation validation study yeah yeah well quotes i think are important there um the second study was three different data sets one out of singapore one out of finland and one out of the u.s they were larger each of them each each individual data set was larger than the initial validation study and they were actually equal to slightly more females in each of those groups than there were in the initial validation study so i think and they were longer it wasn't just a one night study so i would say just like to set the stage a little bit too on this new on the new research that they've that are the new validation study is that it's a it's a higher caliber data set that they're working with than from two years ago in 2019 when they did the first validation study so i think that's important just to note um as we talk about advancements in both the technology and the research also groups across different continents yep which is a big one in the mean age

the mean age as well it went from let's see here it was pretty young in the first study yeah singapore 16.4 mean age finland 38 years old and then usa 45 so that's pretty interesting to see that it had a a wider range of ages so i think we can conclude that the validation study in quotes is better right we still come down we still we still come down to the question and that's fair and i would say that the the first validation study was weak that i don't i don't think anybody here would disagree with that nor anybody who's actually in this space would disagree with that but you got to start somewhere and that's a reasonable it's a reasonable place to start i don't mind the marketing team or i don't mind the marketing team saying that there's a validation study there people extrapolating that the validation is good or bad we can you know we can we can blame those people for uh for that type of analysis but here once again to set this up again you have this once again you have this gold standard which uses several different ways to stage and score sleep right you've got a bunch of different things hooked up to you they're measuring brain waves they're uh they're they're measuring much muscle activity they're measuring uh your ecg or your uh cardiac or different types of cardiac signals and they're putting that all into this is when you go to sleep this is when you're in deep sleep this is when you're in light sleep this is when you wake up and what those and what those cycles look like the or ring isn't capable of making all of those measurements but they're using surrogates

to approximate for all those and then comparing it to the gold standard and so i want to hear from you guys again after like reading through this whole thing is it doing a good job of scoring this sleep i mean what going back to the listener's question that i started with is it worth it with this with this particular respect and we'll get into the other areas in a little bit i promise my big like just simple answer is it's a lot better but it still has a lot of limitations and is it worth it i think there is some room for improvement before i think it's really good at detecting it says it's going to detect in terms of sleep like what are what are you going to use this data for you know um that's a good place to start if if it's worth it or not so if this is measuring deep sleep and REM cycle more we need deep sleep that's when we recover from a physical standpoint as athletes we definitely would like to know that and then REM sleep that's when we're uh the brain is resetting recovering so to speak so yeah knowing those data points would be very helpful but what what is the athlete gonna do to change that i mean i think it's pretty obvious we all know the things to do to sleep better put your phone on the other side of the room don't look at blue light don't drink alcohol close to bed do all those things but like

is having this data gonna make you more neurotic and give you more anxiety or is it gonna motivate you to do the things you know you need to do corinne's laughing your ass off so you better jump in oh no i just uh when people ask me about this it's like you know it's a habit tracker at the end of the day right it's if if you need this thing and they honestly they kind of say that at the beginning of the second paper a little bit that there's like this habit tracker component of it like it holds you know quote unquote can hold you accountable and so i think that's the biggest thing and is like do you need to spend the money for something to say for something to encourage you to get into bed at 8 30 or something to encourage you to not drink alcohol every night or to drink caffeine late in the day right like you could hold yourself accountable i've got a sticker chart in my daily planner that i use to hold myself accountable but you could also you know spend money on this um i'll agree with steph here that the data is like it's saying that it's better um particularly in two stage and i was trying to dive into that a little bit more the two stage versus four stage i feel like that's a maybe a little bit high level complication there it's getting better but it seems like there are certain areas where it still has a long way to go despite the addition of all these like different factors that it can measure like which i don't know i don't think that it's quite there yet to be this perfect measure and so i'm not sure why like what what is the necessary investment for an

athlete in that if it's not completely accurate so here's the issue that i've had that i've always had with the you're using it as a behavioral tool right we we we all want up down or sideways indicators are things getting better worse are they the same and we we do this in the physiology lab we measure people's vo2 max and their power at lactate threshold their pace at lactate threshold their pace on different intervals and things like that all is indicators of are you getting better are you getting worse if you're using something like this in terms of is my sleep getting better or worse and inherently the way that you are determining that does not have a certain level of accuracy you may you're making behavioral changes with which you don't really know either what is going on beforehand or what is going on afterwards and so this goes back to my coin flip thing initially if i have an athlete that says okay i'm starting it i'm and i'm just going to give it a one to ten score just to make it easy for everybody to understand i start out i get my ring and it's telling me that i'm sleeping at a level five and i want to improve that to a level seven or whatever i make a behavioral change i put my phone on the other side of bed at night like ryan like ryan just mentioned and all of a sudden that five went to a four you don't know whether that five went to a four because that behavior didn't work or because the the readings and the way that this that the scoring system works inherently and now with the new machine learning it's the same thing you don't know if

that's adding a degree of variability that supersedes the amount of improvement that you might get from the intervention which is which is a big thing right a lot of times the magnitude of the change from the intervention is smaller than the accuracy and the precision of the way that you're measuring that certain thing and we see that once again even in the lab if you have a two to three percent accuracy with whatever whatever measurement and you get two percent improvement you can actually show it as getting one percent worse depending upon how you're depending upon how you're measuring things and with the with the wide swath of what i'm seeing in this in this latest research paper i still even though even though they'll come to the conclusion that it's that it'll track you know sleep stages to 96 percent or whatever i still look at the wide swath as problematic because you don't like you don't know those before and after after points and the magnitude of change is just so small go ahead corinne so i think that's like the perfect the perfect little thing that i wanted to add earlier that is only the 96 accuracy that they that they're going to claim is for two-stage classification which is only delineating rem from non-rem versus forced classification the best they could get there was just under 80 it looks like which is which is different right and that's going to be light sleep deep sleep getting four stages of classification out of there so once again it's like what what data is

actually valuable there and what is the accuracy of that data yeah i mean you're kind of you're kind of faced with two you're kind of faced with two problems in my opinion right you make all the behavioral changes that ryan that ryan just mentioned and we could go over however many more there actually are there's probably 10 of them right cool room it's dark put your phone on the other side of the room you know no blue light you know keep your room uncluttered all those you know kind of all those things and you hope that those behaviors are going to result in some sort of positive in sort of some sort of positive movement if we're talking about it in sleep and it's kind of the same thing with training if you're not tracking training right you hope that all the intervals that you're doing are going to improve you but if you're not tracking that you really that you really don't know but here when you have a way of of of actually recording it and the magnitude of those changes is so small compared to the accuracy level it becomes inherently problematic because you really can't track or those behavioral changes actually making a difference and going back to the whole the neurotic aspect of it absolutely if i put the phone on the other side of my room and my sleep score got worse i'd bring the phone back to my head i mean because it's data right it's science go ahead step i i think what the consumer doesn't realize is that this is a surrogate measure and it's not always accurate and so we tend to take the scores from these devices whether it be an accelerometer or an aura ring or just even a

heart rate monitor and we assume they are 100 accurate and that is not the case and i think that's where the problem comes in because you're just looking day to day at your numbers and not realizing that there is a lot of variability and it's not always super sensitive specific and and when you use it as a like a hard rule of like this is what it is that's where you get into trouble and then if you take a step back even further you know it's like do we need i do we need something to tell us if we're getting enough sleep i mean i can tell you nights when i don't get enough sleep i can tell in the morning it's not that i need a tracker or a number to give me a score and that's over generalizing it but that's kind of like the practical application i think of of using a tracker of sort to give me more numbers whether or not they're accurate or not but a lot of people dig it i mean i had you know i i've i've probably had six of my own athletes either ask or just do this without asking go and get a wearable and then we're trying to incorporate the data you know into training in some kind of logical way and i kind of agree with you steph it's a hot like it's hard for me to honestly say okay we're going to do this or do that based on what i'm what what i'm seeing the best the best example are the whoop scores like there's no correlation between the whoop where they call a readiness score right is that right or recovery score maybe it changed that's why i'm getting confused i think it's i think

it's readiness i think that's kind of their their mo there's no i i find no correlation between if i give a hard workout to an athlete and their readiness score is 200 versus 20 there's no correlation on on that athlete's performance between those two wide swaths zero it's like zero at all they perform really good when it's 20 they perform really bad when it's 200 and then like vice versa the next week it's it's just so from a practical perspective i've always found that really frustrating well and you see that number two and you're like oh i can't obviously i can't do the workout today and you get in your head about like am i well it's i'm in the red so clearly like i shouldn't be doing this today and it's like well it's not once again it's not as steph mentioned it's not perfect right and like they try to they try to play it off as if heart rate variability is it's like hard and fast data point and it's really not you know like the best way to even if you want to use heart rate variability isn't a one-off number like it takes a lot more time and effort than that to look at like a rolling weighted average of this value and context is always going to be important and i feel like context is oftentimes lost when you're using one metric to be you know the how you steer the ship that's not how it works yeah ryan what were you going to say you're going to jump in there really quick i was going to say the to stephanie's point when she said i know when i haven't got a lot of sleep i mean yeah like mom dad like i'm trying to train i'm trying to work i'm trying to

get my kids to bed and then you're just going to get this other thing to tell you you're not getting enough sleep and add stress to yourself why would you do that to yourself you you realize all the battles and limited time you have don't get something that adds stress to the pie becomes more of a psychological issue then too and if you you think you're getting good sleep and you wake up race morning and you're in the red it's like oh crap you know like and and that's not necessarily if it's not a true score measured based off of something physiological you don't necessarily need that um to already kind of set you back when you're when you're going to the start so i'm going to present the the argument from the data scientists out there that i that i see a lot and i've had to think i think i've had to think really hard about this because i think it plays out differently in different sport groups but what they will say is is that including this type of biometric data and we're going to broaden this out from just a sleep score right to biometric data whether it's heart rate variability your body temperature or whatever to help direct training in the sense that i'm going to go easy on these days and go hard on these days either in full or in part with this biometric data what that enables you to do is to give you a better rule set to go from as opposed to the athletes who inherently want to work really hard especially at the real level from going yeah coach i can go hard again today that's what they will say they will say that this

gives you something it might not be perfect but it gives you something that you either use wholeheartedly or in isolation i guess is the best word you either use it in isolation or in addition to other variables to help come up with that training directional arrow in terms of what to do what you guys can hear my dog in the background she's gonna annoy the crap out of us for the rest of this deal what do you guys think of that let's say yeah that could potentially work because if you're an elite level athlete um especially let's let's say at the olympic level where you could potentially have a team helping you where you've got your your coach designing your workouts you've got somebody working with you from the nutrition side and now you bring in this this sleep coach so to speak um yeah if you if you could balance all that out i mean that would be awesome to have all those different experts to help you but yeah it's not applicable to the majority of the population i i slightly disagree i i see value in making sure all those areas of your life are dialed in but i'm not certain that a sleep score is going to tell me if i can train an athlete differently i think the feedback i get from the workouts and from the athlete themselves of um how i feel and all the things that are going on in their life i think are going to be a lot more indicative of their ability to train whether they need an easy

day or if they can keep pushing then just looking at a number so i i do see value but i also think we can't just use numbers to override our dialogue that we have with athletes and really just checking in and using our words and not just looking at numbers yeah i think i mean we've kind of we kind of had this conversation as a coaching group all the time of what's our most important thing in training peaks right in the platform that we're using to prescribe training from and i think nine times out of ten it's subjective post-workout comments right like it's understanding how the athlete felt about the workout and using that in conjunction with the data to decide how the workout went and what they can handle the next day or how they feel the next day so i think it's i would i think we do athletes a disservice to say that you need a number to steer your training versus just being able to listen to your body and i know that's easier said than done i myself have been an athlete when i've ignored all those signals and kept pushing because you know you're driven you're motivated and you want to succeed and so i think part of that is though that goes back to steph's point of like having that dialogue of having someone that you trust and that is part of your support system to to temper those personality quirks and and allow you to listen to your body and allow you to have honest post-workout feedback and not ignore those signals so i think that i mean there have been there have been studies done on ai coaching right and this is coming down the pipeline for all of us like there there is ai machine learning

stuff in the pipeline this is some of it um they've done studies on on you know with control groups with hrv um driven i would say workout prescription right if your hrv says this we do that versus whatnot and you know basically the hrv group had slightly fewer but not a whole lot less um intensity sessions during those and they came out about even so i don't know it's ai is coming machine learning is coming but it's going to be you know at the end of the day you're still a human being with the brain and i think we have to listen to that as well i think that when we're looking that when we're looking at this in totality you guys hit the nail on the head right you're using subjective feedback first and foremost and then you're using workout data second and then it's almost like a pick-em behind everything else that you can use and i've always thought that those first two steer the ship so strongly that the rest of everything even if it's really good provides such little steerage that it's kind of it's always like a nice to know or i don't really care you know that's that's what i've really thought is that the first two when you're looking at this proposition of something providing information to steer training i'm going to go hard on tuesday or i'm going to go easy on tuesday those some things should start with subjective feedback and then how the workouts are tracking

and then everything else like i don't even know i mean it's hard for me to even say that it matters like one or two percent because it might not matter they kind of like might might not matter at all so then then i'm left with the okay is this is a complaint is this a compliance mechanism for you know some other habit that that that we want to try to reinforce what do you think ryan so we've subjective feedback best thing for the athlete and the coach and that relationship of honest communication our data on training peaks is helpful and then if we start bringing in these other data points then maybe the athlete starts doubting their own subjective feedback and that would be a vicious cycle because then they're not able to communicate with their coach honestly it's like well well my my sleep tracker said i'm good to go but i don't feel like it i need i need to give that feedback that i actually do feel good um and that that is very problematic well in a lot of ways these devices so so you guys can remember at the uh the coaching summit that we had if you listen to just justin ross ryan you're gonna help help me i have to help me out oh no wait i wrote this quote down on my notebook hold on give me two seconds i'm gonna find it he had this really uh he had this really interesting quote that said that that and so justin ross is a sports psychologist i've had him on this podcast he was an advisor of the book and he's he's very very good at what he does he said athletes who can self-regulate better are going to make better decisions and therefore perform better

and part of that self-regulatory so first off shout out to justin what he's saying by that is is that as coaches we should be assisting them in their cape not only in their physiological capabilities but in their capabilities to self-regulate right to say okay i'm going hard or i'm going too easy and i feel that a lot of and even the power meter does this back to my original my original point when we're put when we're throwing in tools that would run counter to that goal we have to look really hard and really fast at or really hard and really deep at if we want to actually incorporate those tools with athletes and this is a good one right if you're using your readiness score your sleep score or whatever to determine am i going harder am i going easy as opposed to the athlete being honest in their communication and saying i'm cooked or i'm not that is regressive in terms of helping the athlete be or it's kind of productive to to helping the athlete be self-regulatory so i've always or i've not always but i've i've looked at the at these pieces of technology through that lens as well in terms of is this going to facilitate their own self-regulatory capabilities or is it going to actually make that problem worse i agree with you i think i think it's a regression and i think i like to think of it like nutrition where our bodies have so many systems in place to tell us

when we're hungry when we're full and we have the ability to override those systems on a on a daily basis and when we start to use external feedback to tell us when we're hungry when we think we should eat then we're really confused and we're not able to listen to our our body actually giving us those hunger cues or those fullness cues and i see this in a similar manner of we're not listening to our bodies as cliche as that sounds we're using an external number and that doesn't give us that doesn't empower athletes to to know what's going on and to be able to feel that of like yeah i'm ready to go or oh i'm actually really tired today and it takes away a piece of that just being honest and communicating so i agree that it can be a bit of a regression when we're not actually tuning inward which i think is the strongest thing we have as athletes and as coaches to talk with our athletes about how they're feeling internally so are any of you going to make go ahead ryan so to to steal something from justin ross's presentation about this okay we need to be we need to be commuting with our communicating with our coach often because they're going to give us insights that we didn't fully see they're going to they're going to be empathetic towards us and we're in turn going to be empathetic to ourselves and he had one study um he cited it's like the higher your emotional intelligence is than the greater use of your coping strategies and then the most successful athletic

performances correlate to the effective coping strategies so that was very layered but basically the more emotionally intelligent you are the better you're going to cope when it gets hard and not only the races but your training and handling the stress of life and all the all the factors that go into being um an athlete let me pose this a different way we're going to move from sleep staging onto another area of this this wearable and i told you guys this is going to take up the whole time but let's say it was perfect let's just say that we could wave our magic wand and all of a sudden have a a perfect way to collect and analyze sleep and then we could use that then it was exactly we knew exactly when the athlete went to sleep exactly when they went into REM sleep exactly how long the REM sleep was and exactly when they woke up it was it was perfect there's some something that you know somebody came up with that can measure all that and pipe it into our training peaks dashboard at 6 a.m when everybody wakes up and you can look at that number and use it for something before the athlete goes to goes out and trains would you use it and what would you use it for if it were perfect i don't think that would make me a better coach i would use it in context with some of the other numbers but also if you don't go out try even if you didn't get good sleep i don't think that's going to make or break a

workout i think there's other metrics that are more central to performance than sleep so i i don't think it would be that useful for me go ahead corinne i was gonna say so we know that sleep is obviously from like a long-term perspective very important but it's i don't know i don't think it's the king metric here like when i see these wearable sleep isn't the thing that i find most intriguing about them even and so yes from a long-term perspective being able to be like hey like you know i have to do this you know subjectively it's like an athlete says they're tired and i say okay well have you been sleeping and they say well no my two-year-old's sick and i'm like okay well now we might know why you might be tired so i don't know like sleep gives me maybe that layer but it's not you know once again that's just kind of policing an athlete's habit or like habits or letting them police their own habits to me that's not necessarily valuable information day in and day out that i need from an athlete in order to coach them ryan what do you think i'll answer from the opposite side for the sake of the conversation um yes i'd love to use it as a coach because i feel like i can plan the the harder efforts and when they're recovered of course um so okay we've got we've got this vo2 hill interval block we're starting we've got three workouts in the first week of course they're going to be a little worn down that's what we're expecting as we go on and then maybe they just drop out the floor and say okay let's let's

cut we don't need to do that anymore um but yeah it it would be really really cool if they could give us yeah 100 accurate representation of yeah the recovered let's work hard or hey let's back off the the two-year-old is sick we're not getting we're not getting that amount of sleep sleep and recovery are not the same metric like that's like that like that to me is important here sleep and recovery are not the same metric sleep is important for recovery 100 but it is not they they're not an equal like it's not cool like it's not perfectly equal there yeah and i think if you're using sleep as like a metric to determine if you're ready for hard work then it's like you're shuffling around workouts almost on a day-to-day basis at least a weekly basis and you might not have a good a good build-up you know if you're trying to work on upper end fitness and you're doing a lot of do2 max workouts they need to be in sequence like you can't be like oh we're going to do one this tuesday and then you're not recovered so we're going to push this one way back to next thursday and i think it just keeps it just instead of placing like the the lens on the big picture of the block it's like day-to-day and almost micromanaging it in a way that's not useful we so we think this is complicated for the coach well yeah so we think we think that this is complicated just as a little bit of an anecdote there's this company called omega wave who a few of you guys might be familiar with that has been trying to solve this kind of in a different way for maybe three decades now i remember seeing their first uh the first generation of their device and

maybe like 2005 or 2006 and they actually have good penetration in some of the like the interdisciplinary sports like combat sports and things like that that have you have to train a lot of different areas right you have to train power you have to train speed you have to train endurance and things like that and their whole system is aimed at giving you these stoplight systems specifically for the type of training that you are primed for for the day so if you're really primed to adapt to let's just say a power workout right it will it will take all of these biological measurements and say you know what you need to go lift fast or if you're really primed for a strength workout they'll say okay you need to go and train strength or if you're really primed for an endurance workout or really primed for rest it kind of categorize it categorizes it differently uh and and gives you guidance on the the type of physiology that you are most apt to be receptive to based on those by based on those biological inputs so it can get way more complicated but i kind of i've i've i've i've thought about this a lot if the measurement was perfect because we need we don't need perfect measurements but we need them to be pretty freaking good in order to to make sense out of them if it were perfect i might use it one out of every hundred workouts so does that make a difference maybe for one or two athletes maybe it may maybe maybe it makes a difference and what i mean by that is is if i saw a sleep score that was really horrific or really good and it lined up with two or other three two or

three other pieces of data that all were giving me the same directional arrow they were in a bad mood they had you know two previously poor workouts then i would say okay my plan was to do this since all these directional arrows are pointing the other way let's do that that would be the use case for it if we had in my opinion if we had perfect numbers as i would use it alongside other data to come up with that training direction if it were all if they were all collaborative right if they were all kind of pointing the same direction if they're all pointing in different directions which is the 99 times out of 100 you still have to use coaching instinct or kind of rely on the on the plan that you you've built you've built beforehand which should should be rooted in solid physiology from the get-go well and here's one more thought to that um because this is a factor that we experience as ultra runners like how many people sleep well a night before race or two nights before race i know i've slept terrible before some of my best races and if i had used my sleep as a kind of a i guess a metric for if i'm going to go do long runs or if i'm going to do my workouts and i just like skip it when i'm tired then i get to like race day and i'm like oh crap you know i'm tired i've never done this before and i think that's that's doing a disservice to athletes as well yeah we can go back karen probably knows the story better than i can so if you can if you want to elaborate on it do it where they've blinded olympic level athletes to their heart rate variability scores which is part of this whole mix they've

blinded the athletes to those specifically before competition and what ends up happening a lot of times because of all these you know sleep disruptions and things like that the times where their heart rate variability is the lowest which would be indicative of they couldn't they're not going to perform uh good that day or they're not they're not going to perform very well that day they've gone out and won medals you know when if you were evaluating that from a training perspective you go oh your heart rate variability sucks let's you know do an easy run today or something like that these people were like winning freaking gold jesse diggins right was the one who specifically won a gold medal when her heart rate variability was saying that she wasn't going to perform very well that day yeah they use a sunto based software called first beat that does some overnight reading stuff very scandinavian company but additionally there's kind of this i don't know in my mind kind of an og paper in hrv space that was written in 2014 um who's it by martin buchet i'm probably not saying his name right but it's called monitoring monitoring training status with heart rate measures do all roads lead to rome and it's probably my favorite heart rate variability paper out there and partially it's because it expresses the nuance of these readings i.e saying this is actually really complicated and that we assume that high heart rate variability low resting heart rate that's always a positive that's not always the case there's actually all these different factors that could create that dynamic or high heart rate variability

high resting heart rate or you know low heart rate variability high resting heart rate all these different like pairings of these metrics do not always equate to what we think they should like while athletes are tapering actually your heart rate variability can get low and just a nervous system response to this reduction in volume and that like if you're a coach or an athlete only using readiness scores and you happen to be an athlete whose heart variability drops actually during tapering you'd be panicking right thinking that you weren't going to perform but truly that's just your nervous system's natural response to that training like that change in training so i think it's really easy to fixate on these values having to say a certain thing and it's truly so much more nuanced than that that i don't know that ai will ever be clever enough to figure out that nuance without the necessary context and once again like context is key and the simple inputs that they're getting from a wrist worn monitor or a finger you know a finger worn monitor can't unless i don't know how it could take in all that context appropriately so we're kind of poo-pooing on this a lot i didn't expect this conversation to go quite on this rabbit hole what like what is like there the or ring and other wearables measure other things there's heart rate variability there's body temperature and sometimes all those things get combined into a score and stuff like that what in you guys's eyes are the are the potential use cases

if there if if there are any i'll i'll start out since i've gone last the last the last few times but i would use body temperature if i saw athletes body temperature rising over the course of a couple days and they were feeling poorly i'd be like you might be getting sick let's back off and the reason that the one of the reasons that i don't really hesitate that much in giving that counsel is because like know that they're not going to miss out on any training because you can only handle so much stress over long periods of time and if you have a few things that are telling you that you need to back off and body temperature is a pretty powerful one in my in in my opinion um you can you can just say okay we're going to take this rest phase or even a little short rest period earlier and that work that you were quote-unquote missing out on just gets replaced four weeks or six weeks down the line so i i view that as is if there were if there were one thing that i would use the most out of this four hundred dollar device and i don't know what their plan is to actually access that data ten dollars a month or something like that i honestly think it would be that i just take body temperature i take body temperature and the awake sleep duration and that was it so that's me yeah i think those are useful um i think looking at trends over time so if you have if you're wearing this device for months and maybe have like a lot of data you can see changes throughout the season um and you can learn things

about yourself i see it more of a long-term interesting end of one um project that you can you can learn more and i i always think tracking and learning more about your yourself is useful i just think you have to take it with a grain of salt and know that it's not perfect so day to day there's probably some variations like zoom out and and use that information to just see long term how you're moving throughout your your life corinne do you want to mention the period prediction part of the new aura ring there are a couple of other wearables that are trying to do it as well as well as ai that's trying to get it get at it so as soon as you said well my athletes got this increase in body temp and they're not feeling good maybe they're getting sick or maybe they're about to menstruate um or as steph mentioned in our chat as well or ovulation so um body temperature changes are part of hormonal fluctuation over the course of a woman's menstrual cycle month to month and so um using that data um with aura they're going to basically include a period tracking component of the app which will allow um women to kind of monitor that i think part of it's gonna be predictive but the idea here and steph and i have talked at length about this and in the process of writing um actually the next edition of your book was that tracking is important in part because you're learning once again individual variability about yourself as opposed to like what you know broadly we assume is the same for every

single person who menstruates which is not the case right so there's a lot of individual variability and understanding how you feel in and around different phases of your menstrual cycle it can be important valuable information for you and for your coach um that being said i'm not exact exactly sure how that will look in um the new the newest edition of the aura ring um akin to your mention about being sick so aura ring has been using body temperature tracking that finger temperature um but and then whoop has been using i'm not exactly sure how this works on a wrist worn monitor but they track they track respiratory rate with theirs and they use that as an indicator of potentially becoming sick um they've got a bunch of covid covid study data in and around that both with um vaccine getting the doses of the vaccine and with athletes who or athletes or people who got covid while wearing the devices as well so they've got some interesting data sets out there um but i think akin to stuff like i think the long-term stuff like akin to getting blood work done right when do you want to get blood work done well i'd like you to get blood work done when you feel good right you need a baseline of something to go off of if you're trying to look for detectable important changes and then understanding you know how much of a change in any of these variables is meaningful um is also i mean one complicated and two very individual and so i think having that long-term data would allow you to possibly decipher what meaningful changes are for the individual if that makes sense so both of you

i'm going to synopsize that a little bit you both of you and i i agree both of you think the power is in the long-term tracking not i'm gonna do this tomorrow or that on wednesday it's looking at patterns over long periods of time and seeing how everything influences those patterns just like training karen's giving me a thumbs up big thumbs up this is a podcast karen it's going to come out on youtube but like 10 10 10 people like watch the youtube channel so people can't see that ryan do you have anything to add to that that is an appropriate synopsis i would say keep it simple if if you've got the the time slept on your phone and the app and you see oh man i've only been getting five to six hours of sleep in the past week that's not good i'm gonna get in bed early like keep it simple you know i think coop you've mentioned that it's like yeah if it if it makes you get in bed earlier great um or you can be like karen and having your log with your stickers to track it that way i like karen's like probably they're probably a tenth of a penny each sticker compliance mechanism as opposed to a 300 tech device all right so this is a big no or maybe if you've got the 300 bucks to throw at it i think that's fair i think it's you know do you need it not necessarily i wouldn't use it blindly if you've got a coach that's the biggest issue don't don't spring it on them have this conversation with your coach if it's something that's practical for you or not

um but i think you're buying an expensive habit tracking device that's more than anything that's the biggest it's the blind following and here's the thing i get a soapbox since we're at the end of time here and i can do that because it's my podcast the the the blind following is created from the device manufacturers trying to extract as much value as possible out of the data that they're collecting and they put it into all these different you know suggestions on what they should on what people should do about their fitness and wellness and training and it's too much of a leaf of faith to go from those measurements to go run hard tomorrow without some sort of advanced or human intervention to filter through all the noise and it's the blind following of that that really kind of that that's what kind of like irks me the most the people that'll wake up and say oh well i'm supposed to run hard today or i'm supposed to work out easy or whatever because of my body temperature is you know one tenth of one degree different or i'm getting uh i'm getting a readiness score of less than 100 or whatever the the kind of baseline is that's that's the piece where i think we're not there yet and i don't know if we'll ever get there no matter how many different wearables we can kind of put on our bodies who's going to test them all who's going to wear the whoop strap the or ring the fitbit ones or the fitbit ones actually have pretty decent actually a pretty uh decent decent

accuracy when we're comparing them all not that they're all great but it's it's pretty decent who's going to wear them all and compare them so has somebody done that there's probably i don't i assumed you saw this twitter thread i will find it for you coop and send it your way but there's a great and we'll yeah we'll make coop link it in the show notes but there's a great twitter thread about this where a female um researcher did this she used aura ring she used whoop and she used something else and she compared you know and and and is and exercises actively she does crossfit and she does cardio um and so she was able to look look at like how was it picking up stress from those workouts how was it where that was it overestimating sleep you know was it you know precise versus accurate um like how consistent was were the measures and so it's actually very interesting obviously an n of one study but um i'll send it your way and it's definitely a very interesting thread that we could link in the show notes for people just to see what someone did with that information you know so going back to my power meter analogy at the very beginning of this this might have been dc rainmakers one of his first like deals that kind of put him on the launch pad he did that with power meters so he had like seven power meters on his bike and compared them all in different conditions which is really important right so okay i ride at 100 watts so i ride at 200 watts i ride at 300 watts i do this interval workout and how does it change and it was really illuminating the the the research came after that because it's harder to do but it was really illuminating for the consumers because they could see okay these surrogate measures potentially could work in these conditions

and these surrogate measures are horrible like it kind of took the edges of the bell curves and completely threw them out because of this like really simple test granted it was still on one person because but because some of them were so horrifically inaccurate to use that word again because some of them were so horrifically inaccurate the consumers filtered down the different products in a much more in a much more quick fashion than they would have otherwise super interesting all right all right that's it for today you guys appreciate the conversation as always links to everything on the show notes we will see you around next time all right folks there you have it there you go much thanks to those three coaches for coming on the podcast today and sharing some of their insight and wisdom and i know that at times it seems like we were hating on a lot of these different pieces of technology but really in actuality we're kind of at the coalface of using these with our athletes our athletes can choose to buy any devices and incorporate any type of technology that they want to in their training and at the end of the day we have to be we as coaches have to be that filter that takes all of that information and makes it actionable and something that we can actually use to help improve athletes if you appreciated this podcast as we

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