BC148. Kristen Holmes-Winn – Whoop Technology

Brian sits down with Kristen Holmes-Winn, VP of Performance Optimization at Whoop, to discuss a new wearable technology that is helping athletes better understand recovery.


You will learn…

  • How to maximize your recovery.
  • How sleep, hydration, and other factors affect on-field performance.
  • How advances in technology are leading to performance breakthroughs.


Follow Kristen & Whoop on Twitter @kh_winn & @Whoop




I think what I’ve been able to see working with athletes is that having this ability into their own data – it is just a game changer.  It motivates behavior change.  I think that’s what was really inspiring to me, and again, one of the reasons I joined WHOOP is I saw this as an athlete empowerment tool.

Cain:  Hey, how are you doing?  Brian Cain, your Peak Performance coach, here with the Peak Performance Podcast, and today, groundbreaking technology.  Not only are we going live video podcast where you as Inner Circle members get to experience the podcast before it comes out live, you also get to ask questions and get to interact with our guest.

Speaking of our guest today, Kristen Holmes-Winn, she’s the Vice-President of Performance Optimization at WHOOP, a fascinating new wearable technology helping peak performers unlock their potential by measuring and uncovering secrets that your body is trying to tell you about recovery, regeneration, and performance.  Today on the podcast Kristen takes us deep into the trenches with WHOOP, the science, and explains how their technology is leading to breakthroughs in performance.

Now before joining WHOOP, Kristen was an NCAA National Championship-winning field hockey coach.  She led the Princeton University Tigers – that’s right, the Ivy League Princeton University Tigers, no scholarships – to the 2012 NCAA National Championship.  It gets better.  She won 12 Ivy League titles in 13 seasons.  She had a winning percentage in her career of .940.  This puts her amongst the all-time college coaching greats.

Not only does she excel on the NCAA level as a coach, she also won six National Championships as head coach of the USA Women’s High Performance team.  As an athlete, she was a member of Team USA field hockey for six years, winning a World Cup.  She was also a three-time All-American as a field hockey player and women’s basketball player for the University of Iowa Hawkeyes.  Please welcome to the Peak Performance Podcast Vice-President of Performance Optimization at WHOOP and one of the most successful coaches in NCAA history, Kristen Holmes-Winn.  Kristen, thanks for being with us.

Holmes-Winn:  Oh, thanks so much for having me.  It’s a real honor, Brian.

Cain:  Now I’ve got to ask you before we get into WHOOP, because our audience is coaches.

Holmes-Winn:  Yeah.

Cain:  You’re winning 12 out of 13 Ivy League championships and you win a National Championship and then you step down and change careers to go work with WHOOP.  What was the decision behind doing that?

Holmes-Winn:  I guess I just – I loved Princeton and I love coaching and I wouldn’t say that my passion for coaching had waned at all.  I just became really interested in just technology as a way to foster and enhance performance.  I started getting – I guess I started nerding out at Princeton in the Computational Biology department and Statistics and learning and started kind of – I really wanted to solve this question of when my athletes are with me for 2-3 hours, what is happening the other 21 hours?  How do they understand what habits, what behaviors, are going to lead to optimum performance?

So I just started kind of went down this journey really almost a decade ago to figure out what can we do in our practice environment to really think about the physiology on a deeper level and really try to leverage everything we can from that standpoint in the sense of how do I know how to train my athlete?  I really wanted to answer that question.

When I battled into I and got some technology for when my athletes were in my environment, it was still that open question of okay, well, they get to my practice environment, what can they do leading up to that moment to really ensure that they’re ready to go fire on all cylinders?  That was really the question I was trying to solve and that’s what really led me to WHOOP.

It’s weird to kind of pivot out of coaching because most of us don’t really do that.  But I think for me it was just a new challenge.  The team went to the Final Four last year (Princeton) so I certainly didn’t leave the cupboard bare by any means.  They just kept trekking along, which makes me really happy.  But yeah, I just needed a new challenge, I guess.

Cain:  Well, fantastic.  I think as a coach at the elite level – and a lot of the coaches that are on this podcast listening to this – I think one of the areas that we often overlook, under-train, under-educate on, and it could be the source of maybe our greatest competitive advantage, is recovery.

Holmes-Winn:  Yes.

Cain:  And I think that’s really what attracted me when I heard from Nikki Parsley, field hockey coach at Liberty University, who I think you probably met through either Team USA or through coaching the Ivy League when she was at Yale.  She talked about how WHOOP is really putting metrics – which in the 12 Pillars of Peak Performance is Pillar #4 Knowing Your Numbers – and she hooked it up with how can we quantify and measure recovery at a deeper level so that our teams and athletes can perform at a higher level?

So if you would, I know you’ve put together an awesome presentation here about WHOOP.  I’m going to put that up on the screen and kind of have you share that.  Then for the Inner Circle members that are on this call, please post any comments, post any questions that you have for Kristen either about WHOOP, about recovery, about coaching and the mental game, Princeton – we’ll tap into that side of it as well and we’ll rock and roll.  So let me pull up the presentation here and go ahead and rock and roll.

Holmes-Winn:  Yeah.  So WHOOP at our core is a data and analytics company.  From the wrist, forearms, or bicep we collect key measures of heart rate, heart rate variability, ambient temperature, and three-axis motion.  These measurements are used by our data science platform to obtain insights in sleep, recovery and strain, to provide recommendations for athletes on how they can optimize decisions that influence their ability to perform.

WHOOP also provides a platform (that I’ll give you a little bit later as well) that enables coaches and trainers to better understand both individual and group performance.  So we have kind of an athlete visual.  That’s the app.  That’s where the athletes live.  Then we also have the coach platform, which you can kind of see what’s the bigger screen, the bigger visual on the screen, that you’re looking at right there.

Then of course this (as Brian mentioned), this is the collection method.  It’s a wrist-worn device but you can also wear it on your forearm, as many of our athletes do when they weight lift, or on the bicep – as many of our football players, our baseball players, soccer players, they’ll wear it on their bicep.

So on this slide, I really just put this together just to kind of show that we’re working with a lot of different folks across a lot of different leagues and conferences.  We’re really proud of really everyone that we’re able to work with and really honored.  I think one of our main missions at WHOOP, and one of the reasons why I joined it really, to aim to be a thought leader in exercise physiology.  We’re always pushing the envelope to understand our product better but also understand the underpinnings as it relates to the physiology and the science behind our platform.

We did a huge study with Major League Baseball, which I’ll dig into the data from that study in a little bit.  Really interesting insights into performance and recovery.  Then most recently the Korey Stringer Institute at the University of Connecticut did a yearlong study and they’re about to announce the results of that at the National Strength and Conditioning Conference in July in Vegas.  We’ll be able to really, I think, draw some pretty powerful correlations between WHOOP recovery and recovery metrics, sleep recovery, heart rate variability – I’m sorry, sleep, resting heart rate, and heart rate variability, and performance in athletes.  So we’re excited for that announcement.

So this is really the athlete view.  So this is the mobile app and this is (like I said) really where the athletes live.  This is where they spend the bulk of their time.  On the left is strain.  Strain is essentially a summary statistic of cardiovascular loads.  So basically how hard your heart is working.  I’ll dig into that a little bit deeper.  But basically strain – it’s your 21 scale and it builds across the day.  So as long rhythmic, not linear.  That’s important to know.  It basically takes into account everything from non-workout strain as well as workout strain.  And I’ll explain why that’s really important and why every coach has to understand that, because it’s not just workout strain that impacts the well-being of your student-athletes.

Then recovery.  This is basically how capable your body is to take on strain.  Then sleep performance tells the athlete how close they are to meeting their sleep needs for that night.  That’s a 0-100 percentage and they kind of get that percentage, and that factors into their recovery.  I’ll explain that in a bit as well.

I think what’s really cool – and just to go back one second, Brian, into just the three pillars.  I think what I’ve been able to see working with athletes is that having this ability into their own data it is just a game changer.  It motivates behavior change.  I think that’s what was really inspiring to me, and again, one of the reasons I joined WHOOP is I saw this as an athlete empowerment tool.  Most of the time athletes don’t have this ability in their data.  They arrive at a practice facility.  They’re able to kind of understand in that moment maybe what readiness looks like, but they don’t know necessarily what behaviors helped them get to that ready point or what behaviors might have hurt their ability to kind of get to achieve optimal readiness.  So really this is what I think the app wrestles to the ground in a very elegant simple way, is just this visibility into your own physiological data so you can make more intelligent choices about your body.

Cain:  So the three main pieces that you get, it sounds like, is it’s going to be strain in terms of how much effort or strain you put out that day, where you’re at in terms of recovery towards optimal performance, and then what you need from a sleep standpoint on the third screen here to be able to make sure that you’re ready for peak performance the next day.  Is that accurate?

Holmes-Winn:  That’s exactly right.  Yep.

Cain:  Excellent.

Holmes-Winn:  As well so you can see sleep performance, day strain, hours of sleep, resting heart rate, heart rate variability, and any workouts they might have tracked that day.  You can see a one-day view, one week, two months; so if you look at that little red button at the top, you can kind of go back in time so you can do some retrospective analysis.  And we always have that team average in there as well.  You can put it in any order you want.  I’m highlighting – I’m on recovery so that will kind of give you the order highest to lowest value.  But you can do that across all the metrics.

Cain:  So this would be the screen like this morning when I’m over with SMU Football.  Their strength coach is going to log in, he’s going to be able to look and see all the players that are there and all the players that are tagged with (let’s say) red for recovery.  So if I pull that screen back up, all the players that are tagged with red in recovery, meaning they’re probably in a state where they’re going to have a decreased performance, they could be increasing injury, like they can monitor that and kind of give them a different type of workout.  Is that accurate?

Holmes-Winn:  Totally.  And we can have – with some of the football teams I’m working with currently, they’ll have, the different position coaches will have their team on their own dashboard.  So they’ll see their own team use.  So they’ll see quarterbacks, they’ll see special teams, offensive line, defensive line (for example), and they’ll be able to go on it again.  Athletes will be bucketed based on what their recovery is for that day.

If you click on – so there is an overview of strain, recovery, sleep.  If you clicked on “recovery team view” you’d see just recovery metrics of all your team.  Then you also see subjective inputs.  So we have a quick subjective questionnaire that pops up.  It doesn’t impact any of our algorithms but the subjective questionnaire pops up and will basically ask questions around soreness.  So I don’t think I have a visual of that but that’s powerful in that we’re – this is all about the heart, right?  WHOOP, so we don’t necessarily – we can’t understand neuromuscular fatigue.  But what this wellness questionnaire does is it gives you some context around that recovery score.

For example, if an athlete has a 97% recovery but they are experiencing a lot of soreness, you might want to deal with that athlete differently that day.  You might want to reduce their lifting workout or you might want to modify it.  So I think it gives a really nice picture, a complete picture, of kind of how they’re experiencing.  The question gives, I think, a good context around that recovery metric.

Cain:  Yeah, for sure.  I think I’ve worked with some teams that have used various GPS trackers and I know sometimes they’ll look at an athlete and see – I don’t get to always see the backside of it but – the distance that they’ve gone.

Holmes-Winn:  Right.  And they might not be running as fast.  Yeah.

Cain:  Yeah.  They back off the next day.  And I’ve seen basketball teams that have used heart rate monitors and then they’ll kind of use that to determine what the next day’s sort of workout is, based off of how much they did and things like that.  It sounds like WHOOP kind of takes all of that and simplifies it and puts it together.  The thing I love about the band is like I’m charging mine right now …. this little remote battery pack that goes on so you never have to physically take it off.  But for a football player that is tackling and things like that, do they use the bicep band?  Do they tape it up?  How do they use that as a football player so it wouldn’t break in practice?

Holmes-Winn:  Yeah.  Darrell Stuckey, for example – you’ll see pictures of him.  He just tapes it.  He just puts athletic tape and then a sleeve over it.  A lot of the basketball players, if you go online and – and a lot of basketball players – I think DeAndre Jordan, it’s safe for me to say that he uses it because he Tweets about it.  As well as Blake Griffin.  But they just tape it for practice and they don’t miss a beat.

Then our NHL athletes are starting to wear it on their bicep.  That seems to be the best place for those guys.  So there is a lot of flexibility on the arm in terms of where you wear it and you just have to tape it, wear a sleeve – and yeah, you can wear it during games as long as it’s approved for your particular league.

Cain:  And is it NCAA approved, do you know?

Holmes-Winn:  I think it varies per sport, honestly.  I know that they have different conferences and have different rules around athlete monitoring.  But I think with all the monitoring – you mentioned some of the external load.  I use all the systems and – but again, it was just during practice.  I think the value of WHOOP is really this 24/7 picture that I think really just gives you a better view of really how the athlete is managing, not just the workout and game stress but also just all the other factors that come into play that influence their ability to perform on game day.

Cain:  Excellent.  Let’s take a look and focus here on maybe the athlete strain part.  I know here you’ve got an ice hockey player that I saw quite a bit when he was playing, Jack Eichel.

Holmes-Winn:  Yeah.

Cain:  A piece of information on Jack – I believe it was Boston College, correct?

Holmes-Winn:  Yep.  No, Boston University.

Cain:  Boston University.

Holmes-Winn:  Bite your tongue, yeah.

Cain:  I knew it was one of the two that usually beat up on the Vermont Catamounts.  But I had the privilege of working with those guys.  Would you talk a little bit about kind of this screen that you see about strain and some of the other data that is on there that applies?

Holmes-Winn:  Yeah.  So on the left, that’s kind of the athlete view.  Basically on the day strain you can kind of swipe up and you can kind of see kind of a summary view of what you’ve done across the week.  So this is really trying to mimic what you’d see on the web platform and putting the trend view on the app.  So this is just a new feature that came out, which is great because athletes, honestly, they just don’t go on the web platform to see the trends that coaches do; but athletes don’t, so we wanted to bring some of those features into the mobile apps so the athletes could benefit from those trends as well.

Then you see day strain, average heart rate, as well as calories.  Then you can dig in and see the raw data as well.  When the user identifies that they’ve performed an activity, that will get populated into the app and they’ll be able to see what level of strain they took on during that activity.

On the right, that is the coach view, so if they were to click on any one of the names that you saw in the previous screen, that would enable you to dig in.  So if you clicked on – I know you can’t see the name but #1 (say) – that would take you to the view that you just saw.  If you click on strain, recovery, sleep, you’d be able to then dig into any one of those areas.  Here we’re digging into strain so you can see how much time Jack spent in these various heart rate zones.

So again, I think the value there is being able to see if what you intended for the workout – if the athlete is kind of hitting that target zone and you can kind of modify accordingly.  There are some notes in there and then also some subjective questionnaire as well that talks about ways to perceive exertion which, as we know, is nice to see if those two kind of line up.

Cain:  Yeah, and I’ve seen some research.  I know there are other – some of the college teams I’ve worked with, their strength coach would have their athletes fill out a perceived exertion kind of recovery scale, which it sounds like now that’s all being done right through WHOOP on their cell phone so when the coach logs into the dashboard to see all his players, he doesn’t have to then go into Excel and tabulate anything.  It’s all right there.

Holmes-Winn:  Right.  It’s all done for you.  We can populate any of this into a CSV, so any of these user inputs can go right into CSVs so you can kind of see them up against the objective data that we have going.  I think just in tandem that creates a very powerful – if you think out of the kind of the three factors of human performance, if you look at, you’ve got the external load, the internal load and the subjective load.  If you’re able to kind of account for all three of them, I think it’s kind of the Holy Grail in terms of monitoring.

Cain:  Sure.  If we take a look at the next slide, it kind of shows the pillar of recovery.  Talk about that if you would.

Holmes-Winn:  Yeah, so recovery.  It’s on a scale of 0-100.  Again, it tells you how capable you are to kind of take on strain.  Just a little bit about the score itself:  It relies on machine-learning algorithms to give the athlete a sense of where the body is compared to today compared to baseline.  The three metrics that feed into recovery are resting heart rate, heart rate variability, and sleep performance.  As we know, Brian – I know you know this – there is a lot of literature, a lot of research that tells us that all three of these things play a really important role in determining how physiologically ready one is to reap the benefits of training on a given day.

So this view really – again the app on the left, this is what the athlete would see.  They swipe up.  They get the overview for the week so they can kind of see okay, a couple of green, yellow, red, yellow, brown, trending it back up, awesome.  It’s not bad to be in yellow and red necessarily.  That means that you’re going to have to push your body.  You just don’t want to push it over the edge.  That’s where I think this data becomes really valuable for strength and conditioning coaches to just monitor to make sure that there isn’t this kind of cycle of decline that keeps going on.

So the value of this data is being able to course correct.  So before an athlete falls off that cliff and gets injured, gets sick, weakens immune – all the things that can come from burning the candle at both ends and not getting optimal recovery – you’re able to intervene faster.  Because you have this data, you have this insight, you can really start to balance strain and recovery in an optimal way.

Cain:  Yeah.  I mean, just having done my first IRONMAN in the last year, I wish I had had this last fall.  When you’re traveling and you’re on the road and then you’re trying to train and you’re like, “Well, maybe I’m fatigued but maybe I’m just being weak mentally, let me push through” and the next thing you know you get injured or you get sick.  It would be really nice just to have that data to be able to say “Okay, maybe I do need to cut it back a little bit” or “Maybe I am being weak and I need to push harder because my data says that I’m recovered.”

Holmes-Winn:  I love that you said that because I had at Princeton – my girls were so tough.  They were so tough.  They never wanted to take a day off.  Another reason why I was trying to pursue some technology like this – because this just made it – it was like, “Hey this is what the data says.”  It didn’t make it personal.  It didn’t make it – it wasn’t me saying that they were weak or them saying that “I’m not tough enough to tough it out.”  This was really new to us.  I think it just makes for a heck of a lot better conversation than when you’re trying to guess “Wow, she looks really tired; she just doesn’t seem like herself out there.”  This kind of takes all that guesswork off the table.  And frankly, you don’t even get to that place when you have technology like this because you course correct so much faster.

Cain:  Totally.  Talk a little bit about the next one of the pillars, which is sleep.  We’ve had Dr. James Maas, who is a professor at Cornell, another Ivy Leaguer for 48 years, and he’s talked a lot about the importance of sleep through his books Power Sleep and Sleep to Win and Sleep for Success.

Holmes-Winn:  Totally.

Cain:  There are just so many different ways to measure it.  Have you – we had the CEO, Lasse Leppäkorpi, of the company called Beddit, which was a wrap that goes across your bed.

Holmes-Winn:  Yep.

Cain:  As an athlete, when you’re going on the road and you’re staying in different places, sometimes you forget the strap or it doesn’t hook up because there’s not an outlet close enough, so it sounds like WHOOP is kind of keeping track of a lot of that for you as well.  Is that accurate?

Holmes-Winn:  It definitely is.  As we know, biological sleep is probably the most important human behavior we have so it’s something that we need to pay a lot of attention to.  I think from just coming from an environment like Princeton – where you had the kids walking around in T-shirt “Sleep Is for the Weak” – and I feel like now I think that mindset is starting to shift a little bit.  There is a lot of education.  Schools are investing in education around sleep to help students understand the importance of it.  But honestly, what’s crazy is you don’t know until you start to track.

I’ll have athletes – this is the first thing that we notice when athletes come on the system.  They’ll be like, “Oh my gosh, Kristen, I thought I was sleeping for 8½ hours but I actually was only asleep for 7 hours and 14 minutes.”  So this allows you down to the minute; it allows you to understand exactly how much sleep you’re really getting.  It allows you to see the disturbances that happen across the night.

Most athletes are really – our good sleepers are getting less than 10 disturbances a night because they’ve accounted for all the things that go on from a sleep hygiene standpoint.  They have that wrestled to the ground.  They wear eye masks.  There’s no light pollution.  They wear earplugs.  They do all the things that championship sleepers do to make sure they’re being as efficient as possible when they put their head down on the pillow at night.  But yeah, that’s what this pillar does, is it allows you to quantify all of that and really give great feedback I think to the athlete to how they can kind of right the ship if sleep is a problem.

Cain:  Yeah.  I mean, even last night myself, I think I got in bed at 10:00 and woke up this morning at 4:00.  So you’re thinking, “Okay, well, if I get in bed at 10:00 and get up at 4:00 I’m getting six hours of sleep”; but then as I was looking at my performance data for today for the call, it said I got four hours of sleep.  I’m like, “Well, wait a minute” and I think about well, how many times did I go to the bathroom, or I had my dogs sleeping with me and how many times do they keep you out of getting into a deep sleep, or whatever it is?  So it’s really the time your head hits the pillow until your alarm goes off is not the actual amount of time that you’re getting sleep in.  But that’s what I think often athletes factor it in.  They think, “Well, I’m getting six” when really probably they’re getting a lot less.  Is that accurate?

Holmes-Winn:  It’s very accurate, yeah.  I think when we see – and I’ll get into some of the data, but athletes, when they start to recognize this, they end up dedicating more time to sleep.  They go to bed earlier.  Through the education that we do with the teams that we work with, we really help them understand how to optimize your pre-bed routine.  What are the nitty-gritty details?  How do you mitigate negative stress accumulation throughout the day?  How do you incorporate mindfulness and meditation?  What impact does that have on your autonomic nervous system?  How does that impact HRV?  How does that impact sleep latency?  So there is a lot of education I think that we do, that we love to do, that really helps athletes dial in and figure out how to optimize sleep.

Cain:  Excellent.  Talk about kind of how – you mentioned it a little already here – about kind of how WHOOP helps athletes to make better decisions.  I found one of the ones that was most fascinating to me was the amount of less alcohol that was consumed.  I think it’s something that 18-23 year old college athletes think is like hydrating with water.

Holmes-Winn:  I know, right?  And it is funny.  And it’s not just the young kids.  I’m working with an NBA athlete who – he went out pretty hard over the All-Star break and after that he was like, “You know what?  I’m just, I’m not going to drink anymore.”  The performance cost of drinking is just really high and I think we see these behavior modifications – a reduction of 79%, a reduction in alcohol consumption by 79%.  We see that because athletes see their data and they see what happens when they drink.  They see an increase of disturbances, almost double.  They see a resting heart rate increase by – I’ll show you the data in a second – I think it’s almost double.  They see a decrease in heart rate variability.  They see a suppressed recovery, not just one day after a drinking event but up to five days.  I think it just – it doesn’t mean athletes aren’t going to drink but they end up drinking a heck of a lot less.  We see this across all of our athletes, which is really cool.

And dedication.  They dedicate 41 more minutes to sleep per night on average.  We see an increase.  We see a huge physiological kind of cardiovascular improvement in four months on the platform.  I’ll show you this with some real data before the end of the presentation, but an increase in heart rate variability by 8 milliseconds, which is huge; a decrease in resting heart rate by 4.4 BPM, which also – anyone who understands realizes that that’s pretty significant in four months.  Then a performance of lesser injury.

Then we also see just another behavior modification, is a decrease in screen use before bed, as we know that – I know that blue light, you just don’t realize that that blue light is going to suppress melatonin production, right?  So when you have exposure to that before bed, it really does get in the way of your sleep.  Not just your ability to fall asleep but it will crush your sleep cycles for the rest of the night.

Cain:  Well, then there’s the whole other piece that goes with it of the attention residue, right?  For anybody who is listening to this that has gotten a text message or gotten that e-mail or seen something and then they go, “Okay, let me put my phone away” and then you’re lying in bed thinking about it the whole time, right?  It’s the attention residue.  It’s like that follows you and you have a harder time falling asleep.  Not just the blue light that (as you said) suppresses that melatonin but just the thought patterns that come from being on your phone and from just the addiction of “I’m just going to go look mindlessly at social media or do other things.”

My one tip for athletes is if you’re going to use your phone as your alarm, put it so that you cannot physically reach it while you’re in bed.  You’re not going to be on it.  Then when it goes off in the morning, you’re going to force yourself to get up and set a snooze bar.  But I love the piece about you can actually now quantify that they’ve decreased screen use in bed.

Holmes-Winn:  And I think as athletes and just as human beings, I think we’d all say, “Yeah, I know drinking hurts me, I know it doesn’t help performance” but to actually see it in black and white, I think that’s what creates this change of behavior.  Because a coach all day can tell their athletes they need to sleep more, they need to drink less, but I don’t know how much that works.  I think seeing this data from what we’ve seen has really changed behavior.  And this is just a study that we did looking at alcohol consumption across our NCAA population.  You can see their resting heart rate after not drinking and then the resting heart rate after drinking.  Obviously a massive increase.  Then also a huge reduction in heart rate variability.  So when it comes down to it, it’s just how much is drinking really worth it?


Holmes-Winn:  Yeah.  And they’ll see it.  They’ll see the performance cost of that heavy night out.  That’s where I really encourage our NCAA coaches to actually make sleep – to hide sleep, to make it private.  Because athletes will see this on their own.  They don’t need a coach telling them to make these changes.  They will see it in their sleep.  They’ll see it in their recovery.  So I think by hiding sleep you really do put the onus on the athlete, and from what I’ve seen they take their own action.  They don’t need the coach coming down on them with numbers as it relates to this.  They do it on their own.

Cain:  Wonderful.

Holmes-Winn:  Yeah.

Cain:  [FEEDBACK LOOP].  It sounds like that might have fixed it.  Can you still hear me?

Holmes-Winn:  I can hear you, yep.

Cain:  Alright.  Let’s rock and roll.  So talk a little bit about the recovery suppression sort of post drinking and that stuff.

Holmes-Winn:  Yeah, so this is – so you won’t return to your – in this case.  So this athlete doesn’t return to their baseline until day five.  So their baseline recovery was suppressed for up to five days post drinking event.

Cain:  Got it.

Holmes-Winn:  So it takes a lot.  I think most people think it’s just going to take a day to recover and that’s not the case.  As we see in the data, it takes up to five.

Cain:  Yeah.  How about that?  So a lot of it is just kind of building that awareness about how all their choices and things affect their body’s ability to recover and then perform again.

Holmes-Winn:  Exactly.  And again, one of our MLB coaches calls this app “the wisdom accelerator,” which is kind of cool.  It accelerates wisdom.  Again, by giving your athletes I think – investing in your athlete in the way that – and by giving them access to their own physiological data, I think is really important and I think a great first step to build that awareness toward elite performing behaviors and an elite performing mindset.  This is just – that was just some data around the recovery and how we see a recovery – more green days as opposed to red days because they’re thinking about sleep in a different way.  They’re thinking about their hydration and their sleep and all that.

This is just kind of a high-level view of the recovery.  You can see lots of things affect recovery:  fitness level, health behavior, stress, diet, hydration, recent strain, and sleep.  So the recovery score basically kind of takes all that into consideration and kind of buckets it in this very kind of simple kind of stoplight visual.

Cain:  Love it.  I know you hit on some of this research already, but a little bit of kind of the case study outlines that you all put together.

Holmes-Winn:  Yeah, so this is one.  We’ve done many types like this but I thought this one was kind of cool, just to pull out one example.  This is an NBA athlete and their first two months on the system, so it’s going to take you kind of through a journey of what he looks like from a strain, sleep, and recovery perspective across these two months.  So yeah, you can go to the next one.

This first – and this is the web so I literally just kind of took this from the web platform.  So again, this is what the coach would see.  So this is the first month and you can see the strain (the blue line) is a 0-21 scale and the recovery is the multicolored red, green, yellow, 0-100.  You can see that they’re mapping really far away.  So this first month I think the coaches were just kind of seeing how this athlete responds to strain.  They weren’t really actioning the data.

So this is the first month.  You can see again big – not really – the strain and the load isn’t necessarily corresponding with the amount of recovery that was needed.  If you go the next month, you can see this is where the coach is now starting to action the strain.  So if the strain is really high, they prioritize recovery the next day to get the athlete back to baseline.  So again the velocity is, of course, to want to try to manage that load, map strain and recovery as close together as possible so you can keep this athlete firing on all cylinders across the season.

The first month’s sleep.  This athlete’s average sleep performance was 75.6% and you can see that he’s spending some good time in that peak zone but he definitely has a lot of days where he’s really missing the mark from a sleep performance standpoint.  The second month you can see that just through education, awareness, maybe taking some different steps from the sleep hygiene, kind of buttoning things up, he’s now really in that kind of peak zone a heck of a lot more and definitely is not in that low zone really barely at all compared to that previous month’s.  Just in one month it’s an increased improvement of up to 10%.

Cain:  That’s fascinating.  If you go back to the first month, you see all the dips, right?

Holmes-Winn:  Yep.

Cain:  Which might be travel.  This might be partying.  This might be just up watching TV or whatever it is.  But if you look at the set stuff, he just totally recommitted himself to recovery.  It would be fascinating to see his scoring percentage during those two months.

Holmes-Winn:  I’m going to show you.

Cain:  How about that?  Awesome.

Holmes-Winn:  But before we get there, go back one more.  The athlete in this second month stopped playing video games after 4:00 PM.

Cain:  Wow.

Holmes-Winn:  And again, this isn’t a scientific direct correlation but he started – he did change some behaviors that I think really helped him improve his sleep efficiency.

Cain:  Awareness is the precursor to all behavior change, isn’t it?

Holmes-Winn:  It is.  It is.

Cain:  What you’re unaware of you’re never going to change, and what you’re aware of you can change, especially when you see the data.  It’s not necessarily Well, how do I feel, because how you feel is irrelevant.  It’s Let’s look at the data and see how you’re actually performing and where you’re at and then use maybe feel as an addition to that, but we’ve got to get the numbers.  I think this is a breakthrough and going to help a lot of performance.  I’m excited to see the next slide about how the scoring went up.

Holmes-Winn:  Yeah, so go – skip past this.  Go to the next one.  Okay.  So this is really interesting.  So the first – so there is a forward.  This first column shows 2016 without WHOOP.  So no guidance whatsoever into sleep, strain, or recovery.  Not really looking at the load of the athlete or really anything.  This is not being monitored at all.  You can look at the difference between the first column and then the second column when he was using WHOOP in the exact same time period (and he was healthy in both of these time periods).  He played actually fewer minutes in this second column than he did in the first column but was more obviously a heck of a lot more effective.  He almost doubled his points; total assists, rebounds remain the same but you can see the improvement in his field goal percentage and pretty much the same in free throw percentage.  I think the points per game is pretty shocking.

Cain:  Wow.  Yeah, it would be interesting too if you did a study where you just asked him how he felt and how much more confident he was or how much more prepared he was, what he would have said.

Holmes-Winn:  Yeah.  I mean, I definitely see from just talking to folks – and we do have some questionnaires about energy levels.  I think people do have an increase in energy, the mood.  And one of our swim coaches at Penn State University is just an awesome guy.  He had a great quote.  He just said, he’s like, “I don’t really know a whole lot about data but all I know is my kids when they step on the pool deck, they’re happier, they’re in a better mood.”  He’s like, “It’s probably just they’re sleeping more.”  I was like, “Yeah.”  So yeah, I think there is something to be said for that for sure.

Cain:  Awesome.

Holmes-Winn:  Yeah.

Cain:  Can you kind of talk about the engagement with WHOOP and how it translates to optimal performance?

Holmes-Winn:  Yeah, so I think – that last slide was just one example but I think this just shows across a lot of different disciplines.  When we look at 43 (we’re looking at swimmers here), actually athletes who are more engaged on the platform, they do a better race time in the championships than the teammates who were less engaged.  So visibility in the data and engagement in the platform will help you perform better is what we’ve been able to prove.

Cain:  Love it.

Holmes-Winn:  And this is another example.  This was actually the 2015-2016 season.  We followed an athlete the entire season.  This is pretty compelling.  When you look at his recovery when it was in the green, what his stats were versus when he was in the red.  So just this idea that group recovery correlates with performance is something that we’ve been able to prove time and time again.

So I wanted to go through the MLB study of it.  I know you’ve got a lot of folks who you work with are in that baseball world.  We actually, we do not have one NCAA baseball or softball client, which is shocking.

Cain:  Right after this one we’ll see, because I know there are now coaches that are million dollar men in college baseball, so we’ll see if… baseball is a little bit behind unfortunately, but it’s coming.

Holmes-Winn:  I know.  I hope so because this is a population I work a whole lot with.  I work with 13 Major League organizations and they’re just awesome guys and I just really see a place for this and certainly at the NCAA level.  But so we’re able to see a positive correlation between recovery and pitch velocity, so I think what this is compelling is if you have a higher recovery, you’re going to throw the ball faster and that’s just the bottom line.  So there is a lot of incentive again by putting guys on the mound who have a high recovery because they’re going to throw the ball faster.  The same with exit bat velocity.  We also saw a very strong correlation.  Guys who were more recovered, they swung the bat faster, which is what that means, right?  Exit bat velocity?

Cain:  Yeah.  Exit velocity would be the ball coming off the bat.

Holmes-Winn:  Oh, coming off the bat.  Okay.  So, but I would imagine that’s getting your hands through?

Cain:  Yeah.

Cain:  For sure.

Holmes-Winn:  And this I thought was really interesting.  So I think normally it’s like five days that you get pitchers off but we actually saw pitchers were fully recovered after three days.  So they return to their baseline after three days’ rest.

Cain:  Wow.

Holmes-Winn:  It’s kind of interesting, right?  I don’t know – we’re working with quite a few different major league teams right now trying to really nail this down and try to see how what – because everyone is going to respond differently, right?  So five days for one guy might be what he needs but another guy might need three days.  Another guy might need four days.  So if you know how to customize that across your bullpen, I think – because there are a lot of people wanting to figure that out.

Cain:  In baseball it’s always been five days just because that’s what it’s always been, right?  There’s a lot of old-school “that’s just the way it’s been” so trying to back all that up, which I think is fantastic.

Holmes-Winn:  Yeah, it is.  I think it’s just asking question of the data and really see/try to figure out well, what does this really mean and can we do things differently?  Not just – and again I think we have to be really careful about assigning protocol across an entire team because every single person is… Performance is highly idiographic, as we know, but how people respond physiologically is very different.  We almost need to start to treat our athletes like triathletes in the sense that we’re really customizing training based on how they are adapting or how they’re not adapting to the various demands that come across their life.  I think if we could do that, we’d have a healthier team and a higher-performing team.

Cain:  For sure.  For sure.  Talk about the travel a little bit now.  With James Maas we talked a little bit about the travel and time zones and using a light book and eye mask and all those things when you’re traveling.  Talk a little bit about some of what you learned with the recovery from a before-travel baseline.

Holmes-Winn:  Yeah.  So it usually takes a couple of days to recover after travel.  Same time zone.  When you’re definitely crossing time zones, it’s going to take a bit longer but travel definitely has an impact.  It’s interesting because I did an analysis with NBA and I actually saw the opposite.  This was not – this was across five athletes.  But the five athletes all have families.  They have young kids so their home environment actually is a lot less conducive for sleeping, so when they go away, they actually sleep better and recover better, which is really funny.  So I think that was – again the data into that.  They went home and were like, okay, we need to figure out how to improve the home environment a little bit so they can get the sleep that they need.

Cain:  Sure.  I know I’ve heard of the Yale football coaches saying that the best night they sleep is the Friday night before the game when they’re on the road.

Holmes-Winn:  When you’ve got your game plan done, you’re all – there’s nothing more you can do.

Cain:  No doubt.

Holmes-Winn:  Yeah, I hear that.  And this is just an example of some of the cardiovascular improvements we saw in the Major League Baseball study that we did.  Again, this is across 230 athletes in the 2016 season.  Just two months on the platform we saw a reduction in resting heart rate (which again, that is a good thing) and an increase in heart rate variability, which is a good thing.  So this just basically demonstrates that athletes on the system improve cardiovascular fitness and a lot of this has to do with just by prioritizing sleep, changing behaviors.  All of that is going to affect your capacity for effort, right?  So if you can give more, it stands to reason you will improve your fitness levels, which is what we saw in the time of the athletes on the platform.

Then this is just another kind of view of the dashboard.  We actually were able to kind of dig into this pretty well but this just gives just a quick rundown of what this dashboard view kind of gives a coach.  You can again monitor sleep efficiency.  You can blow through that.  It’s fine.  You can go to the next one.

We have tons of reports which are really I think interesting and kind of help coaches understand a higher level how the athletes are responding.  This is just a quick weekly view, weekly report, that a coach can get that just shows at a high level how well they’re balancing strain and recovery across the week.  It’s actually a two-week view and you can kind of see the two weeks – Week #1, Week #2 – kind of up against each other.  You can see this coach is really mapping strain recovery almost perfectly.  So this is a really great example.

I think the other way – and this is a VIP report.  This is what the athletes get.  So this goes directly to the athletes in their inbox on a weekly or bimonthly basis.  They’re able to basically kind of see a summary of their recovery, what they did for workouts, and we also give them some insight into what behavior is correlated into a higher level of performance.  So it’s just, I think, a nice touch point with the athlete.  And again, driving this kind of – we really want to try to empower the athlete so I think that’s what this report kind of helps us do.

Cain:  Great.

Holmes-Winn:  And this is a view.  This is another report that we send out.  Again just a high-level view.  You can see that left box is resting heart rate, heart rate variability on the right trending in the right direction, and then basically all of our sleep metrics that we track.  I think this is a really powerful report for a captain (for example) or – that’s how we’ve kind of used it toward the back end of the season last year just as a …  You can’t tell who it is, right?  So each little data point is an aggregate view of the entire team.

So we also have these for individual athletes as well but this happens to be one that shows a view of the entire team.  Where this I think is really helpful is a captain could kind of say, “Wow, guys.  Hey, we’re trending in the right direction, we’re about to get into playoffs, keep it up.”  Just using data to kind of talk to the team and get some insights around where they can improve and what they’re doing really well.  “Hey, we’re starting to accumulate some sleep debt here; let’s try to keep this under 30 minutes going forward.”  They actually can start to set tangible goals based on data, based on statistics, and I think that’s where you really start to gain some ground in an environment and really improve a culture.

Cain:  I think that’s wonderful.  Kristen, thank you for taking the time to join us here on the podcast.  We’re going to get to some of our Inner Circle members’ questions as well as some of the questions that I’ve got for you.  The contact information, is it best for them to contact you [email protected] and on the phone number here?

Holmes-Winn:  Yep, that works perfectly.

Cain:  Excellent.

Holmes-Winn:  Call anytime.  E-mail.  Yep.

Cain:  Excellent.  Well, let’s go to some questions here from our Inner Circle members which I’ll be able to pull up here.  Jacob Armstrong comes in with a question of What is the biggest obstacle to overcome with a new technology like WHOOP and old-school coaches?

Holmes-Winn:  Yeah.  It is tough.  I’m not going to lie.  But I think when you start to – I think showing a whole lot of numbers is definitely not the way to go about it.  I think it’s sharing some stories.  I think sometimes it’s getting an athlete to use it and endorse it from inside can be really valuable.  Yeah.  I mean I think – and a lot of these coaches who are kind of old school are also really successful too and I think it can be hard to convince those guys.  But I just think that if you can get across that there is another layer/another level that the team can get to if you start to quantify the right things – again, you don’t have to measure everything but if you measure recovery and you measure sleep and you measure strain, then you’re ¾ of the way there.  And I think getting a coach to recognize that this isn’t going to go away and if you don’t start collecting data, your competitors will and there’s going to be a point where you’re not going to be able to catch up.

Cain:  I think another great question brought in that kind of ties in with the recovery piece and ties in with kind of the strain because strain – obviously you’re going to be sweating in how much you work depending on environments.  One of the leading sports nutrition consultants, Brittney Bearden, has the question of Does diet and the diet habits that an athlete has (water intake, food, hydration, etc.), how does that influence the recovery score?

Holmes-Winn:  Yeah.  So one of the inputs in the recovery score is heart rate variability.  Heart rate variability is such a powerful marker because pretty much everything influences the autonomic nervous system and that’s where – heart rate variability is a function of the heart but it manifests in the autonomic nervous system.  So if you are under-eating, over-eating, you’re going to be sending signals to the heart.

So the autonomic nervous system is broken into two branches.  You’ve got the sympathetic and parasympathetic.  When your body is stressed, it’s going to send signals to the heart from the sympathetic branch and that’s going to be basically saying “Okay, I’m under stress, I need to perform right now.”  So when those signals are sending over and over again, that’s going to reduce your heart rate variability, which is going to make you less able to adapt to your environment, which is going to influence your recovery score.  So diet and hydration absolutely influences your autonomic nervous system, which is reflected in the recovery score.

Cain:  Wonderful.  Any other questions coming in from Inner Circle members, go ahead and post your question in the comments section here on our Inner Circle Members Only Facebook page.  We’ll take those questions, we’ll put them up on the screen, and have Kristen answer them for you.  Kristen, one of the questions that I have would be for a coach or somebody that wants to get involved and they’ve got to come up with a budget to try and work with WHOOP.  What kind of financial investment is a program looking at to get started with WHOOP?

Holmes-Winn:  I mean, I would say to come in.  We have three different levels of service, software, and analytics.  So the hardware is basically $375 and if you go online and purchase it, it’s $500 so there’s a little bit of a kind of a price break there.  Then the service, software, and analytics kind of gets more expensive the more service, software, and analytics you desire.  So the base level is kind of our bronze level and that’s about $720 per athlete per year.  So it’s, I think, not too huge of an investment.  It depends on how big your team is but there are price breaks at 50.  Brian, I can send you the pricing sheet for you to kind of post for your Inner Circle.

Cain:  Great.

Holmes-Winn:  But that’s kind of just how we break it down.  I would say just to get your feet wet with the technology, I would come in at bronze and then you’ll start to recognize what kind of questions do I actually want to ask about the data, and then that’s where we can get really into the reporting.  One of my favorites is the experiment report, which basically allows you to kind of test and see how athletes are responding to something new you’re doing in your environment.

So let’s say you’re incorporating a new strength and conditioning program and you want to see how your athletes are kind of responding to that.  You can actually do a little report that kind of shows you exactly the baseline of your athletes across the metrics that we track up against the experiment time frame.  You can do that with nutritional interventions.  Let’s say a team starts working with you (for example).  What was their baseline before you and then what was it after, once you start giving them the interventions that you put in place to kind of help them think about performance?  So lots of different reports like that.

Cain:  Yeah.

Holmes-Winn:  That costs money.

Cain:  That’s awesome.  One question from Dana Oliver.  He is a little bit late to the party coming in here from Montana.  Dana is an athletic director and high school football coach.  I think the question he is asking and that comes to my mind is, let’s say he wanted to use WHOOP with his team and as a high school athletic director and coach wasn’t able to provide a WHOOP band for all of his athletes.  Would it be beneficial to take a sample size of his athletes?  Maybe the 11 that are playing the most, or maybe 2 additions, and does that seem beneficial in terms of just kind of quantifying data?  I know it’s an individual but can they use it that way as well?  I know Catapult (that one of the football teams I work with uses), they don’t have everyone in it, just only certain athletes.

Holmes-Winn:  Yep, you can definitely do that.  At the University of Tennessee, actually that’s how they got onto the system early on and it kind of grew from 10 to 20 to 25 and now they’re up to like 100, I think, at that university.  How they went about it is that they put it on the athletes who were really serious.  They put it on the captains.  They kind of created a culture around it.  They say #TennesseeTrains.  Those are the people that wear WHOOP.  They are the ones who are serious about their craft and they’re serious about performance and they want to optimize all their behaviors so they can be the best athlete for UT possible.

So I guess my recommendation would be yeah, go ahead and take a small group within that population who you think is really going to take to it and get them using it, and hopefully they can evangelize throughout the team and get more athletes on it.

Cain:  Love it.  Love it.  Again, we’re speaking with Kristen Holmes-Winn of WHOOP.  You can contact Kristen at [email protected]  Her phone number is here as well.  Check them out at www.WHOOP.com/elite.  And Kristen, my question for you is what question has not been asked that should have been asked by one of our guests?

Holmes-Winn:  Yeah.  I think just really understanding the power of HRV and that metric.  Just not – just understanding the general mental and physical well-being of your student athlete, there is just no better marker.  I think when we think about technology, it’s really – I think WHOOP in particular – it’s about helping them think about lifestyle.  It’s not just about being a better insert-your-sport (basketball player, football player, baseball player), it’s about being a better student, a better friend, a better mom, a better dad, or whatever it is that you’re trying to do in your life.  And you can’t do that if you don’t prioritize sleep, if you don’t prioritize recovery, and I think that’s what the power of this platform really brings.  That’s why I believe in it the way that I do.  I just think it’s hard to – you have to start to measure stuff or you just are kind of guessing.  And life is too short.

Cain:  Yeah, life is too short and athletic opportunity is too short.

Holmes-Winn:  It’s really short, yeah.

Cain:  Look at what Theo Epstein did, not only with the Boston Red Sox as their general manager but now with the Chicago Cubs, in taking a databased approach and then coupling that with – if you read his book The Cubs Way, which is one of the best books I’ve ever read, especially the last couple of years because I’ve seen them go from last to world champions.

He talks about the data and the metrics and the measurement, the whole new Cubs facility with sleep rooms and aqua flotation tanks and yoga rooms and Pilates rooms in terms of recovery and regeneration, but then also the character piece that ties into it.  I think when you put all that stuff together, it’s a significant win but if your athletes aren’t recovered, it doesn’t matter how hard you work, it doesn’t matter how great your culture is – if you’re not at an optimal level for performance, you will be beat by someone who is maybe with less talent and with less culture.

Holmes-Winn:  Yeah.  So well said.  Yep.  Absolutely.

Cain:  So for all the coaches that are on the call, again, thank you for joining us.  Again, if you want to contact Kristen, please head over to www.WHOOP.com, contact her via e-mail, give her a call.  Kristen, thank you so much for being on the Peak Performance Podcast.  It was outstanding and I’m looking forward to a continued relationship and continuing for myself to recover using my WHOOP band to report back to you smashing IRONMAN times and not getting hurt.

Holmes-Winn:  I love it.  I love it.

Cain:  Well, thank you for being with us so much.  I appreciate it.  And Dominate your Day.

Holmes-Winn:  Alright, thank you so much.  Thanks for having me.

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