Podcast From: https://bengreenfieldfitness.com/2017/01/what-is-whoop/
[4:35] Introduction to this Episode
[6:08] Will Ahmed and Kristen Holmes-Winn
[13:35] The WHOOP Wristband
[17:20] How The WHOOP Measures
[25:10] Quick Commercial Break/Greenfield Fitness Systems Gift Box
[26:16] Four Sigmatic Green Coffee
[29:13] Continuation/Measuring Strain
[36:01] Measuring Recovery
[43:54] Working With Teams
[49:20] What The App Does With The Questions
[51:01] WHOOP’s Water Resistance
[53:25] WHOOP and Signals
[55:02] Data From People Using the WHOOP
[1:02:59] End of Podcast
Ben: Whoop, whoop-de-doo, whoop-de-doo, whoop-de-doo, de-doo, de-doo. Hey, what’s up? It’s Ben Greenfield. I’m singing the “Whoop” song ’cause this is the WHOOP podcast. Why is it the WHOOP podcast? Because in today’s podcast, I talk all about this thing called a WHOOP, a WHOOP wearable, which is this brand new device a whole bunch of you have been asking me about, and it’s actually one of the more intriguing wearables that I’ve come across lately. I like to experiment with different things that allow you to collect really intriguing information about your body, and this one’s pretty cool. So we’re going to talk about it here and discover information about body temp, and heart rate variability, and sleep, and all sorts of cool things.
In this episode of The Ben Greenfield Fitness Show:
“We need to be agile enough to be able modify programs so we can really help the athlete get the most out of the day, and I think that’s where I’ve seen this platform be extraordinarily powerful for coaches.” “WHOOP will give you an objective measurement of strength, and you will separately have your own subjective rate of perceived exertion. And so what happens is you have these two different numbers that you can look at. And so you may advance yourself, there may be times where you say a workout is a 14, and WHOOP says it’s a 14.1.”
He’s an expert in human performance and nutrition, voted America’s top personal trainer and one of the globe’s most influential people in health and fitness. His show provides you with everything you need to optimize physical and mental performance. He is Ben Greenfield. “Power, speed, mobility, balance – whatever it is for you that’s the natural movement, get out there! When you look at all the studies done… studies that have shown the greatest efficacy…” All the information you need in one place, right here, right now, on the Ben Greenfield Fitness Podcast.
Ben: Hey, folks. It’s Ben Greenfield. Welcome to the WHOOP Show, like I mentioned earlier. Whoop-de-doo. My guest on today’s show is Will Ahmed, and Will grew up playing sports, exercising, he had a lot of childhood heroes who were athletes, and he actually wound up getting recruited to Harvard and became captain of the men’s varsity squash team. He was a D1 athlete, but he was also pretty surprised about how little he knew about his body. And in today’s show, you’re going to learn exactly what he did about that, because he took a deep, deep dive into medical science, he met with a bunch of cardiologists, a bunch of exercise physiologists, and kind of figured out how you can find out more about your body, whether you’re an athlete, or just a fitness enthusiast, or an anti-aging geek, or a consummate biohacker, or just someone who’s obsessed with self-qualification.
Will also has a special guest on along with him, and I’ll let him intro that guess. But prepare to hear Will’s school story about how he figured out how to self-quantify his own physiology and his own performance, and then what he’s gone on and done since then in terms of developing a pretty cool self-qualification tool that I think you’re going to dig. So, Will, welcome to the show, man.
Will: Hey, Ben. Thanks for having me. And I’m lucky to be joined here as well by Kristen Holmes-Winn. Kristen is our VP of Performance Optimization. She works with a number of elite athletes across professional collegiate and Olympic markets, and a rock star athlete and coach in her own right. So she was an all-American field hockey player in her day, and as well a 12-time Ivy League champion at Princeton University as head coach, and also won a national championship as head coach at Princeton. So she’ll also be able to tell us a little bit about her experience with technology and how she’s been working with athletes today.
Ben: Nice. Well not only are you guys slackers, complete slackers, Ivy League athletes and beyond, but you also play two sports that you could definitely kick my butt in. Both squash and hockey are sports I have not taken a deep dive into. And if you put a tennis racquet in my hand, I might be able to give you a run for your money. But definitely not squash, a squash racquet? Is it a racquet that you use?
Will: Yep! Squash racquet.
Ben: Yeah. It’s like a badminton racquet in a way, right?
Will: It’s a game similar to racquetball in terms of look and feel, but it’s a much softer ball, more cardiovascular in terms of intensity.
Ben: Nice. Oh, and Kristen, by the way, welcome. Didn’t mean to ignore you there.
Kristen: Thank you so much, Ben. It’s an honor to be on the show.
Ben: Alright. Cool. Well for those of you who thought you might have trouble telling Will and Kristen apart, that was Kristen who just spoke. So, just clearing that up. So Will, speaking of squash, you were captain of the squash team, and you were trying to figure more about your body, right?
Will: Yeah. Being a college athlete was a pretty fascinating experience for me. And as a student athlete in general, you’re balancing so many rigors across exercise, and studying as a student, and socializing with friends, and going out, and everything else in your life, and you’re training as much as three or four hours a day. And so for me personally, I was someone who used to overtrain almost every season where you keep pushing, you keep pushing, you have these moments where you feel incredibly fit, and then all of a sudden it hits you, and you’re like run down for a week, or sometimes even longer. And that feeling of fatigue really got to me where I just wanted to better understand how could I prepare my body to perform optimally.
And furthermore, given how much time, and energy, and money goes into sports and exercise, like shouldn’t we know so much more about our bodies on a general level? And even the experience of being a captain of a team, I realized how team-based all the practices and schedules were, where you’re treating almost 10 or 20 athletes as one. And that got me thinking too, like shouldn’t this be so much more personalized, individualized as you think about a training plan. So for me, it was getting really interested in, to you point, self-qualification, physiology, cardiology. I met with a number of cardiologists and physiologists while I was at Harvard, I read something like 500 medical papers, I just did this incredible deep dive, which is for unfamiliar territory for a government concentrator in school. And…
Ben: So you weren’t studying physiology in school. You were studying government?
Will: Yeah. I was studying government and economics, and next thing you know, I’m in the science department geeking out over HRV and other so-called secrets really that your body is trying to tell you. And it was through that process that I wrote a paper around how I thought you could continuously understand the body, and I also met my now co-founder John Capodilupo, our CTO, our chief technology officer. And John was studying the hardest math classes in the country at Harvard. And as it turns out, his father is a professor of exercise physiology. So we had this like clear marriage around physiology, and he really had the technical chops to implement a lot of things on the engineering side, and I had a vision for how I thought this could help coaches and athletes. So that was about four years ago, we started the company at the Harvard Innovation Lab, your typical…
Ben: And the company is called WHOOP, right? W-H-O-O-P?
Will: WHOOP. Yes. Absolutely.
Ben: Why’d you guys call it WHOOP?
Will: Well, we wanted a name that was energetic, that made people smile. In college, people would talk about sort of their different WHOOP levels in terms of how prepared they felt for the day or for the night.
Will: And it was something that made people smile. And so, all the feedback that we’ve gotten on it to date has been terrific, and it seems to be a name that people love.
Ben: And you haven’t gotten any cease and desist orders from the whoopie cushion people?
Will: No, no. They don’t seem to know much about us yet. I think performance and the cushion market are still somewhat separate. Although we may find things about the right [0:12:41] ______ just for the environment.
Ben: You never know when the self-quantifying fart pillow might come out. So this WHOOP that you wound up developing, I mean from what I understand, you guys have like 50 engineers, and designers, and data scientists now over in Boston working on this thing. But what exactly is it? I mean in full disclosure, everybody listening in, I own one. You guys sent me one to play around with. I’ve been messing around with it for a month, syncing it to my phone, seeing how it does tracking my sleep, tracking what’s called my strain, et cetera. But I’m trying to wrap my head around what sets it apart because, as you guys know, if you were to go to like the Consumer Electronics Show, there are 8 billion devices out there that all claim to be like the next big thing when it comes to self-quantification. So what are the key defining characteristics that set the WHOOP, it’s a wristband, apart?
Will: Yeah. So WHOOP at its core is really focused on performance, it’s really focused on working with athletes, and we really want to precision you to be the most optimal version of yourself. And I think a little bit of that lens is a key differentiator on it’s own right. And then on top of that, we summarized the world in terms of strain and recovery. And recovery is probably the single most important thing that we’re bringing to market. So you can think of strain as the intensity of a workout, or the intensity of your overall day, and you can think of recovery as how prepared your body is for strain. So if you have a higher recovery, you can take on more strain, and if you have a low recovery, you may want to take on less strain.
And so if we go back to my college anecdote, in college I was probably someone who WHOOP would have told was run down, but was consistently taking on a lot of strain. And so that recovery piece, Ben, and I’m sure you’ve found this yourself when using the product, is pretty differentiated in the market. We measure heart rate variability continuously, which goes into it, we have super accurate sleep…
Ben: So you’re measuring HRV continuously throughout the day.
Will: You got it.
Ben: Okay. And that’s on the wrist?
Will: Yeah. So we’re one of the first companies to be able to accurately measure heart rate variability from the wrist, we do it continuously. And I think part of the differentiation too, from a hardware standpoint, is that we’re sampling five sensors a hundred times a second. So we’re looking at heart rate, heart rate variability, capacitive touch, which is sort of the relation of the sensor to your skin, ambient temperature, which is the temperature in your environment, and accelerometry, which is effectively movement.
Ben: Okay. Got it. So you’ve got continuous HRV measurements throughout the day that are done from the wrist, and I actually want to ask you a little bit more about that in a moment, you’ve got heart rate, what are the other things that this thing is measuring as I’m wearing it during the day?
Will: Yeah. So again, all of the sensing rolls up to strain, and recovery, and sleep. That’s how we like to summarize the world. And there’s incredible depth in which you can go through those different scores. So within strain, you’d be able to look at your maximum heart rate, or your resting heart rate, or your average heart rate, or your calories. Or if you had your phone with you, distance traveled, and time, and pace for any given activity. If you’re looking at your sleep, you’d be able to understand the quality of your sleep through hours, you’d be able to understand your REM, and slow wave, and light, and awake. I mean not all cycles are created equal, as you know well, Ben. The more slow wave and REM you’re getting, the better. So having a real granular understanding of that is critical. We look at micro-arousals over the course of the night. So are there certain things…
Ben: Micro-arousals? That sounds interesting. Is micro-arousal what I’m thinking of, or something different?
Will: Yeah. And they also go by disturbances.
Ben: Okay. Gotcha. So that’s all good and well in terms of the strain and the recovery. But what are the actual parameters, because my listeners are geeks, they like the nitty-gritty science. So what are the actual things that are being measured to tell someone their strain and what’s being measured to tell someone their recovery? Are we talking about like skin temperature, skin conductivity, accelerometer data, oxygen, or lactate? Like what is it actually measuring?
Will: A lot of the value of the technology is that it’s using a number of sensors it wants to triangulate a specific number for you. So WHOOP is really optimized PPG, which is photoplethysmography, and the sensor technology around that. So we have four…
Will: Photoplethysmography, yeah.
Will: And so we have four LEDs and one photodiode, along with the 3-axis accelerometer, the capacitive touch sensor, the ambient temperature sensor, and we look at all the sensor data alongside the activities that people are doing, and we do a lot of data collection as well alongside electrocardiograms and chest straps. So we really want to calibrate our technology as closely as possible to the gold standards in the market. And so from that standpoint, we’ve been able to create the most accurate wrist-worn device, which I’m sure you’ve seen a little bit in your testing.
Ben: So what is, I want to back up here I’m go into some of those things, some of those big words you just threw out, photoplethysmography. What is that?
Will: In simple terms, it’s light shining on your skin. So if you look at the underside of the sensor, you’ll see green light. And we’ve done all sorts of testing to look at how light reflected from the inside of your skin and correlate it with your capillaries firing actually equates to accurate heart rate. And we look at that as well, alongside of motion artifact, alongside of ambient temperature, alongside the capacitive touch…
Ben: What’s capacitive touch?
Will: It’s effectively measuring whether the sensor’s on your skin. So it gives a separate reading in terms of how well oriented it is to your body, and it adds or removes confidence associated with any statistic that we give you.
Ben: Now you also talked about a 3-axis accelerometer. What is that?
Will: So we’re measuring a range of motion that is moving on your wrist. So if you go up and down, you’re talking about X, and Y, and Z axes in terms of relation to the ground, or your body, or anything else in your environment.
Ben: Okay. Got it. So using all these different sensors, this photoplethysmography, the accelerometer, the touch sensor, and the temperature sensor what is kind of like the full list of physiological parameters that this thing is measuring? I’m just curious. I’m still not fully up to date on exactly everything that it’s measuring.
Will: So we’ll summarize this across the three pillars of strain, recovery, and sleep.
Will: So within sleep, we’ll give you your heart rate throughout the night, we’ll give you the disturbances over the course of the night, we’ll calculate automatically how much time in bed you spent, and how many hours of sleep you actually got. And then within the hours of sleep that you actually got, we’ll calculate REM, so the amount of time you spent in REM, the amount of time you spent in slow wave sleep, light, and then also the amount of time you spent awake. So that’s within the sleep pillar. It’s…
Ben: Now before you go into like strain or recovery, a lot of other devices do that. Is this thing like more accurate than other devices? Have you ever compared it against a sleep lab? Like how is that any different than what any of these other sleep tracking devices do?
Will: Yeah. So a number of products fail to be able to measure cycles. So if you look at a product like Fitbit, for example, it won’t be able to go into the sleep cycles. And part of what’s valuable about looking at sleep cycles is they happen to be the most important time to capture the heart rate variability, which other products don’t actually measure. So we look at your heart rate variability, Ben, during the last five minutes of your slow wave sleep, and then we baseline that to you. So slow wave sleep and REM sleep, the transition between those two periods is when your body’s restoring. So you have to be able to measure those things to really understand restoration. And then you have to be able to measure heart rate variability to really understand recovery. And so that’s where we’re able actually to get at are you recovered.
So much of the data that we collect is really getting to sort of these key questions of, “are you prepared to work out”, “is your body run down”. And as you can see, it takes a number of layers of technology to get there. So it’s not just that we’re measuring sleep, it’s not just that we’re measuring, Ben, slow wave sleep within cycles. It’s that we’re actually able then to look at the last five minutes of slow wave sleep, and measure heart rate variability, and then compare it to 3-day, and 7-day, and 30-day moving averages to really understand for you how recovered your body is at this moment.
Ben: Got it. And how accurate is it compared to just like going into a sleep lab?
Will: Yeah. So if you look at…
Ben: And by the way, sorry to interrupt, but one of the reasons I asked that is I’ve heard like the Fitbit, the Jawbone, a lot of these devices, we’re talking about like 60 to 70% accuracy, which is not that high.
Will: Yeah. So we’ve seen over 90% sleep-wake agreement, and that’s calibrated against the PSG machines, which is the highest regard for sleep lab accuracy. So I think it’s the most accurate wrist-worn sleep analysis that you’ll be able to find. And although we don’t sort of take credit for being able to measure sleep apnea, we’ve actually seen people who have had such questionable sleep results on our platform that they’ve gone and gotten tested, and it turned out they had sleep apnea. So there’s some cases where you’ll actually notice something about your sleeping behavior that may take additional follow-up steps. It’s amazing, we’ve worked with professional athletes, Ben, who are like half a step away from being the next star in a league, and they spend nine hours in bed and they get three hours of sleep. I mean it’s like they’re playing drunk, right?
Ben: I’d get up and watch TV.
Ben: No. I actually wouldn’t get up and watch TV. I’d probably read a book or wander around and eat something. But, yeah. That’s…
Will: In a lot of cases, they don’t even know it. They don’t realize how poor their sleep efficiency is. So I think from an accuracy standpoint, what makes WHOOP different is that, look, it can tell you these things in pure transparency.
Ben: I think it’s really interesting, the part about sleep apnea. Does it actually measure oximetry, like your actual blood oxygenation during the night? Because in the past, I recommended to folks to get like one of those constant pulse oximeters that you put on your fingertip that will monitor your oxygen levels throughout the night so you could see if you’re dropping low in oxygen throughout the night. Does the WHOOP measure oximetry at all?
Will: We currently don’t report on it, although there’s a number of things that are in our, I’d say research pipeline, and that’s one of them.
Ben: Okay. Got it. So which of those things you talked about, like the photoplethysmography, or the centers, would those be able to, at some point in the future, measure oximetry? Or do you have to like build a different sensor into the device?
Will: There’s a number of optimizations that you can make from using photoplethysmography. And today, actually one of the main ways that pulse oximeters work is through photoplethysmography. So it’s similar technology, and a lot of it comes down to really smart data analytics and signal processing. Unfortunately, that makes up most of our team.
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Ben: Kristen, what goes into measuring strain? So we talked about sleep, what about strain?
Kristen: Yeah. Strain is a measure of cardiovascular exertion, and we kind of used a Borg scale loosely kind of plot you on a kind of 0 to 21 scale.
Will: So you can think of the Borg scale, Ben, it’s the best way to rate perceived exertion.
Ben: Yeah. It’s not a 1 to 10 scale. It’s like 6 to 20, right?
Kristen: Yeah. I think that, like it’s not linear. I think that’s a lot of people view in those terms, but it builds like ever time.
Will: Right. So…
Ben: When you say it’s not linear, what do you mean?
Will: So if you work out for an hour at the same rate and you get a 10, and then you work out for another hour at the same exact rate, you won’t end up with a 20. That would be linear. It’s an exponential curve in that your strain over time, it gets harder and harder to move up on the scale. And the way the score was created, Ben, is by actually looking at individuals baselines. So we took a number of athletes across all sorts of different sports, and now at this point, we’ve done thousands of athletes. And when we looked at their baseline information, so their resting heart rate, their maximum heart rate, their heart rate variability, their anaerobic threshold. And we had them wear chest straps, and we had them work out, and then tell us what their thought their rate of perceived exertion was for a workout.
Will: And this was all in the Harvard Innovation Lab. And so we what saw is you spent X amount of time in these different ranges of your maximum heart rate zone, and you called the workout a 12, or you called the workout a 16. And Borg actually spent a long time determining that if you called a workout a light workout, versus a moderate, versus a maximal workout, all of those things actually can correlate closer to the number. So he did the research on the psychology, so to speak, of what you would actually call a workout, and then we extrapolated it on this. I time it, actually, to physiological information.
So the benefit today is that when you work out, WHOOP will give you an objective measurement of strain, and you will separately have your own subjective rate of perceived exertion. And so what happens is you have these two different numbers that you can look at, and so you make a balance of yourself. There may be times where you say a workout is a 14 and WHOOP says it’s a 14.1, and in lockstep. And there may be other times where you say a workout is a 12, and WHOOP says it’s a 16. And that may be a sign actually you were peaking physically. Actually, the workout felt a lot easier than the objective strain that you put on your body.
Will: The opposite’s true too, where if WHOOP said a workout was a 12 or a 13, and you said it was a 16 or a 17, which would be high strain, then it’s a sign maybe your body was run down, or you were doing a workout that you were less efficient at.
Ben: Why wouldn’t you just look at heart rate variability to determine that? Like look at HRV, see the HRV is low and say, “Oh, hey. You’re beat up,” versus like going through all this RPE and heart rate measurement?
Will: Well, so we look at your HRV in the morning once you’re up, right? So we’ll take your heart rate variability before you do any of these workouts…
Ben: And it’s automatically measuring HRV for those five minutes before I wake up?
Will: Yeah. And that’s a lot of the differentiation…
Ben: That’s kind of cool.
Will: There’s no chest straps, there’s no wake up, press an app, breathe for five minutes. It’s completely automated. And by being automated, as you know, Ben, it gets a lot more accurate ’cause you’re comparing it to your baseline.
Ben: Mhmm. Interesting. Okay. So you’ve got the exercise strain, but then what about just the strain? ‘Cause you’ve got this other measurement that I notice it’s telling me, which is the strain for my whole day. What’s that made up of?
Will: Exactly. So that’s looking at over the course of the day, what kind of strain are you putting on your body relative to all the other workouts that you’re doing. So WHOOP just looks at overall time from the minute you wake up to the end of the day, what sorts of exertion levels are you putting on your body.
Ben: Using heart rate, or heart rate variability, or both?
Will: It’s looking at all of our sensors, again. Now the main readout in that case is heart rate, but everything that we do, mind you, is triangulation of five different sensors. So heart rate is something that plays a key role in our strain measurement. And what will it say is, “Okay, we’ll look at maybe stress that’s accumulating throughout the day.” Maybe various activities, maybe working out, obviously. Exercise. I mean that’s a main driver of strain. What’s interesting too is that you have athletes who have a low recovery and they know that they need to rest, and so they wouldn’t think in the past that rest meant like, “Oh, I can go out to see my buddies in a bar,” “Or I can play ping pong for an hour and a half,” and they don’t actually realize that they’re accumulating strain by doing these things to their body. And so the day strain metric actually helps you really to optimize for days when your body’s with a lower recovery and you want to give it the ability to rest.
Ben: Okay. Got it.
Will: So we have athletes who set targets for work out strain that may be high, and we also have athletes who set day strain targets that are low because they want to make sure their body’s recovered.
Ben: Is there a way for the WHOOP to like, when I open up the app, let’s say at the beginning of the day, can it just tell me, “Hey, you should make this an easy day,” or “This could be a hard day”?
Will: Yeah. A lot of that feedback is being built into the consumer product. So the aspirational athlete who’s listening to this, if you’re someone who likes to train regularly and wants to compete in events, or you’re an up and coming high school athlete, or you’re an endurance competitor maybe, or you’re someone who works at a gym regularly, or one of these different fitness cults, I think this is a product that can help guide your big workouts, and also can tell you, “Hey, you don’t need to go today. You’re better off resting today than actually exercising.” I mean it’s funny, WHOOP is the first fitness product to tell you not to exercise.
Ben: Yeah. That’s really interesting. Or at least to take it easy, right? To do yoga, or a sauna, or something like that. Now what about recovery? Because we talked about the sleep measurements, the strain measurements, but what goes into the recovery measurements?
Will: So with recovery, we’re looking at…
Ben: And by the way, sorry to interrupt, but I feel like we’re ignoring Kristen. So Kristen, if you want to jump in, just a feel free to, I suppose, shut your boss up and talk if you feel like it.
Will: Well, I want to turn this over to…
Kristen: He’s on a roll.
Ben: He is on a roll.
Will: I want to turn this over to Kristen to talk about how she works with athletes around recovery ’cause I think it’s so important and so interesting. I just want to quickly say the way we capture recovery is by looking at heart rate variability, and by the way, that’s the statistic that we’re measuring during slow wave sleep. It’s this lens into your autonomic nervous system. For the first time, it’s going to be calculate automatically for you. And then we look at 3-day averages, 7-day averages, and 30-day moving averages. So the longer you’re on WHOOP, the smarter it’s getting in terms of understanding who you are. And we also look at your resting heart rate and how much sleep you’re getting relative to the sleep that you need. So again, it’s looking at number of sensors, and then number of sensors rolled up into a number of statistics, and then it’s weighting different statistic over time to try to give you one number that explains what you need to do, which is to score 0 to 100%, red, yellow, green, how ready am I to go.
Ben: Wait. When you said the amount of sleep, you said it’ll track your recovery, or make recovery recommendations of the amount of sleep needed versus the amount of sleep you got. And this is something I noticed, I didn’t quite understand. Like it would tell me, “Hey, you should go to bed at this time,” “You should get up at this time,” “This is how much sleep you need this night.” How is it figuring out how to tell me how much sleep I need each night?
Will: So that’s one of the, I mean one of the ways that we designed the product was to try to have it with a step ahead of the app. So you wake up in the morning, you’ve got a recovery, that recovery is telling you how much strain potentially to take on your body, over the course of the day you accumulate strain, then actually at the end of the day, we look at the strain that’s accumulated on your body, and we say based on who you are, based on how much you’ve been working out, based on the sleep debt that’s accumulated, this is how much sleep you need for tonight to recover for tomorrow.
Ben: Yeah. I’ve actually never seen a device do that, like tell me how much sleep I need based on where I’m at.
Will: Yeah. And Kristen, I mean, have you seen that, where by telling out athletes how much sleep they need, there’s actually some kind of a mindset shift that may take place?
Kristen: Yeah. I think our athletes don’t know how little sleep their actually getting. And I think that’s what’s been illuminating for many of the NCAA athletes we work with and professional athletes, it’s just this realization that, “Wow. I am not giving my body enough time to restore and regenerate in a way that’s going to allow me to optimize my performance the next day.” So we’ve seen a huge behavioral shift in all of the athletes that we work with around sleep in particular. And because this is such a huge input to our recovery score, we’ve seen athlete’s ability to recover and improve, and I think that’s what’s been really impressive about the platform is really the behavior modifications that just exposure to this data has enabled our athletes to make.
Ben: Will it take into account whether or not I’ve napped in terms of calculating like how much sleep I need that night?
Will: Yeah. So WHOOP will autodetect naps as well, if they’re over 30 minutes in terms of actual sleep.
Ben: How does it know if I’m napping versus like sitting on an airplane?
Will: Well, again, this is the brilliance of triangulating across a number of different sensors. So for example, the difference between lying on a couch with a low resting heart rate and no movement and sleeping in a bed with a low resting heart rate and no movement is that in the course of falling asleep, your core temperature drops and you emit heat. So by being able to monitor things about heat and by being able to look at heart rate variability, all of a sudden you have an immediate understanding, “Wow. This person just fell asleep.” We wouldn’t be able to do that with any one sensor, but if I’m measuring five sensors, you start to really understand the body.
Kristen: And you have to actually be asleep for 24 minutes in order for it to get recorded. I think that’s…
Ben: Gotcha. One thing that I thought was kind of funky was like sometimes it would tell me like, “Go to bed at 11 PM and get up at 7 PM,” and that kind of flew in the face of what I know about circadian biology, like you’re, ideally, by 2 AM, you should have been asleep for about four hours to allow your body temperature to come down, to allow for adequate leptin and melatonin release, et cetera. How do you determine the reference of how much an athlete should adhere to normal circadian biology that we know humans are like ancestrally hardwired to be in versus what the device is telling you? ‘Cause I thought that was weird a few times, when it would tell me to like go to bed at like 11 PM.
Will: Yeah. So we generally defer to circadian rhythm and the mindset around it, and there’s a long history of medical literature to go with it. A lot of this, Ben, is also just optimizing for you. So in the interface, you can actually change when you want to wake up. So if you’re telling us that you could wake up at 8 or 9, then as a result, we can tell you that you can go to bed a little bit later. But for a lot of people, going to bed early is a challenge, even though it may be optimal for their sleep performance. So a little bit of the sleep coach is dedicated to actually allowing individuals to optimize what works within their schedule. You might be on a plane, or you might have to get up early for certain meetings, and we want to make sure that you’re also getting the appropriate hours of sleep.
Will: So what you’ll notice is that you can actually change. Do you want to peak tomorrow, perform tomorrow, or get by? And that will actually just how much time we say you need to spend in bed.
Ben: Yeah. I saw that. That was really interesting. So if you know you’re going to be like at a conference all day the next day, just like sitting around, versus you have a game, or a practice, or a hard workout, it will adjust the amount of recommended sleep.
Will: Yeah. One thing that I’ve noticed with athletes, and Kristen, you may have seen this too, is like they think of sleep in such binary terms where it’s like, “Okay, tonight I’m going to get a ton of sleep ’cause I’ve got this game tomorrow.” But it actually doesn’t matter that yesterday I got like two hours of sleep and was pulling an all-nighter for a paper. So a lot of that sleep coach is designed to get people to get just enough sleep as much as it is to get them the sleep to optimally perform. And we’ve gotten a lot of good feedback, I think around how you can sort of navigate that based on your own lifestyle.
Ben: Gotcha. Now…
Kristen: I think it helps reduce the binge sleeping mentality, where you think you can kind of make up for lost biological sleep, which we know is not possible. So I think it does like prevent, because we monitor debt accumulate, sleep debt accumulating, we can see that accumulation happening, or the user can see that accumulation happening. It kind of gets them, or helps them maybe just change their, modifies their choices, I guess instead of maybe just sleeping for two and saying, “Okay. Tomorrow, I’m going to sleep for 12 to make up for it.” They’re like, “Okay, I’m going to sleep six tonight and maybe seven tomorrow, or six tomorrow.” I think we’ve seen modifications that area too, which I think are helpful.
Ben: Now one big thing I notice that you guys are doing is you’re working with like teams, you’re working with athletes, like a big, a lot of devices, they’re catering to the fitness enthusiasts, or the self-quantifying nerd, but it looks like you guys are doing a lot with like, I noticed Will recently had an interview with Major League Baseball where you guys worked with a bunch of baseball players. What is it that you do in terms of uniqueness when it comes to athletes or teams and the ability of a coach to look at data of a group of athletes, for example?
Will: Yeah. So I think first of all, just again, the basic analytics of strain, recovery, and sleep really speaks well to the coach and the trainer. So that mindset, I think, is the right framework for an athlete. We don’t measure steps, we measure strain. We really look at your body’s recovery. So that speaks to athletes. Separately, we built a team dashboard that allows for, actually like 27 different layers of privacy in terms of what can be shared between an athlete and a coach.
And that’s a really important detail here as you think about super personal information that can affect performance is how do you create an environment that makes coaches and athletes both feel comfortable using a product? We spent a lot of time working close with athletes to make sure that we do create something where they’d be comfortable wearing it all the time, and both parties, both the coach and the athlete would see value in it. And Kristen, I mean maybe talk a little bit about just how do you see coaches react to, sort of, for the first time being able to see like, “Oh, man. Here are all my athletes and how recovered they are. ‘Cause I think that’s so much of the value of the team dashboard.
Kristen: Definitely. I think everyone has different challenges of, I think there’s lots of different ways to kind of measure HRV and timing wise, but I think being able to wake up as a coach and have an understanding of how well recovered or not recovered every single one of your athletes is, it just helps you plan so much better, and we’ve certainly seen that with the coaches who are using this system, I mean using the data to kind of modify training plans. But I think it’s just the mindset around that you can’t just train everyone the same way anymore, and I think coaches who are doing that are really missing an opportunity to optimize the individual attention of each athlete.
Every athlete is going to experience training in a different way and are going to have different lifestyle choices, therefore are going to recover differently. And we need to be agile enough to be able to modify programs so we can really help the athlete get the most out of the day. And I think that’s where I’ve seen this platform be extraordinarily powerful for coaches is it’s just being able to customize, when you’ve got a team of 24 athletes, for example, being able to customize training so you can help the athlete capitalize on recovery, or pull them back if they are ready to take on a lot of strain.
Ben: So if I’m like, let’s say I’m a coach and I’ve got like 20 basketball players and they’re all wearing the WHOOP during scrimmage, and during sleep, et cetera, how do I actually go in and look at each of those athletes’ scores? Is there like an online dashboard that I can log into as a trainer or a coach to just automatically get a glimpse of each member of the team?
Kristen: Yeah. There’s a dashboard that kind of displays really anything that you want to see around the metrics that we talked about for each individual athlete, or you can see everyone at the same time. So it really does give you an awesome picture, and it’s color-coded, so it’s really clear. You’ve got green, yellow, red, and then you can kind of dive in and look at a little bit more detail around the different metrics. If someone, for example, is in the red, what’s going on? And is this an isolation or is this trending? You can kind of certainly make better decisions or have a lot more insight in order to make better decisions for the athlete for the day. ‘Cause I think the numbers in the isolation, on a one off, aren’t necessarily actionable. But we see the bigger picture, that’s I think where the insight becomes really valuable.
Ben: Okay. So I can see like my point guard is at a green for the day, but my center is at a red or a yellow?
Will: Exactly. And so instead of necessarily having both the center and the point guard doing the same exact workout today, maybe you scale it back for the center, or you think about recovery modalities.
Ben: Yeah. Or the center is going to get nine hours of sleep versus the point guard who would be prescribed seven by the built-in sleep coach.
Will: Yeah. There you go.
Ben: Okay. Got it. Now in terms of how that works out for like a coach or a trainer, I’ve been using it as an individual, but is there some kind of like a subscription-based service that you sign up for? Would a coach like pay for something like this and then all their athletes buy a device? Do you guys just like have like team packages that you ship out to a personal trainer, to a gym, or a coach? Like how does that work?
Will: Yeah. So that’s a lot of the work that we’ve been doing to date, Ben. I mean we started working with professional teams, collegiate teams, and like you saw recently with Major League Baseball, we just conducted the largest performance study actually ever conducted by a pro sports league with them. So that’s the platform that we’re describing where you have coaches looking at 20 to 30 of their athletes every day. And what’s amazing is actually just how much time they’re spending on the platforms, so on average up to 30 minutes per day looking at the WHOOP dashboard to understand their players data. And so I think what you’re seeing is this like mindset shift around how to treat athletes, how to train athletes, and it’s going to be a lot more physiological and a lot more data-driven, going forwards.
Ben: Why is it when I open up the app and I go into my day that it asks me questions. Like it’ll ask me when I open up my sleep like whether I shared my bed, or if I had sex, or if I looked at my screen before bed. What’s the app actually doing with all this data that I’m feeding into it each time that I use it?
Will: Yeah. So all that information we keep private to the user, and we do ask questions after you wake up in the morning, after you receive a recovery, and then also after you workout. And that information can actually be used for you later on to understand how certain things in your life affect performance. So for example, we have some athletes that actually sleep a lot more effectively after having sex, and we have some athletes who don’t, it’s the opposite. Or we’ve got athletes who, across the board, don’t sleep as well or recover as well when they consume alcohol. But we can actually show an individual after they’ve recorded this information into the app, “Hey, in simple terms, when you’ve had alcohol versus not, this is how well you sleep and this is what your recovery is.” And on a broader scale, Ben, this is an opportunity to actually look at how all sorts of inputs affect your life. ‘Cause WHOOP is always baselining you. We’re looking at 30-day periods, 3-day periods. It’s always baselining. And so you could look at, “Okay, here’s Ben normally. And here’s Ben now after 30 days of meditation,” or a new diet, now I foam roll twice a day, or cryotherapy. Fill in the blank. And let’s look at, “Hey, did this new thing that I introduced to my body help me perform at a higher level?”
Ben: Gotcha. Interesting. Okay. So a few kind of like practical questions about the use of the WHOOP. First of all, swimming. How does it do in terms of water resistance, in terms of like taking deep dives, things like that? Like what’s the water resistance like?
Kristen: We actually, we work with swimmers and we work with swim teams. We’re real fortunate to have on staff a three-time Olympian who’s a former captain of the Beijing team in 2008 swimmer. So he’s captured a lot of that market. But really what’s great about WHOOP is that it is waterproof, and it’s one of the only devices that actually is waterproof and collects the metrics that we collect. So, yeah. We do very well in the swimming market, and I think it’s proven to be very accurate in the water, collects just loads of really clean, wonderful data. So it works well, and I know that we can go deeper now. Not exactly sure how deep we can go in water…
Will: Yeah. Up to 30 feet.
Kristen: 30 feet?
Ben: Okay. Got it.
Will: And that’s all we’ve tested up to, but we’ve also seen results where it’s even deeper.
Ben: How long does it hold? Oh, go ahead.
Will: We have a very flexible warranty policy as well. Like if someone’s unit were to, for whatever reason, if they’re scuba diving or something, we haven’t had that happen yet, but if it did happen, we’d swap a band out, no problem.
Ben: Okay. How about the battery charge? How long does the battery last?
Will: Yeah. So the Gen 2, our battery life is 44 hours, and what we invented as well is a modular charger. So you can slide on a battery pack onto the sensor while you’re actually wearing the sensor to charge it. So you never need to take WHOOP off your body, and therefore you truly get 24/7 continuous data.
Ben: But you can’t get that battery pack wet?
Will: Yeah. The battery pack’s the piece that you shouldn’t get wet.
Ben: Okay. Yeah. I saw that on the instructions when I was using it. ‘Cause I’ve done that multiple times, charge up the battery pack, slipped it on, and then gone out and done my things while the WHOOP is charging on my wrist.
Will: Yeah. And look, we don’t recommend getting it wet, but again, we tried to build these things to perform as well as they can in obviously high intensity environments.
Ben: We have a lot of listeners who are concerned about the overall effects of things like WiFi radiation constantly transmitted from an Apple watch, or like Bluetooth from a headset up next your head. What do you guys do in terms of the ability for the WHOOP to be able to collect data without like constantly transmitting a signal? Is there anything like that built in?
Will: Yeah. So what we’ve done is we built a hardware system that’s really intelligent about its relationship with a mobile device. So if it’s in range of your mobile device, it’ll send data to it. And if it’s not, it won’t. And so you don’t have to worry about things like WiFi concerns or anything like that ’cause we’re not connecting to WiFi.
Ben: Okay. So just to clarify, like if I put my phone in airplane mode and then I sleep with the WHOOP on my wrist, it’s not constantly searching for my phone?
Will: Yeah. So it stays connected when your phone is on and Bluetooth connection is made. In your settings, if it says connected, it sends data. If it’s not connected, then it won’t be sending data.
Ben: Okay. Got it. ‘Cause I asked the folks at like Fitbit, and Jawbone, and stuff about this, and they told me that you know no matter what, like the devices transmit like every one to three seconds.
Will: Yeah. So we store data for up to three days, and I think the storage capability has allowed us to optimize with that relationship.
Ben: Gotcha. So it just stores the data in the WHOOP, and then when I finally sync up to the phone, it’ll download all the data?
Will: You got it.
Ben: Okay. Cool. What kind of, I don’t know if you guys are allowed to say this, but like I mentioned, Will, I notice you tested the WHOOP out on a bunch of MLB baseball players, are there a number of professional athletes or teams using this thing? Like what have you found in terms of just like hard data out on the streets from folks who are using this?
Will: Yeah. I mean one of the most fascinating things I think is just looking at the correlation between WHOOP recovery and actual in-game performance. And we’ve seen this at the professional level and the collegiate level. So with Major League Baseball, we had 230 athletes wearing WHOOP every day, and we actually got to look at their pitching velocity and their exit bat velocity relative to their recovery. And I mean this is the first study of its kind, and what we saw is a really strong correlation between how recovered athletes were and how well they performed.
So if you had a higher recovery, you were pitching faster fastballs relative to your average. And if you had a higher recovery, you were able to have a better exit bat velocity relative to your average. Now we’ve even seen this in other sports as well. So we’ve got a point guard in the NBA who, when he has a high recovery, he’s scoring 22 points per night, averaging one turnover, and shooting 52% field goal percentage. When he’s got a low recovery, he’s scoring 18 points per night, he’s got eight turnovers, and he’s averaging 35% field goal percentage. I mean those are like literally two different athletes. The higher…
Ben: Are you allowed to say who that is?
Will: In this case, I can’t say. But he was former all-star and a loyal WHOOP user. So it’s fascinating just to look at this data alongside performance. And then we’ve also published white papers on studies that we’ve done with college athletes, Ben. So you can find this at whoop.com if you just go to the validation section, and there’s science section as well. We like to write white papers, we like to publish stuff, we invite curiosity and critique as well. So we’ve written a couple papers on how sleep and recovery have correlated with cross-country performance, so more sleep, higher recovery leading to faster time trials within cross-country. We’ve seen the same correlation with recovery and time trials within swimming. We’ve seen the same thing with NCAA basketball and free throw percentage. And mind you, we’re just getting started. So I think this is what gets us so excited, and that’s why Kristen and I go to work everyday.
Ben: Yeah. It’s pretty cool. I mean I noticed you guys of have been covered by like ESPN, and Digital Trends, and Sports Illustrated, and the MLB Network. So you’re know obviously getting some traction. USA Today did a story on you guys too, right?
Will: Yeah. We were in USA Today this week. It was focused on the MLB performance study. And I think for your listeners, if they are interested in like how can you use this data to beyond just understanding your body on a daily basis, how can use it to optimize your body, you’ll see a lot within our publications relative to the studies. So we’ve posted things about findings from the MLB study on our blog called The Locker. So if you go to thelocker.whoop.com, you can actually read about how MLB players were traveling, how travelling actually affected the home team versus the away team, dramatically less sleep, lower recoveries, you can look at some of the things that I just described around correlations with performance, you can look at actually correlations with injury.
I mean we haven’t talked much about injury here, Ben, but how important is it to not get injured. We’ve got someone on our team who jokes “the best ability is availability”. And I think there’s some truth to that. We’ve seen a lot of focus at the professional level on injuries. So that’s another thing that we saw an interesting correlation with. And I think just as we collect more and more data, and get to work closer with athletes, we’ll learn so much more. And that’s why we’re excited as well to have a product now that’s publicly available for other athletes who want to work closely with us.
Ben: Yeah. It’s pretty cool. And I know LeBron James has been using it, Michael Phelps has been using it. So you’ve got some pretty big athletes using this thing, which is quite cool for you guys, and for them I suppose. So this thing collects more than 150 megabytes of data every day. Tracks heart rate, heart rate variability, skin conductivity, ambient temperature, accelerometry and motion. It’s actually a pretty cool device. And like I mentioned to those of you listening in, I’ve been experimenting with it, and hopefully I’ll be able to get some screen shots out to you guys along with this post to kind of show you some of things that I’ve been learning as I use it.
Now a couple things I want to make sure folks know. First of all, if you go to WHOOP’s website, whoop.com, there’s a $50 code you can use at checkout if you just want to buy one and mess around with it. The code is just Greenfield. That’ll give you $50 off at whoop.com. Or if you wanted to go to the show notes for today’s show, you can just go to bengreenfieldfitness.com/WHOOP. That’s W-H-O-O-P. And again, the discount to get 50 bucks off is Greenfield. How much does it actually cost you guys?
Ben: Okay. So 500, and then 450 if folks use that code.
Ben: Okay. Cool. Awesome. And obviously a little bit more expensive than like a Fitbit or a Jawbone, but you’ve got the built-in computer, you have all this data it’s collecting, there’s a lot of stuff this thing does that goes above and beyond some of these slightly less advanced devices, which is what I like. As an athlete, I like to be able to track every single parameter that’s going on inside my body. So it’s cool stuff. So nice job, you guys.
Will: Hey, thank you, Ben. And I would just say, look this is a product, this probably isn’t a product for everyone. It’s a product for people who really want to perform at a higher level.
Will: If you’re a competitor inside, if you work out regularly, if you’re doing events, you will see enormous benefit from this product and we’d be lucky to work with you.
Ben: Yeah. And that’s the thing, like folks who are just wanting to like lose a few pounds, you’re probably good with like just a basic calorie tracking, or basic wearable like a Fitbit or a Jawbone. But if you want to kind of take things to the next level, or if you’re a trainer or a coach, this seems like a pretty cool solution for you or your team.
So, anyways though, bengreenfieldfitness.com/WHOOP, or you can use code Greenfield, just go to whoop.com if you want to just go grab one. So, Will, and by the way, Kristen, I’m a little bit upset that you talk so much and took over the conversation from Will, but thank you both for coming on the show today and sharing all this stuff with us.
Kristen: Thanks for having us.
Will: Yeah. Thanks for having us, Ben. Pleasure.
My guest on today’s show – Will Ahmed – grew up loving sports and exercise. Many of his childhood heroes were athletes. He was recruited to Harvard and became Captain of the Men’s Varsity Squash Team. As a D1 athlete, he was amazed by how little he knew about his body. He would train for 3 or more hours a day with his teammates without knowing what gains he made. He was surrounded by athletes, himself included, who overtrained, misinterpreted fitness peaks, underestimated recovery and sleep, and got injured. Being prepared for game day often seemed…random.
So he became inspired by a simple idea: Humans, especially athletes, could optimize their daily performance. Optimizing performance was not a random sequence of events and decisions, but rather a systematic approach to understanding your body.
At Harvard, he met with cardiologists and physiologists. He read over 300 medical papers because he became obsessed with understanding the human body. What he learned was amazing: There are secrets that your body – your physiology – is trying to tell you. These secrets can help prevent overtraining and injury, they can detect fatigue and even sickness, and, sure enough, they can be used to optimize human performance. But few actually monitor those metrics.
He partnered with his co-founder John Capodilupo, who was studying math and statistics at Harvard before dropping out to found a self-quantification company called “WHOOP”, and also partnered with Aurelian Nicolae, a graduate from Harvard with a gift for mechanical prototyping and engineering. They then spent the past 4 years building a technology called “the WHOOP System”. They assembled a scientific and performance advisory board and now work alongside our team of 50 engineers, designers, and data scientists in a downtown Boston office overlooking Fenway Park.
They’ve been fortunate to work with many of the best athletes in the world. What they’ve discovered has amazed Will, and we talk about it all on today’s show. Self quantification can transform your life and induce effects like positive behavior change, fitness improvements, injury reduction.
Will believes that the data he’s collecting on athletes is unprecedented, both in its sophistication and scale, and that no physiological studies have ever occurred on this magnitude. WHOOP benefits from the fact that athletes also have tangible performance data (wins/losses, batting average, time trials, etc) across sports. They want to share this data: the unbelievable correlations between physiology and performance; the approach to health monitoring and the different ways to interpret or action your body’s feedback. Beyond building a product that people love, Will and the team at WHOOP hope to advance human knowledge with our discoveries.
During our discussion, you’ll discover:
-The key defining characteristics that set WHOOP apart, including skin conductivity, accelerometer data, and continuous HRV monitoring…[13:25]
-Why WHOOP is the only company to measure the activity and fluctuations of the cardiac autonomic nervous system, particularly as it relates to recovery, training status, and training readiness…[13:57]
-The actual hard data being collected by the WHOOP, and HRV, pulse oximetry, temperature, respiration, etc.)…[15:30 & 24:30]
-Why the WHOOP uses a combination of PPG (photoplethysmography) sensors (4 LEDs and 1 Photodiode) along with 3-axis accelerometer, capacitive touch sensor, ambient temperature sensor…[18:17]
-How coaches and trainers can use WHOOP to monitor the sleep, training and recovery status of a large number of athletes and clients…[20:00, 30:00 , 35:50 & 47:50]
-Why the WHOOP has 90% sleep/wake accuracy compared to gold-standard sleep labs…[22:10]
-How the WHOOP sleep coach automatically calculates sleep needed based on your sleep baseline, any sleep debt that has accumulated over the last few nights, and any naps taken for that day…[39:15]
-The technology the WHOOP uses to tell you how much sleep you need and to give you a picture of when you should go to bed based on your habitual sleep efficiency and desired wake up time…[40:15]
-Why athletes like Lebron James and Michael Phelps are using the WHOOP…[59:15]
-And much more…
Resources from this episode:
–WHOOP (use code GREENFIELD for $50 off at checkout)