Should You Trust Your Recovery Score?-এর সম্পূর্ণ প্রতিলিপি

the metrics that are automatically populating, in particular sleep hours, HRV, resting heart rate, uh steps taken throughout the day, time in deep sleep, light sleep, things like this. 00:04:58.800 --> 00:05:05.759 When they are recording how they feel, they are recording the fatigue of how they feel. 00:05:05.920 --> 00:05:10.720 They're recording how yesterday's session went, normal or not normal. 00:05:10.800 --> 00:05:12.319 And we'll get into that here in a second. 00:05:12.399 --> 00:05:16.480 Um, an overall feeling, either uh above average, superior, or something like this. 00:05:16.639 --> 00:05:21.360 How you do this, because these are mood is also something that they rank. 00:05:21.600 --> 00:05:28.240 The resting heart rate, time in deep sleep, light sleep, that that's all sinking from the aura ring itself. 00:05:28.399 --> 00:05:36.480 When the athlete is putting in a mood, okay, a mood feeling over here, which there it is, way up there. 00:05:36.639 --> 00:05:42.079 All you do is you have to go into training peaks and put in worse than normal, normal, or better than normal. 00:05:42.160 --> 00:05:44.720 I'm not going to change this right now because I would change the data. 00:05:44.879 --> 00:05:49.040 But the same thing with yesterday's training, overall feeling. 00:05:49.199 --> 00:05:52.319 And as you see, it just takes a couple clicks, okay. 00:05:52.399 --> 00:05:53.920 And you can do this on the app as well. 00:05:54.079 --> 00:05:55.600 This is on the desktop version. 00:05:55.759 --> 00:06:02.959 But overall, the athlete or yourself, if you're a self-coached athlete, you you do need to go in here and just push a couple buttons. 00:06:03.040 --> 00:06:09.519 Okay, it doesn't take long, but gathering this subjective feeling is really important. 00:06:09.680 --> 00:06:10.000 Okay. 00:06:10.319 --> 00:06:11.839 Qualitative information. 00:06:12.000 --> 00:06:21.759 That means the quality of what is being done or felt or perceived is just as important, if not more important, than the data itself. 00:06:21.920 --> 00:06:22.160 Okay. 00:06:22.240 --> 00:06:35.759 We'll we'll talk about like time and zone for sleep and um some of the measurables that are coming in like this because it's not bad, but this subjective feeling, the qualitative information is really, really helpful. 00:06:36.000 --> 00:06:40.079 Additionally, if you know somebody is injured, you want to know that, right? 00:06:40.240 --> 00:06:48.319 And in particular, it's like if I've got an athlete that's that is injured, they're gonna text me direct and say, okay, crashed and broke my arm today. 00:06:48.480 --> 00:06:51.120 Of course, then we don't do training, right? 00:06:51.439 --> 00:06:59.680 But also recording it, that's a good history of what happened when, or, or maybe it's an overuse injury, something more mild. 00:06:59.759 --> 00:07:23.759 Uh, but recording it is always really helpful, especially when they feel sick, okay, just like slightly sick or something like this, that cues the coach in particular, if somebody's looking at the data, in and it color codes it in in red, okay, because see up here, there's not too much other than the mood state going on uh in in this particular week. 00:07:23.920 --> 00:07:28.319 But then all of a sudden this week we see fatigue is high, feeling is below average. 00:07:28.480 --> 00:07:38.560 Okay, and this is where if you start to see that a couple days in a row, now you might want to intervene, obviously reach out, check in, see how things were going for this athlete. 00:07:38.720 --> 00:07:50.480 And in particular, when you have enough data kind of streaming in over several months, you can get a snapshot of the trends that are going on, especially HRV and sleep hours in particular. 00:07:50.639 --> 00:07:54.240 That's really what I'm looking at there, as well as a resting heart rate. 00:07:54.319 --> 00:07:57.759 That's a pretty good one, too, which we'll talk about more overall. 00:07:57.920 --> 00:08:01.040 But these trends, very good to look at over time. 00:08:01.120 --> 00:08:11.839 But I really want everybody to be encouraged to start doing more subjective things, such as sleep quality, fatigue, soreness, stress, all these things. 00:08:11.920 --> 00:08:23.439 But you do have to go in and you have to click on the particular metrics in order to get that into training because that's not going to automatically sink as of right now, anyway, without a neural link planted in your brain. 00:08:23.600 --> 00:08:30.240 Okay, so now what I'll show you is the same athlete's data streaming into WKO5. 00:08:30.639 --> 00:08:40.720 It's a it gets to be a little bit more granular and you can do uh a few other things with it, especially in terms of kind of a better way of looking at uh trends over time. 00:08:40.879 --> 00:08:42.000 Like are they stable? 00:08:42.080 --> 00:08:43.120 Are they baseline? 00:08:43.279 --> 00:08:45.440 You know, is the stress changing rapidly? 00:08:45.600 --> 00:08:48.480 Are the sleep hours steady or are they all over the place? 00:08:48.720 --> 00:08:51.919 Okay, and here's where some of the noise can come into play too. 00:08:52.000 --> 00:08:54.159 You see these streaks of sleep hours. 00:08:54.399 --> 00:08:57.120 This is just some bad data coming down into there. 00:08:57.200 --> 00:09:03.200 It's not like the athlete is, you know, sleeping zero hours per night, but they they've got times awoken and things like this. 00:09:03.279 --> 00:09:14.720 So again, what you're doing right now, anyway, with the data as it is, you still need to kind of like visually look at things and make sure that you can understand this over time. 00:09:14.799 --> 00:09:23.120 But again, I'm not using any of this to necessarily change the training because what we do is we look at when things are a little bit more volatile. 00:09:23.279 --> 00:09:28.559 For example, that athlete where things were more volatile over here, right? 00:09:28.720 -->

00:09:37.279 The the kind of more recent data where the sleep quality overall is changing quite a bit, right? 00:09:37.440 --> 00:09:42.799 And the mood and motivation and stress levels were were ticking up a little bit. 00:09:43.039 --> 00:09:46.879 You can go to the training side of things and see has the performance changed. 00:09:47.039 --> 00:09:53.360 And in particular, I'm looking at five minute, 20 minute, 60-minute normalized power here, and a ton of other things actually. 00:09:53.600 --> 00:09:59.600 But it's like the performance, at least on a few data points, this isn't suffering necessarily. 00:09:59.679 --> 00:10:04.720 And then there's a ton of other things that I check on the back end in terms of just how they're feeling. 00:10:05.039 --> 00:10:07.440 But are they able to do the training? 00:10:07.600 --> 00:10:07.840 Yes. 00:10:08.000 --> 00:10:11.360 Okay, well, let's just add in a bit more recovery, right? 00:10:11.440 --> 00:10:18.639 Um, checking in on what's going on with sleep in terms of getting in the way of a good night's sleep or something like this. 00:10:18.799 --> 00:10:24.399 So you check in with the athlete, but overall, when things are a little bit wobbly, you can see it in the data. 00:10:24.639 --> 00:10:26.320 Do you see it in the performance data? 00:10:26.480 --> 00:10:28.639 And if so, you can do a massive intervention. 00:10:28.799 --> 00:10:34.960 If not, usually it's just a matter of adding in more recovery, getting more sleep, and taking care of yourself. 00:10:35.120 --> 00:10:43.759 Okay, so now let's look at uh an athlete who doesn't have a wearable device streaming in all the sleep data and and other metrics too. 00:10:43.919 --> 00:11:01.519 If this is you, what you can do, and this athlete isn't doing it, but what you do is on the day, this is on the laptop version, you can do it, uh, the app as well, just hover over the plus button on both platforms and you go into metrics and you can log mood for my female athletes any menstruation, right? 00:11:01.600 --> 00:11:02.960 And then you look at the sleep hours. 00:11:03.039 --> 00:11:05.120 You you can put in whatever you want, okay? 00:11:05.279 --> 00:11:14.960 But the subjective aspects, the overall feelings, letting the coach know you're sick or tracking that stress, soreness is a huge one, fatigue. 00:11:15.200 --> 00:11:18.320 Just go in there and rank it right there. 00:11:18.559 --> 00:11:22.399 Once you start to do that, it'll populate more data over time. 00:11:22.480 --> 00:11:32.159 And like I said, not every single one of my athletes do this, and not every single one of my athletes have devices, but the power is at your fingertips if you so choose. 00:11:32.320 --> 00:11:37.600 It does take a little bit of effort, maybe you know, 30 to 60 seconds per day. 00:11:37.759 --> 00:11:43.519 If you're just plugging in a couple of them, again, come in, click it, away we go, right in there, right? 00:11:43.679 --> 00:11:45.039 It just takes a little bit of time. 00:11:45.200 --> 00:11:49.440 Now, if you don't care, you don't have that time, uh, it's just not of thought. 00:11:49.519 --> 00:11:52.480 It's not part of the hobby of what you want to do as an athlete. 00:11:52.639 --> 00:11:55.200 Continue to train, get good sleep, move on. 00:11:55.440 --> 00:12:00.399 Okay, let's discuss other important things coaches care about when it comes to readiness and recovery. 00:12:00.559 --> 00:12:04.320 The next one is the context of life and training goals. 00:12:04.559 --> 00:12:09.039 This is life stress versus prescribed workout for the day kind of stuff. 00:12:09.360 --> 00:12:13.519 If both stress levels are high, can you handle it? 00:12:13.759 --> 00:12:15.279 Should you handle it? 00:12:15.440 --> 00:12:16.240 Should you do it? 00:12:16.480 --> 00:12:16.799 Okay. 00:12:17.200 --> 00:12:24.159 Or maybe you just slide that workout to another day if life stress and training stress and perceived stress is all high. 00:12:24.320 --> 00:12:32.480 Now, if life stress is always high, what tools or options do we have that can bring that down to match the goals of your training? 00:12:32.639 --> 00:12:34.799 This is what I'm talking about with the context. 00:12:35.039 --> 00:12:38.720 Next is current quantified training load. 00:12:38.879 --> 00:12:45.759 For this, think about training stress balance or acute training load numbers, or how fresh or unfresh do you feel? 00:12:45.919 --> 00:12:52.720 Also, how hard was yesterday's training, which is a metric that I showed you on how to measure in training peaks alone. 00:12:52.879 --> 00:13:00.080 These are all things to help quantify where you're at right now relative to where you're headed or think that you should head. 00:13:00.240 --> 00:13:03.919 Another one is total amount of sleep from last night. 00:13:04.080 --> 00:13:07.919 Now, with the device or not, you can measure this. 00:13:08.159 --> 00:13:13.440 Do you know roughly the quantity of sleep that you got last night or you usually get per night? 00:13:13.600 --> 00:13:16.000 Another big one, resting heart rate. 00:13:16.159 --> 00:13:18.879 This could be captured overnight or upon waking. 00:13:19.039 --> 00:13:20.320 This is super useful. 00:13:20.480 --> 00:13:26.960 Old school, maybe for some, but super effective to get the insights on readiness status. 00:13:27.200 --> 00:13:33.440 You need to establish baselines first, then track it over time to know what's high, low, or normal for you. 00:13:33.600 --> 00:13:37.919 Knowing the day of and trends are very important with resting heart rate. 00:13:38.080 --> 00:13:40.320 Next is perceived sleep quality. 00:13:40.559 --> 00:13:48.960 This this is a big one too, how you actually perceive your sleep to be versus what the device tells you can have a gap. 00:13:49.200 --> 00:13:59.840 I try to coach my athletes into ranking this either on training peaks or internally for themselves before checking the app first thing in the morning or

making any decisions on the day. 00:14:00.080 --> 00:14:03.279 Okay, tune into yourself before you tune into that app. 00:14:03.440 --> 00:14:09.840 So getting reliant on a device to tell you how you feel is a slippery slope that you don't want to slide down. 00:14:10.159 --> 00:14:12.799 HRV, heart rate variability. 00:14:13.039 --> 00:14:16.399 This could be captured overnight or upon waking as well. 00:14:16.559 --> 00:14:31.120 Based on most of the research I've gone through, experts that I've interviewed on this channel and working with athletes, measuring first thing in the morning gives you a better net outcome alongside these other subjective feedback data. 00:14:31.360 --> 00:14:43.200 This is due to a number of different reasons, including how the autonomic nervous system actually works, how a wearable actually measures HRV overnight, and athlete habits. 00:14:43.440 --> 00:14:54.799 If you want to learn more about how to measure HRV first thing in the morning, I suggest you read anything from Marco Altini and his company HRV for training. 00:14:55.039 --> 00:14:58.240 I've got articles and interviews linked below. 00:14:58.320 --> 00:15:02.000 This is something that I use myself on a very regular basis. 00:15:02.159 --> 00:15:06.960 Overall, it's another tool out there that's not sinking into training peaks. 00:15:07.039 --> 00:15:12.799 It's a separate app to measure some of this readiness and give you insight on the go or no go on the day. 00:15:13.039 --> 00:15:21.360 So this is the majority of stuff that most coaches I know care about when assessing readiness for training and recovery status. 00:15:21.600 --> 00:15:22.639 So let's move on. 00:15:22.799 --> 00:15:25.440 Let's talk about what coaches don't care about. 00:15:25.600 --> 00:15:27.120 I'll just kind of rip through these. 00:15:27.200 --> 00:15:27.519 Okay. 00:15:27.759 --> 00:15:30.240 Number one, supposed time and sleep cycles. 00:15:30.399 --> 00:15:32.480 Number two, proprietary recovery scores. 00:15:32.639 --> 00:15:34.799 Number three, proprietary readiness scores. 00:15:34.960 --> 00:15:37.200 Number four, total times woken. 00:15:37.440 --> 00:15:39.519 Number five, total times awake. 00:15:39.759 --> 00:15:45.440 I pay very little attention to these numbers for myself and my athletes. 00:15:45.679 --> 00:15:54.960 If I see something super strange in the data outside of the normal trends and stuff, I may reach out, but otherwise, I just let the noise be noisy. 00:15:55.120 --> 00:15:59.360 Why don't coaches care about some of these finer details and deeper numbers? 00:15:59.519 --> 00:16:02.879 Well, it's because they are not yet accurate. 00:16:03.120 --> 00:16:12.080 They're not accurate compared to lab-based technologies such as polysomnography or how sleep is actually measured in a controlled setting. 00:16:12.320 --> 00:16:16.720 Wearable devices infer sleep from peripheral signals. 00:16:16.879 --> 00:16:19.679 It's not actually measuring sleep itself. 00:16:20.000 --> 00:16:28.240 Data are consistent night to night, and they're doing a good job of capturing the macros of things, but not the micros. 00:16:28.639 --> 00:16:37.279 That means the trends of the data may be helpful over time, like I've been saying, but not the day of granular information to decide training stays. 00:16:37.600 --> 00:16:50.080 In short, sleep data alone, especially from wearable devices, does not accurately paint the picture of recovery status for any athlete from any device as of now. 00:16:50.399 --> 00:16:52.639 So, what are the training implications? 00:16:53.360 --> 00:17:05.440 Ultimately, most athletes are trying to figure out the answer to my training says X, my whoop or whatever says Y, my body says maybe, I don't know, what should I do? 00:17:06.079 --> 00:17:11.680 This is where the process of logging all that subjective data leads to awareness. 00:17:12.240 --> 00:17:17.839 Reading your body, knowing your body, and making smart decisions about training comes from awareness. 00:17:18.079 --> 00:17:24.559 If you have a daily process of assessing your body and making decisions, you will get better at assessing your body and making decisions. 00:17:24.720 --> 00:17:25.839 You see my point. 00:17:26.480 --> 00:17:35.200 The one golden rule I have with my athletes, though, on the go or no go on the day is I do I call it the warm-up rule. 00:17:35.359 --> 00:17:43.920 What this means is if you're ever in doubt of recovery stays, readiness, and hard training is on the docket. 00:17:44.559 --> 00:17:48.000 Upon waking, do your assessment, log training peaks. 00:17:48.240 --> 00:17:49.920 Don't check the app right away, right? 00:17:50.799 --> 00:17:56.160 But go about your day, your normal routine, and don't make any decisions just yet. 00:17:56.400 --> 00:18:01.039 Proceed as if you were to be doing the hard workout and get into the warm-up. 00:18:01.359 --> 00:18:21.839 My warmups before a hard workout, as you can see in this example here, usually follow a pattern of progressive aerobic overload with cadence drills, openers, hard efforts, and short recovery periods to increase core temperature, activate all energy systems, and get the muscle groups uh where they need to be for a hard workup. 00:18:22.240 --> 00:18:31.680 This usually pulls the veil back of anything masking or confusing the feelings of your body so that it can help you make better decisions. 00:18:31.920 --> 00:18:38.720 So, in summary, you do a hard warm-up, then you evaluate, and here's a couple scenarios. 00:18:39.119 --> 00:18:45.200 If you do the warm-up, still feel tired, legs aren't there, and your body feels worse, don't do the workup. 00:18:45.519 --> 00:18:48.559 Ride endurance or just ride home if you feel bad. 00:18:48.799 --> 00:18:56.799 If you do the warm-up, body feels normal or not any worse, proceed with the workup because sometimes you just have to punch through. 00:18:57.440 --> 00:19:04.160 Now, if you do the warm up and the

legs open up, body feels better than before, definitely proceed with the workup. 00:19:04.400 --> 00:19:09.839 Here I'm giving autonomy to the athlete to read their body and give it what it needs on the day. 00:19:10.000 --> 00:19:13.759 Typically, most athletes want to do the hard work. 00:19:14.000 --> 00:19:17.279 So I'm not afraid of my athletes skipping workouts. 00:19:17.440 --> 00:19:18.559 I never worry about that. 00:19:18.799 --> 00:19:24.079 It's really helping them to determine when it's good to push and when not to. 00:19:24.720 --> 00:19:33.839 Then learning with them what cues to take from their bodies and their minds to say proceed or pull back. 00:19:34.000 --> 00:19:35.279 This is the art of training. 00:19:35.440 --> 00:19:40.640 And I have yet to see a device that does it any better than a highly aware athlete. 00:19:41.039 --> 00:19:47.920 And to get that awareness, you need to teach it and you need to develop it within the athlete if you're a coach. 00:19:48.240 --> 00:19:52.720 Now let's talk about why you would need to use a wearable device at all. 00:19:53.119 --> 00:19:55.359 Well, you don't have to. 00:19:56.319 --> 00:20:04.960 But if you want to, I want you to know what you're getting into, what to expect, and hopefully you're starting to realize that it won't solve all of your recovery problems. 00:20:05.279 --> 00:20:11.839 It could help bring some awareness to your process, but only if you take the longer term approach. 00:20:12.079 --> 00:20:21.920 If you already have or are using a device, make sure that it's automatically syncing to training peaks or whatever platform that you're using so that you're gathering the data all in one place. 00:20:22.160 --> 00:20:23.359 Hot tip on this one, by the way. 00:20:23.599 --> 00:20:31.200 Training peaks or TP and Aura recently-ish uh just allowed syncing of uh Aura devices. 00:20:31.279 --> 00:20:35.440 So for all the Aura ring users out there, you can now sync your stuff. 00:20:35.759 --> 00:20:48.000 Now, the day of data or the readiness score from most of these devices that push it to you is not as powerful as the trends of the data that is provided over time. 00:20:48.240 --> 00:20:58.559 So you need months of this data first to establish these baselines, then overlay it with training and performance outcomes to actually have some reasonable insights. 00:20:58.799 --> 00:21:07.519 Finally, many of these trackers try to do it all movement, training, sleep, readiness, recovery, and more. 00:21:07.920 --> 00:21:11.039 And if it sounds too good to be true, it probably is. 00:21:11.279 --> 00:21:18.960 Things like HRV, resting heart rate, and total time asleep may be the most important data that's collected from these things. 00:21:19.039 --> 00:21:34.799 But overall, these are small directional arrows when it comes to determining training on the day compared to the bigger directional arrows, such as program design, how an athlete feels, and if something is wrong, like feeling sick, injured, or super low motivation. 00:21:35.039 --> 00:21:42.559 These aspects would influence me to change training more than a suppressed HRV or a slightly elevated resting heart rate. 00:21:42.720 --> 00:21:45.200 In the end, multiple data points are best. 00:21:45.359 --> 00:21:48.559 Devices will probably get better, and so will the data. 00:21:48.640 --> 00:21:54.160 I've had an aura ring since they first launched, I don't know, a thousand years ago. 00:21:54.400 --> 00:21:57.119 But I will admit it wasn't that great at the time. 00:21:57.279 --> 00:21:58.960 It's gotten way better over time. 00:21:59.119 --> 00:22:00.480 And the same thing with the Whoop. 00:22:00.559 --> 00:22:08.640 When I tried that out for the first time, and now a lot of my athletes have it, the data and the device and the software and the insights are much improved. 00:22:08.799 --> 00:22:16.799 It's been fun to see how these devices have evolved and added capacity to what they track, and I only see it potentially improving. 00:22:17.039 --> 00:22:32.480 So there may be something in the future, either better software or hardware improvements that lends itself to better quantitative data tracking for performance and recovery that may give a better answer on should I train hard today or not? 00:22:32.640 --> 00:22:33.440 But we're not there yet. 00:22:33.599 --> 00:22:37.440 In my opinion, if you're a data nerd, you like the numbers, start gathering. 00:22:37.759 --> 00:22:45.440 We may be gathering something that we don't even yet know how to use from these devices, and it may show us something more useful soon. 00:22:45.680 --> 00:22:54.720 However, it's another costly hobby that you'll have to take up, spend time on, money, and have the bandwidth in order to manage the data enough to know how to use it. 00:22:54.799 --> 00:22:56.880 And some people just don't want that. 00:22:57.039 --> 00:23:02.160 So actually, let's discuss a few more low-tech recovery tracking tips and then we'll wrap this thing up. 00:23:02.400 --> 00:23:13.680 I think more than anything, it's helpful for you, the athlete, or if you're a coach listening to this, to start recording subjective things like mood, fatigue, sleep quality, soreness, yesterday's training perceive stress. 00:23:13.839 --> 00:23:28.000 Spending 30 to 60 seconds per day on this, putting it into training peaks in any other training log that you have will help bring awareness to how you feel today and glean insights on what you should do and how you should perceive the training. 00:23:28.160 --> 00:23:45.599 These, alongside the measurable data from devices, may help you bring a fuller picture to the readiness as an athlete and help prevent fatigue, burnout, staleness, or injury and put you in a better place to more appropriately perform well on hard days and race days. 00:23:45.759 --> 00:23:54.720 So, in closing, I really want to make the point that I am not advocating for one device over another or for you to even get a device if you're not already on one. 00:23:54.880 --> 00:23:57.039 More data adds more complexity. 00:23:57.200 --> 00:24:00.559 And on this topic, the complexity may not be worth it right now. 00:24:00.799 --> 00:24:17.119 However, getting into recording qualitative information on yourself, such as how you feel on the day, your mood, and everything else that I talked about, may be very useful for an athlete and definitely for the coach, not only for the day of, but for trends over time. 00:24:17.279 --> 00:24:36.640 So if there's anything you change or adopt from watching this video, it's to evaluate and record more about how you feel and use that information alongside all the fancy data that you can gather to make sense of what works for you, what doesn't, and look for ways to improve your sleep, recovery, training, and performance over time. 00:24:36.880 --> 00:24:39.039 Finally, remember the warmup rule. 00:24:39.119 --> 00:24:49.680 If you're in doubt of how you feel when hard work is prescribed, simply proceed with a good warm-up and evaluate how you feel after that before deciding to pull the plug or to proceed. 00:24:49.920 --> 00:25:00.720 Oftentimes, we'll surprise ourselves and realize that with a lot of good habits behind us, our brain and body just needs a good warm up, clear the head, and go for it. 00:25:00.880 --> 00:25:01.759 That's it for today. 00:25:02.000 --> 00:25:02.720 Hope you liked it. 00:25:02.880 --> 00:25:14.000 Head over to trainwrite.com to explore more about how a coach can help streamline your data and bring more awareness to yourself for better training outcomes.