How to Establish Intensity Ranges with Adam Pulford, CTS Pro Coach | KoopCast Episode 162

trail and ultra runners what is going on what's happening welcome to another episode of the KoopCast the first episode of the KoopCast in 2023 i'm happy everybody is here today and we are kicking off the brand new year with something that is fundamental to endurance training and that is how do we assign intensity ranges this is something that i have long wrestled with throughout the course of my career when i very first started coaching athletes and we used pace we needed a way to determine what was hard what was medium what was easy how are we going to anchor the intensity are we going to do it off of vo2 max or lactate threshold power or lactate threshold speed or critical speed all of these things kind of come into play and they have absolutely evolved over the years and we do it differently in different endurance sports and i've been able to translate a lot of those differences into why ultimately i have kind of settled on predominantly using rating of perceived exertion to apply to ultra runners so as you are trying to figure out that particular endeavor within your training i decided to bring on one of my longtime coaching colleagues and one of my coaching colleagues that i respect the most that has gone through this whole ordeal

with a tremendous amount of athletes as well and i think that has a really good grip on it we're going to welcome to the podcast today repeat offender adam polford adam is a coach that i've worked with since 2006 over at cts he has served a number of different roles most importantly he is a fantastic coach on the cycling side of things but he's also been a team director for the orange seal off-road team the 2016 2020 uci professional women's team and team the team show air professional factory mountain bike team but more importantly more relevant to this conversation adam brings to the table a wealth of experience and knowledge on how to use the tools of the trade to correctly prescribe intensity and throughout the course of this podcast we walk through it all we walk through how he would do it with a cyclist how i would do it with a road runner how i now do it with ultra marathon athletes and why those methodologies are all important in their individual contexts i hope you guys get a lot of a lot of information out of this i know that each and every one of you out there you're trying to figure out how to arrange your individual training and the podcast coming up throughout the remainder of january hopefully lays a lot of that context beginning with this one how to determine intensity so that is it i'm going to step right out of the way and get right into the conversation with one of my longtime colleagues and friends i hope you guys enjoy it here's my conversation all about intensity with coach adam

polford all right let's do it man let's do it thanks for coming back by the way yeah you're welcome um you ever get sick of having cycling coaches on your podcast no because once again man like there's better performance and training context in that sport as compared to trail running like trail running i think is like about a decade behind in a lot of this stuff and we see that in both coaching and in practice where stuff that has already been like vetted like in terms that we'll talk about some of that stuff right determining intensity ranges and stuff like that has already been vetted it's like either novel right to the trail running space or they haven't even heard of it and i can't tell you man like once every couple weeks i come across something in the trail running space i'm like we did that shit like 10 years ago like come on we've got to we've got to like move forward like have a broader context thing so no i don't have especially when it's you man i always appreciate you i mean i appreciate coming on here because i learn like i well before this we're just talking about like uh lacing into some of the stuff that you're doing with the ultra runners and i'm like yeah let's do it because i learn a lot from you guys and you guys you guys all of you coaches are really pioneering um the way individuals are thinking about running and there's gonna be some stuff that we probably talk today i'm gonna be like i don't know what you're talking about but i'll

tell you how i do it that's what i want to know man so here's the context right let's set it up for the audience we'll set it up for the audience right the the ultra marathon lottery season is kind of in the it's at the tail end of it right everybody throws their name in the hats of different races races and their calendars are starting to shake out right they know that they're going to do this one race in february and this next race in april and this next race in march and this is the time of year that athletes they start to get their shit together right they start to get their training shit together and one component of that not the not not probably not even the most important component but one of the big components of it is how to determine intensity like how do i determine is this hard is this easy should i you know run at this heart rate range or this speed or this rating of perceived exertion and when you combine that with the zone two phenomenon that is is kind of like taking over the the space right now i kind of think that this this becomes an intriguing launching point for the for for the year kind of for for two reasons is one what i just mentioned it's even in a sport where you have really good intensity gauges like cycling and like triathlon and even road running where you can use pace there still is a very legitimate conversation around how do you determine what's easy medium and hard or however many you know different gears you want

to give or however many different ranges you want to give that spectrum and the second piece of it is is how do you actually deploy all that stuff right trail and ultra running just has to have this you know unique situation where the the terrain and the duration and the environment collectively obscure a lot of these traditional in ways of gauging intensity that we would know that we would normally use but i kind of want to just start out with like the fundamentals right like we're in the we're in the business of coaching adam so you get an athlete tomorrow right which might even happen like you get an athlete tomorrow one of the first things that you are going to have to do probably not the first but one of the first thing you're going to have to do is determine okay how do i determine what this athlete's intensity ranges are so take take the listeners and take me because it's been a long time since we've talked about this take me like through that process of what you would initially do like on the onset of getting that athlete in order to determine what the correct intensity ranges should be sure um the the first bit is like do you talk to them first or do you get their data first and i try to get their data and it's sometimes like either either way and the more data i can get the better and these days i think we're pretty lucky especially on the cycling side where there's a lot of users a lot of athletes that have been using either training peaks or garmin or exert or something like that where

they're housing their data so if i say have some email correspondence with them i say where do you house your data have you used training peaks before let's get an edge of training peaks and connect me as a coach so that's the first thing i do in before and and and this is different than like five years ago where i usually like jump on the phone and i have a list of questions for them now it's like give me your data then let's schedule a call the reason i do that is because i just get a better understanding of who they are as an athlete and what they've done and then and then when i do get them on the phone see how their perception of who they are as an athlete matches up with the data that i have and the reason i like to start with the data is it's a it's a starting point it's an anchoring point and it for me anyway it gives me a better picture of who i'm working with yeah you know what also kind of goes along with that so i have the same thing i'm just like give it to me wherever it is and you've been through this as well like sometimes it's like very well encapsulated right the training data that you actually get it's in training peaks it's in garmin you can make sense of it there are good notes there are good notes from either if they were self-coach or even if they worked with a coach before you can kind of like peel all that stuff out you can tell what general like volumes they can tolerate when they take time off you know during the year if they have some sort of injury that's that's popped up right or some sort of illness that that that where there's no training like for a couple of weeks

those things kind of become very obvious i've i've you know come to appreciate any and all manners of that from the very well housed training peaks and in the other soft form software platforms out there kind of being the pinnacle of that to just literally stuff written on the back of napkins and i got this one kid who had like this three ring binder right of all just handwritten stuff and it took me like two days to actually go through but it was extremely insightful and i don't want to broaden this conversation out too much but since we're already on it there's a plethora of additional information that you can get out of that initial data dump my two hero points are where were you performing your best and where were you performing your worst and then looking look at the training that was leading into that or what were the potential causes right lifestyle and all those other things leading into those points and use those not as copy paste mechanisms to do in the future but kind of use them as clues as to how they adapt across different types of stress and workloads and and and things like that but but interestingly enough let's kind of focus it back on the intensity right so you go through the athlete's data right what are the things from an intensity perspective are you pulling out that are initially going to start to set that intensity framework yep so i'm looking at um again you scan for when they're when they're performing their best

and how let's just say like how long ago was that yeah and the way the way i work is i look at the past month and the past 90 days in terms of their current physiology and if they have in whatever those numbers are i start to work with those numbers say i get them on the phone and they say well my peak 20 minute power last year was you know 300 watts and but i'm when i'm looking at the data in the past 90 days all i see is maybe 260 and i'll say okay well you know your current physiology is kind of suggesting it's a little lower than that so let's just start a little lower you're not as good as you thought you were exactly um we won't get into like all the power meter options but if they have a a buffet of power meters meaning different brands and options like locations of where they're measuring their power that's a whole other story but if it's consistent then we can go with the numbers right so so so getting a current idea or picture of their physiologies first and foremost uh and i'm a big fan of testing okay so if they have so say they did 300 for 20 minutes and and i and i test like short-term medium term long-term okay when i'm doing field testing and that could take a few days or it's not just a one-time test but if they're telling me that i say i can do 300 i say okay let's go test then if not we're going to roll with like a 260 or 270 so i'll use what's currently in the system or i will

test versus relying upon only um some sort of algorithm or computer generated thing so but i think the key points here is is first off it's recent right i think that's important for anybody to realize is hopefully your your fitness and your performance capacity are malleable right in both directions right they're malleable on the upside and they're malleable on the downside you can train and you can and you can detrain but if you're talking about either setting power ranges on the bike or the equivalent to that on the running would be pace ranges uh for for a runner taking a more immediate or more short-term snapshot and i think 90 90 days is a good window to start with and then kind of working into the 30-day range and seeing if that's actually any different between those two uh between those two points is the right way to go you you led me into the next one or the next kind of like way that you could corroborate that information right you so you get this initial snapshot just based off of the data actually let's not go into that right so you have their data how do you actually figure out where to set well first off what's the anchor i think that's that's an important thing to go off of like what is the anchor of intensity that there we're then kind of expanding upon and then what specifically in the training since you're limiting it to training initially are you looking at to a determine the anchor and then b determine what the ranges are around that anchor

so my anchors are always based in performance in in cycling that's power duration and for those power durations it is 60 minutes and less when we're kind of scanning those specific durations we're looking at uh like five second 20 second one minute five minute 20 minute so the maximum you can produce across those time frames exactly mean max power for those durations yep yep um and and sometimes depending on the athlete i'll go i'll do 60 minute as well okay and the reason i select those is that those duration those power durations pertain to the three different energy systems for the athlete and i'll anchor more on 20 minute peak power to start to glean more insights and set ranges if i've got like one day one data point to base everything off of that's where i'm gonna go but i'm gonna if i can i'll look at five minute one minute and a sprint power to determine much of that because after about eight minutes or so everything becomes a little bit more predictable and steady in the way that people perform and produce their power once you in so that's the more aerobic you go the less aerobic you go or the more anaerobic you go things change and that's based more on genetics but this is all based off of they've been doing workouts or they've been going hard for the last 30 or 90 day evaluation

point that you're actually been doing right because if you're taking a power duration curve based off of a bunch of easy work right you're not you're getting mean max power but you're getting mean max power at some percentage less than what their maximum would actually be so riddle me this when you have that let's just say i'm doing you know i'm gonna bring up zone two because we like to pick on it i've been doing zone two training for the last 90 days and that's all that's going that's all the data that you have can you make reasonable conclusions about their entire intensity spectrum based off of that type of work for that period of time yeah that's a that's a fun question um and i would say straight up like if all you have is 90 days of zone two data for somebody you haven't talked to them you don't know what they've done in the past you don't have races i just say straight up no let's do a field test let's get you into testing at that point it's it's not necessarily like a field test because you could say okay um what race what was your big race last year they say lead bill and they say how fast did you go nine hours okay he's probably at four watts per kilo for uh threshold and then i can and then say how much do you weigh okay now i can do the calculation and make a better observation yeah that's how we go about it okay um however then you got like somebody too and then

this is like another thing where it's like say they've only done a bunch of zone two riding on the bike but they've been like i have a lot of my colorado athletes uh getting into schemo so they're filleting themselves like going up mountains and skiing down and say i don't have rich data from the cycling side of things but their threshold is probably just as good if not better than august yeah so you got to think about that you got to use that yeah you've got to use the context of the workouts that they're that they're actually doing i kind of egregiously skipped something right like the first thing that you that you do may not be a field test i know that you deploy that a lot and and we'll get into into how we can actually uh how to actually drive these numbers out in the field but you can't just give them workouts right just start giving them workouts not a lot of just go as hard as you can for the set of the you know intervals however you kind of can construct the interval set and you can drive really good intensity based information just from getting a handful of those because as long as you know what you're looking at and this is not easy this takes a pretty good coaching eye as long as you know what you're looking at in terms of okay this duration of interval and this combination of rest and recovery and interval length and things like that kind of means this from an intensity perspective as long as you can see through that you're going to get pretty close after you get a handful of workouts in yeah exactly and i think like as you're asking me these questions

i'm trying to you know answer specifically to that question right but like all these little sneaky side things that we do as coaches uh they tease out differently depend on the process of coaching the athlete right so if i got somebody who says i can do 300 but all i've got is 360 right i say let's start 260 270 let's do some tempo work shorten the recovery periods and i'm going to look at how they respond to that right so again that's the example yeah right so let's go through the testing options sorry let's kind of go through the testing options and we'll go through the workout options first so you mentioned the three tests you do like walk the listeners through what you're prescribing and then that what that means for the intensity ranges so first of all i'll say too like i'm a you said before i do testing a lot i'd say that is very dependent on the athlete the situation the data racing all this kind of stuff i'm a huge fan of testing because you don't know what you're working with until you go find it yeah that's true so um that's why i'm a fan of testing and i'll deploy it frequently or infrequently depending on what we're doing um so the let's see one two three the three primary tests that i do are an anaerobic and neuromuscular kind of power test and those will be um a series of 20 second sprint tests and a one minute all-out test generally like if i've got some time i'll just do that on one day call it good and i'll bring it in i'll bring them in with a pretty

good long warm-up get those sprints in the one minute the next day i'll do a 20 minute all out and those are all maximum yeah yeah yeah all up the next day i'll do a 20 minute time trial 20 minute all out and in also a huge part of this it probably an anchoring point by the way is perceived effort because when you tell somebody max you have to kind of quantify this so i'll educate them and i've got documents to show to them and describe on a scale of one to ten what i'm looking for what is a 10 what is a one what's a five that kind of thing and so all these are at 10 and it's 10 for the duration which pacing for 20 seconds is very different than 20 minutes yeah and we laugh and listeners are like well of course adam but like how many athletes don't understand that yeah because you see the the 20 minute power test spikes way up and they got an awesome three minute and then and it just caves right so pacing is huge and it's in the context of that anchoring to the effort all right so anyway the anaerobic test 20 second sprints one minute then i do the uh you know i have a day here that's one day the second day is the 20 minute time trial then i'll usually depending on what i know about them i'll usually give them an easy day and then on like the fourth day of training i'll do a five minute all-out test and that typically i can get three testing days within four days for most people

to keep them fresh and that's how i gather my data and so you design all the power ranges around those i don't i don't prescribe any i don't so if it's a new athlete i don't prescribe any power really so when do you get to the power prescription only if i've got good data i've been working with them and we know within a reasonable range of what they've done before and what they can potentially do and i've got tools to kind of use that and tease that out so even with this even with a new cyclist with a power meter you're potentially foregoing intensity prescription by power for months potentially until you get that context because the thing that i try to teach as well is what is a max effort how do you pace for it the problem so the great thing is that in cycling we have a lot of data the bad thing is we have a lot of data people rely upon it too much and this is like both like a great thing with what i do and also not a great thing of conversations and this is how it goes do a 20 second sprint how much power should i produce go maximum effort okay so what's the number like um all out okay so between what and what all right so now if we have a good rich history of data i say all right you've done 750 before if you beat that that's great if you don't beat that

cool because we're just testing to see what the baseline is right now that's my approach because see stuff changes just like you said like you can train up you can train down decay detrain whatever you want i want to know what the heck i'm working with now well because you yeah you're working with what you got now but you realize especially with a new athlete and especially if in our scenario that we just came up with if they have been doing a lot of zone two work those power ranges are going to be extremely malleable in the within the first 90 days if you're doing if you coach adam are doing your job right right yeah that's it it's so interesting because you know there are a lot of athletes out there and we both you and i probably used to coach this way where we jumped into the range prescription the intensity range prescription whether it was a heart rate range prescription or a power-based range prescription or even a pace uh range prescription if you're working with like a roadrunner or something like that way too early in the process like we thought we were way too way too clever we could do one type of test or we could take one type of evaluation and then go yeah you know here you go your threshold is seven minutes and 30 seconds per mile and that means this range should be seven minutes per mile and then you go a little bit harder and it's 6 45 and things like that and i think what we've come to appreciate is first off how valuable those instantaneous tests are whether you're doing it in the field or in the lab we'll talk about lab testing

later but also how adaptable the system is even with experienced athletes kind of early on and you can get you can not screw it up a lot but you can just like the from an intensity perspective you can get fouled up a whole heck of a lot even with a power meter which is supposed to be perfect if you're not really paying attention from the get-go and i think for like every listener right now like rewind that and listen to it again because number one coop admits that we made a lot of mistakes and we did a lot early as a coach okay and two the the reason why we made those mistakes is all these like fancy zones from based on all this power data and whatnot was originally designed to be descriptive not prescriptive yes okay and that's and that's a lot of people forget that right now and in the reason what what is descriptive mean it means tell me more of what happened during a training session or a race so that i can understand as a coach what the athlete experienced and we moved so quickly and so concentrated into prescribing and telling athletes what to do that we have in my opinion now need to kind of swing back the other way and that's why i think in my coaching practice now i'm especially in testing i'll say don't worry about the power go do the effort then we'll come back and look at the power yep i mean it's interesting to hear that perspective from uh from a cycling coach

because i tell you what man i get i still even to this day i get dinged around a lot for not using heart rate as much as i should probably would be the common piece of uh uh kind of like criticism for designing ranges and things like that and it's ba it's based off of just what you had mentioned a lot of these mistakes that we have made but also the the orientation of them and you remember both you and i've been coaching for long enough that when the the consumer world not the professional cyclist but the consumer world went from heart rate based training to power based training it uncovered all of the idiocy that we had previously thought was infallible with heart rate based training i mean instantly and and we still we were like oh hallelujah now we've got all the answers and then now once we uncover like power based training for a little bit we realize that there are like moles and hairs on it and things like that that we need to kind of course correct but it was never more stark than that transition and i took that experience away and said okay listen if i'm going to use ranges i want to make sure i want to absolutely make certain that it's under the right construction and then i actually am doing what i think i am doing which is what wasn't happening in on the heart rate side of thing that the power thing that that the power evolution really kind of really exposed so it all kind of it all kind of like comes back to that one of the other things i'll mention is is you you and i have a very very similar

strategy for how to teach effort just have them go do the hardest thing possible and then de-scale everything from there right 10 out of 10 for whatever the duration is and then work down to okay i want this to be a nine this to be eight this to be a seven because it's hard to shoot for the middle right just perceptually like people just don't understand if you just go do the hardest freaking thing possible no matter what the duration is that then becomes your calibration point and then you can kind of like almost back calculate things from there so in a lot of ways i will do something very similar where i even when i have good data i'll say listen just go do these set of intervals 10 out of 10 maybe you've got an extra one or two minutes in the tank that's your rating of perceived exertion of 10 out of 10 and then let's calibrate the rest of the workouts the rest of the workflow based off of that that's the anchor point right it's essentially as hard as you can go yeah yeah and to me like i man we could we could get going right now but like to me i don't care how good technology gets i don't care how good ai or machine learning or anything so if i can go and do a bunch of zone two and then have somebody tell me what my ftp what my one minute power should be and all this kind of stuff i think it's all bullshit because it's not real like because because there's stuff between the ears that ai ain't gonna measure yeah right and i'm also coming from like a context of

well um like strength training as well because it's always kind of been based in this too like you've got a rep max yeah go do it come back and then we calculate stuff from there now it's that's not perfect but like go do it find the edge find what you can actually do and then work with that as opposed to some something else well we'll get into all the other contrived it kind of contrived ways to do it but i think something that is is we shouldn't leave out is using physiological testing to to acquire this so i mentioned this off air i might as well mention it on air as well i'm going to bring in our lab manager and one of our longtime colleagues renee eastman who has more tests underneath her belt than you can swing a stick at i mean she's every every week the lab seems like it's freaking full of cyclists and runners that she's uh running through the testing protocol but that is another way so i'll use that podcast to just like more in depth describe the testing process but the the theory is is you go do a a single or a battery of physiological tests in a lab where you are measuring things normally oxygen and lactate are the things that you're measuring and then from there you're deriving the ranges your rpe range your pace range your power range your heart rate range however you want to however you want to slice that uh that fish up so what is your

utility or what is your perception on getting somebody into the lab irrespective of the circumstance new athlete existing athlete and things like that in your mind what's the what's the proposition there sure yeah um so to kind of like back up real quick when i was talking about the testing protocols that i use the one thing we didn't really close the gap on is i look at those edges or those maximums to then set the training zones specifically to them and to the instrument that they're using for training yeah okay and then we go from there do some test workouts and go through so if i've got an athlete that can get to a good lab that has good instruments and a good um practitioner you're already starting on the caveats man i might encourage it i'll ask renee that i'll ask renee that like what yeah what should athletes look for when they are going to do testing in terms of the equipment the practitioner the whole the whole nine yards the equipment all that stuff so yeah we can we can leave we can leave that as the caveats for now and renee can explain it better exactly and i think it's it's good for her too because i'm a little i used to do a lot of that stuff i worked at the human performance lab at the university of wisconsin in lacrosse and then worked in the in the lab at cts did a number of a lot of tests there we had the right equipment and right now off the top of my head in terms of a metabolic heart i don't know

parvo hasn't changed that much yeah our metabolic heart is a parvo metabolic heart yeah okay so you know there's things that i check to make sure that it's good so the reason is if you go do a test with somebody who doesn't know what they're doing or you go do a test with shitty stuff then you're not going to get good numbers and you're not going to get good zones and therefore you're not going to get what you're looking for therefore but if it is good then it's worthwhile then you go get it because in the end we're trying to figure out intensity for training zones so you can go do really good training really high quality training and make a positive adaptation to get better in your sport that said if it costs a lot to get to the lab even if it is a good lab i won't in cost in terms of time and money because i can do something that's just as good if not better because it's like specific to the instruments that they're using without having to travel to get there so but that being said like pump the brakes there for a minute and say if it's a low cost meaning you know let not a ton of travel not a ton of money and if they're into it for sure let's go do it because then it's it's a great learning opportunity for them it helps them to get a different perspective or an angle again making sure that there's a good practitioner to guide them through this process of testing and then what we can do is take that data extrapolate to the way i work to see if my numbers are matching up and they

usually do with what we're looking at in terms of a vo2 max in terms of the lactate threshold and then deploy it into their training to either create training zones or educate them on the numbers that we got from the test and then the numbers that we're using in training on the road with their power meter so that's one way right you're you're kind of using it as cooperating evidence right because you've got your own power profiling kind of setup that you use to set all the ranges the i think it's worth mentioning to the listeners because a lot of this is going to be too much inside baseball for them the graded exercise test that is used in almost all physiology labs is going to differ than what adam just mentioned there are some there are some physiology labs that are going to do a power profiling test that is similar or maybe the same as as what adam just mentioned but a standard graded exercise test which is what you're going to find in most labs when you're when they're looking for lactate threshold and and or vo2 max is a continuous ramp protocol right you either do it on a three minute stage or a four minute stage and maybe sometimes they're broken up between the lactate test and the vo2 test it's all that that's all too much uh too much detail for this conversation that renee will kind of go over but the but the but the the point that i'm trying to make is is that the test is the the test protocol is different you're getting information that is kind of either cooperating or telling you that you screwed it up in the from the from the onset and then and then what do you kind of do from there is that the correct like summation of it yeah pretty much and like to make it like

real short like if you go to it just like we detect uh like you talked about there with a ramp test and we get like a lactate threshold typically you can then educate the athlete like a cyclist on what that means with their power duration because it's going to be a little different than in a functional threshold power and i'm guessing it would probably be the same for running is that correct yeah it's very similar yeah yeah very similar your your lactate threshold speed or if you wanted to use heart rate as the as the intensity anchor your lactate threshold heart rate is going to be slightly different in that condition than your functional threshold speed or your functional threshold heart rate the thing honestly that confounds um uh all of this is just the temperature of the lab right if you can just get the temperature of the lab right it's it actually makes a really big difference in terms of translating stuff to uh to to the outdoors um i want to make one mention that we'll we'll probably go over in this upcoming podcast with renee there are other value there's a there are other value propositions of getting physiological testing that are not solely dependent upon setting the intensity ranges that you can absolutely take into the field of training to determine training architecture and what's going on metabolically and strengths and weaknesses and stuff like that that's a whole other kind of kettle of fish but i want to kind of nail it back down to the intensity and i really want your personal perspective on this adam it's like because you've had athletes that you've worked with for

a long period of time that then and go and get this these this type of testing how much of a difference is it actually making on the intensity prescription because you've kind of couched it as well it's got to be convenient and you know this caveat and that caveat like how much of a difference from a very pragmatic point of view is it actually making um i mean if you're asking the question if they go do a test and i get that information and i compare it to say the data the data that i have based on my tests that i've done with my athlete is that kind of the context yeah um it honestly in my experience it doesn't matter and i don't know if like if you're fishing for an answer or something like that so close it is it's it is so close i what's interesting and if there's like any like running nerds that's into cycling and let's just say they've listened to the train ride podcast um where we talk about a metric that's really interesting and important to know is time to exhaustion which is a duration that's marking your functional threshold power meaning it can be short or long call it 30 minutes or 60 minutes that's something to correlate to the lab tests that we're talking about because typically if you look at if you get a lactate threshold number in the in the lab that's going to pertain more to that longer duration ftp or tte of around 60 minutes and that's super important to know because

again when we swing back talk about pacing and talk about actual training and going that long it can give you good context of how to pace well yeah based on those um energy systems that we're trying to actually train which is the end goal i'm kind of with you i mean once again i don't want to like stop on the interview that i'm going to do with renee but i really think the value like the predominant value of getting testing and especially multiple testing is looking how at how the physiological profile has changed over time and what training has made what difference at what periods of time like is all this threshold training that you're doing is that actually making a difference and to what extent if you're trying to improve vo2 max are you actually doing it and to what extent and then you can find ants you can you should be able to tease that out in the data like you should be able to work like look at that through the workout data but let's be honest man it takes a lot of workout data to like really figure like really figure that part out like you need a lot of corroborating evidence and a ton of files and a lot of fine-tooth combing to really determine yeah i think your vo2 max power your vo2 max pace right or your vo2 max period has improved by two or four percent or whatever that's like without the metabolic data that's my dog shaking her head by the way without the metabolic data i know that's what my i just let her in the door without that metabolic data it's actually i'm not saying it's impossible and you can do it with training but it

the it's much easier to do it with testing well it's it's kind of fun that you bring that up because um yes you find that in testing and it is valuable and i just poo-pooed on like ai and machine learning oh here we go no no this is actually going to swing the other way i actually rely upon quite a bit of ai and machine learning with the metrics that i'm using to monitor athletes on a daily weekly monthly basis i don't always report that stuff to them but i'm looking and then all the training like you said it takes a lot of training to see if you're actually making a change so looking at that stuff monthly i can look at a model of vo2 max that is either progressing or digressing um with the training and in i think more specifically it's like the relationship of the vo2 max to the lactate threshold yeah that is the most interesting and you can get that in a lab test or you can get that with um you know good tech out there yeah um and but it you got to be looking at that stuff on a lot um every day i i think that so that that thing that you just mentioned i think that that's kind of one of the hero metrics right the percentage of the percentage of vo2 max at your threshold is at however you want to anchor that whether it's power or pace or whatever if you can look at how training adapts that metric that's not that it's the only one but it's but it's a really big one and it also

sets the context for training and let me get kind of give a really practical example because i've i've had this uh in the in in the lab with my athletes and i also notice it in uh the training evaluation that we were talking about earlier so if i have an athlete that i know their lactate threshold is really close to their vo2 max either we find it in the testing data or you just look in the training data right they do really good at threshold works and they do really shit at vo2 max works i'm going to do vo2 max work first almost irrespective of what else is going on because you know that you know you have to improve that first before you actually go back and improve threshold because it can't move above the max right that's kind of illogical so how you want to do that that's another that's a training architecture question right whether you do zone two work for forever or you do like proper vo2 max work or a combination of those two or whatever we'll leave that conversation uh to the side but if you see that proposition you have a very good indicator arrow for how to shade the training and the opposite is also true if their lactate threshold is way beneath way beneath 70 percent the reason to max or something like that you can push on that button right there and almost get instantaneous improvement within like three weeks like it's a really easy thing to to to kind of turn on once again how you improve that that that physiological range that threshold range is another conversation but you have that and you have that especially with the kind of like dichotomous sports

like ultra running is a very dichotomous sport you're running for like really low intensities for long periods of time and you're not doing a lot of high intensity track cycling might be the polar opposite of that right where you're doing a lot of high intensity stuff and maybe not a lot of big aerobic stuff you can see those physiological profiles uh manifest in those types of athletes whether or not they're meaningful or not right that's the context of the of the uh of that of the athletic uh uh condition um all right let's get into ai man we were talking before this podcast came out and i've been in it for a while you've been in it you've been in it dude you're in the matrix you're definitely in the matrix you took the red is it the red pill or the blue pill that's get you the matrix it's the red pill right the red pill i think it's the red pill so you've been on the red pill for a while um you know we you remember we've had this coaching conversation for a long time that this is coming down the pipeline and coaching has to be ready for this right we have to be ready for it we have to learn how to adopt it where to adopt it where the blind spots are and things like that uh because it's an it's a it's a win not if right and it's kind of here to be honest with you in kind of a kind of a limited capacity backing into an intensity uh construction meaning how you would determine intensity with your athletes can you can you describe what machine learning and artificial

intelligence is actually going to do and how it might assist you and also where it might potentially fail you oh like as an athlete you're saying yeah yeah yeah yeah yeah so with ai um and machine learning is the biggest context is it takes the data that you're producing from your workouts and it's giving you more insight hopefully more descriptive insight but i think i think it's going to give you more prescriptive insight right now initially but it's going to give you more insight onto how you're doing and what your training zones should be those are the those are the biggest things that like garmin trainer road training peaks i mean name them all right they're all trying to and without getting into because i i don't know how all of the in some of this is like um in a black box a little bit you don't totally you don't know the algorithm that's the big problem yeah exactly and that is the problem with most of the stuff out there in my opinion that's the worst it should be it should be open so people do know because the thing is is like if if you are following a process or a pathway or you're using a tool and it breaks and you don't know how it's made yeah yeah you can't fix it then and so then you're following blindly a process that you're just trusting with no kind of basis and that to me

is the first red flag um however if you if you understand how a machine works then you have you can better identify when it's broken yeah it didn't go back and fix it now the thing that's going to help people coaches and athletes with or the the way that ai machine learning is going to help coaches and athletes is to get description more quickly and get better insights right away the problem is that if you get bad data if you have bad data plugged in in the ai and it assumes too much or if it can't identify that something say bad happened like in our world bad data spikes can't scrub the data right can't scrub the data yeah right um or if you or if you did have a really good day and it scrubbed it based on yeah how it thinks and then you lose that data so it is definitely not perfect and in my opinion there's there should still be an intelligent human that's kind of not behind the scenes but like alongside helping to orchestrate and make the decisions on whether you to you know increase your ftp or um individualize the anaerobic portion of your zones or whatever the case may be so i get really excited when like new cool tools like this come out um but there's been some like recent tools that are coming out where people are super stoked about but it's very obscure

an abstract on how they're generating this stuff and to me when people say oh coaches would be out of a job and stuff bring it yeah i don't think so no i mean because we both have been through a few different iterations of the coaches are going to be out of the job right and it still has it you know i'm in my 24th year of coaching and it hasn't come come full circle yeah not to say they couldn't but i don't think it's i think it's going to i actually think it's good for coaching because it makes the better it puts a spotlight on the better coaches and the coaches that are just regurgitating stuff and copy pasting this then then they are are actually obsolete right because the machines have literally taken over what they are doing and unless they raise their skill set there's no value proposition there that that but i digress it's another that's another deal i i mean i think the initial application of this is getting to the answer faster just as you mentioned earlier right we we it takes a we we don't always get it right and we know within reasonable certainty kind of what of our what our level of precision is when we're initially setting these ranges but if we can use some type of machine learning to tell us a how to set the range and ranges initially and or how to adapt them when like over time if we can reduce the amount of time and or effort that it takes to do that that is a huge win i share your concern that i have to know what's underneath the hood and this is the

thing that is eternally frustrating with almost every with almost everything that comes around that tries to get at your readiness or your recovery or you know even should you kind of like run or work out today or what your training ranges should be the description of those is so vague that i can't even tell fundamentally where the intensity anchor point or points are and i would just start with that like tell me you're looking at the power okay great tell me you're looking at the heart rate okay like okay great now i know now i kind of know what we're working with but in any of these cases and i'm going to use um the the one that i sent you earlier uh over text coros is relative pace or sorry effort pace that's the right terminology for effort pace as an example i'm all for like that conceptually right figuring out what your pace should be in an uphill condition and downhill condition and for the listeners out there what what they are attempting to do and i'll leave a link in the show notes to course the chorus's description is to try to equate the pace equivalent in an uphill or a downhill condition to what it would be on the level and that's not unique right we've had great adjusted pace and normalized graded pace normalized graded pace is a slightly different variant and that's not worth to worth it to get into

but great adjusted pace and strava and normalized graded pace and in training peaks for long periods of time their addition to this is the the adaptation over time so somehow they're figuring out how either your economy and or efficiency atoms is different than mine on a 10 grade versus the flat level ground and adjusting this pace algorithm to that to which i'm like great that solves a big problem for me but i still gotta know how it works like what are you using for the anchor is it heart rate is it pace or how are you like machine learning this like i don't need to know the intricacies of the machine learning but i need to know at least a little bit of the little bit of the context in order to find how i'm going to practically use it versus just blindly accepting the intensity because we know what that happens right when we blindly accept the intensity we usually screw it up we've got a good pattern of doing that for sure but i'll answer your question is uh coop has the better efficiency and economy compared to coach ap we could test it well alert we could test it right in the context of running though yeah we could you'd have to run but i mean i'll sign me up man i love testing okay we'll do it i'll buy you a watch i'll buy you a watch we'll go and we'll train underneath we'll do the how would we test this adam we'd each get the same watch we'd assume that we're the same weight right we can plug in the same weight we're about the same weight yeah i was gonna say you're pretty close i'm about 170 no i'm about about 70 now i put

on some muscle man i've been in the gym you see that bro do you get that 400 pound deadlift no i'm getting close man i'm getting i'm i'm behind but i'm gonna finish like i'm i'm not gonna do like 160 160 well after chris we're close we digress yeah too much here's how we tested though here's how we tested we both get the same watch we do the exact same types of running for a month and then we go out and we run on the same you'd have to come to colorado we'd have to go out and run at the same grade at the same speed next to each other and then compare our relative paces and see if they're the same or different and how much different yeah because we see the problem there is if adam does not get injured in the first month of running we just screwed our test we just screwed our test all right that's enough of the digression so there's another form of of machine learning and or ai out there and that's with trainer road so adam this is your this is your wheelhouse why don't you give some context around that and how that could potentially be useful yeah and like kind of my wheelhouse but kind of not and i'll just start with like the caveat of i'm not here to poo poo trainer road at all um like we're talking about like i don't know their algorithm as much i only know what probably you know listeners and consumers know and in the way that it is using your data to generate training zones and ftp and all this kind of stuff however so what we know

is that you can do training and you can do all zone two training or you can do group rides and races whatever has to be on trainer road and the data has to be on trainer road and i think the first 10 workouts actually have to be trainer road workouts particular i didn't know that yeah then you upload some others or other training data and then it generates your zones based on this so again it's not just like do a ride get training zones like it's it's more to yeah yeah yeah there's to be a bulk of data right a bulk of data yeah and that actually that's like a thumbs up yeah on my end because i'm like oh they actually need data to do this okay um but then over time it says that it learns you and it gives you better training zones that more accurately estimate your ftp and all this kind of stuff and and again like i'm all for that especially with uh self-coached athletes or people who are just kind of like getting into this um pretty good way of starting and if it does what it says it's supposed to do which is like it decreases the amount of overestimation and increases the amount of underestimation cool great gives people better training tools however with what i know as an experienced coach i just can see it going so many different ways south when you get bad data when you don't train when you do all these things um and so in the the problem isn't necessarily the tool i think the i think the good thing is the tool the problem is when you overly rely upon that tool and do nothing

else with it you forget about rpe you forget and just be like my machine's gonna tell me it's stupid do you remember that uh that training platform i think it was called burrata is that right where you plugged in your initial ctl your initial chronic training load and then you plugged in what you wanted it to be like however many months down the line six months down the four months down line or whatever and then it built the ctl ramp for you with all like the like the micro cycles and things like that i remember there was a so so basically the fundamental thing is is you plugged in the end points right the beginning end point and the end end point of this is where the athlete is at from a chronic training load and acute training loads perspective and for the listeners those are just training peaks metrics that describe either your law your uh long your chronic training load your 42 day training load and or that's the ctl and or your short day training load that's your atl you kind of describe those end points those training load end points i'm emphasizing those words intentionally you describe those training load end points and it draws the map in between them like how those things should ebb and flow throughout the the the entirety of of of the process to which there was a group of coaches that went berserk over it like oh my god this is the greatest thing since sliced bread and i just looked at everybody and i said listen you're assuming that everybody adapts

across all intensities at the exact same rate and you know that that is not true like yes you can make generalizations on low intensity takes longer to adapt and high intensity takes shorter shorter times frame to adapt and the inverse is true on the fatigue side low intensity takes longer periods of time to generate fatigue and high intensity takes shorter uh amounts of time to generate fatigue but to apply that like universally is was just like completely like completely absurd so it kind of gets back to this right like you can use these tools to become more efficient but there still has to be some sort of checks and balances on what what is what is ultimately going into it yeah exactly and i do remember that now i was into it for like i was stoked for like a day and then i built all the things i'm like cool and then i'm like wait a minute wait a minute but but we still do that and there's still actually a lot of coaches that are stoked about that because there's actually there's functions within training peaks where you can do that and yeah yeah so whatever um i think it's like i will still say that some of that modeling is helpful because especially with younger coaches to see where like a build can go cool but like the reality is it's that's not it's not linear it's not you know perfect right and so that's where the kind of the art of coaching and stuff will always happen to the athlete they'll get sick they'll do this and all that kind of stuff and i haven't seen an ar but the peaker's ar was was another one that's an interesting one i don't know if you saw that coop but i played around with it for a few months actually you input data and you actually had you got to chat with a bot so you had like a

text message search like yeah it like every time you did a workout it was like how'd you feel today you like you know pretended like it was a real person and like texted back and they would have like you know four or five questions after every workout and it would input it in and then it would supposedly do different calculations of what to do the next day based on your inputs on that oh it's this is a deliberate if then program yeah exactly so we built that i built that and like were you did we work together at this time this was like 2005 or 2006 this might have been like slightly before your time so i started in 05 i personally i i personally built this with our software engineers this is a long digression for those of you that are still listening to the podcast you will this this story is actually kind of good for you yeah good for you good for you but this is going to be a little bit of a digression so part of our command was to increase our amount of leverage that our coaches had right so how many athletes could we put underneath one coach and there's kind of three main points that you can that you can apply leverage to it's how you communicate with the athlete right you send them 10 phone calls or one text message or two emails and things like that you can have more leverage if those communication points are kind of more streamlined how do you prescribe the training right so actually putting in i want you to do this workout on tuesday this workout on thursday and there's a lot of different ways that you can achieve leverage that way you can have pre-built

programs and then modify them you can go to an all static model and have thousands of athletes underneath the kind of the same like coach should uh uh so to speak and then there's the the training evaluation piece right how do you look at the data and then interpret what that means for kind of future inner fruit future iterations is that what we that's what we've been talking about right with machine learning and ai the probably the primary leverage point is looking at the data that's coming across the wire and helping the coach make sense of it either in a more accurate way a more effective way or a way that grants them greater leverage kind of coming back to the business side of things they can coach more more athletes a bigger volume of athletes because it's taken the the the the previous labor constraint away to a large or or all of the extent so anyway the point of the story is is one of my charges was to work with our software engineers and figure out a way to get more leverage out of our coaches and the way that we decided to do this was this really elaborate if then program on based on the inputs which are kind of did you do your workout what to what extent did you do it did you hit the ranges that you were supposed to hit and essentially like how compliant you were and how you felt about it so we took all of those variables in there's probably about 50 of them and then we decided how to keep or change the static program that was then assigned on the next month

but it was all it wasn't even ai it was just if then logic i'm not trying to like overplay it or or anything like that but it was the same philosophy of like here's all the things that are going on let's try to automate it in some way and then kick out the program automatically and then you have a coach really quickly review it and say yeah this or no we're going to shift tuesday by this amount or or whatever but that plight is not indifferent to this current iteration where machines are doing all of that like we have tried to we've tried to do that for a number of different end goals for for for years and i just happen to be involved in one of them the end of that story is is we decided it was shit and we shut the program down because we couldn't get it right like we couldn't get it right we looked at it as coaches and just said we just can't get it close like we just can't get it close to the prescription that's 15 years ago right more than 15 years ago technology is better now we might be able to get it right but the same pattern is going to continue to exist where we're going to have to figure it out see if we get it right and then iterate from there well i think it's also important to know and this is like i try to make this as practical as possible but like humans are not that perfect where they are predictable yeah yeah like like they're always in flux physiologically and emotionally therefore i don't think ai will work to train us without a human being involved yeah yeah i mean the ai people

will say that well the machines will eventually be able to figure out even the human component right that human variability component but a lot of that work is you know john kiley and uh like his his colleagues that you know that will take this stance and i i agree with a lot of this is that we are not linear nor predictable adaptive creatures right just because you apply a stimulus don't think that you can uh in a replicable way predict how that stimulus is actually going to affect a particular athlete because there are so many other complex variables kind of going into it you try to get it close and i think that you know one of my greatest growths is a is a coach is realizing just how close or far away we can get that predictive model right you can try to get it as close as possible but still there are all these other variables that you can't take into into into consideration oh yeah that's it all right let's wrap it up my friend so intensity you've got your general architecture of you initially do a big data dump you can get you can kind of rough in the intensity from there you may or may not apply some type of maximal testing across durations to further refine the intensity i think the last thing before we go is how do you what are your triggers to modify it

so you're working with an athlete for three months six months three years it's five years right you've been working with athletes for over a decade single athlete for over a decade take the listeners through the modification process um well first i think it's important to recognize that again because because an athlete trains up and detrains throughout a year you want to try to stay ahead of that based on the goals that the athlete has because sometimes it is detrained you want them to detrain right so then you got to adjust the intensity down before we go back i want everybody to listen to that you want them to detrain for sure yeah and again like you and i have done podcasts on this um and it is a very good thing to do anyway but that said like once you do have a period of detraining do not go back and chase your old zones bring them down a little bit and you can even say bring them down five percent if you've had a detraining period of three four weeks or something like that and that's probably pretty applicable which you can do you can use some of these tools and a hinge point of ftp and based off that but to your point as you train and develop more how i adjust probably the best way i can look at it is um to kind of see this opens up a can of worms do it won't get into but do it no do it to see how durable they go over a workout and that

workout can be short or long and we can get into this because i've got a i know you just did a podcast on it i've got a lot of thoughts on durability but durability can be a number of different things but it's essentially how they hold up over time based on what you want the athlete to do and if they're not holding up well based on the zones that you prescribed i'm going to bring them down if they hold up really well i may adjust them but the other thing that we really haven't even talked about too this is like the fact of how much well you kind of touched on a little bit but like lower intensity training it takes more say time and zone to get the adaptation versus the higher end so just because i do a four by 12 tempo workout doesn't mean that you know one week we may do it the next week just because we're trying to accumulate time in zone three as we go right and i'm not going to change any zone just because you crushed the tempo workout right could have just been stoked with a good playlist and has some caffeine so it's interesting that you mentioned that right because i think everybody's first uh thought when they when they think about when am i range is going to change they go to the adaptive side of it like when am i going to get better so i can produce a higher power output or i can run at a faster speed for this for the same workout but you're almost kind of saying the opposite it's like if you give somebody workout and you can kind of see them getting to a failure point early that's one of your leading indicators to like make sure that the intensity range is sustainable over the course of the entire set so you can add more volume right i mean that would be your that would be your end goal is just to tack on more volume at a similar intensity yeah that's right

because i think the the more the longer i coached the more i realized how wrong it was early on because because i was probably too manipulated by my own athletes they wanted to push more power right and i was like let's do that right um but it's kind of the opposite so a little bit slower more time in zone adapt to because that longer term because in in i think in your field it's very similar with ultras like my gravel people my mountain bike man we can talk all about this because um that durability for ultra stuff is very necessary i think that we're we're starting to figure out in some research how to actually quantify it i know how i do it it's not perfect but i've got my own ways use a kilojoule model like kilojoule model 3 000 kilojoules and something like that yeah yeah yeah um pretty pretty much because again a lot of the testing stuff that we talked about that's i call it open or fresh yeah i do a kilojoule where i'm looking at five or twenty after a certain amount of kilojoules for masters athletes and kind of women 1500 kilojoules longer 2000 okay and i think you probably yeah we talked about that yeah okay um but then there's other stuff of just uh repeatability yeah over time because if you're talking about mountain bike racers criterion racers how many times can you do 400 watts or whatever the whatever you need to do in the race say you need to do a certain power output how many times can you do it because it's not absolutes it's relatives yeah okay here's here's what the listeners can really take a home take away from

this take home with this god dang it's late in the day man it's it's time for me it's still mountain time brother um time it time and intensity is normally a bigger hammer than more intensity more time and intensity is a bigger performance hammer a bigger adaptive hammer than more intensity at the same time and that's just the nature of endurance sports i'm not saying that is universal across every type of adaptation that you want to get there's certain like caveats to that at the upper ends of the intensity especially in cycling right we're talking about 5 10 15 20 seconds of of the power duration curve that's not applicable and a lot of other endurance sports but when you're generally looking at the adaptive process for most endurance athletes time and intensity is going to be the big hammer and when the athletes out there that are thinking about either designing their own training ranges or the coaches out there that are thinking about designing training ranges for their athletes you're far better off undershooting and just assigning more time and intensity than overshooting and having the failure because you're missing out on part of the adaptation that comes from the stimulus of just getting it close like that's kind of thing like get the intensity close and get as much time underneath that stimulus as possible yeah that's that's where i was going with it and you said it much more uh articulately because i'm older than you and i'm in mountain time zone you look older than that's right for sure yeah adam thanks my man thanks for coming on the podcast again i appreciate it this

is a great kickoff for the year like i said earlier we're gonna have podcasts with our fantastic colleague grenade eastman and several more that are going to like kick athletes seasons off because everybody's now they're they're kind of like what do i do i know i need to train they have the oh shit moment right i got into this race i know i need to train where am i gonna where am i gonna start this is a good kickoff for it with the intensity so i appreciate your time my brother yeah thanks for having me on and i hope it uh hope it helps your listeners all right folks there you have it there you go much thanks to adam for coming on the podcast today i think i hope you guys peeled away a few nuggets of wisdom for that here is what i was reminded of and i think is important to come away with when we are looking at this incredibly important aspect of intensity first off realize that when you are designing your own intensity getting the time duration correct and trying to spend as much time as possible at any intensity is far more important than the precision of the intensity all workouts are valuable we pick on a lot of the recent uh a lot of the recent pop culture fixations of zone two training but the fact of the matter is is that all intensities are important yes some are more important than others but in the endurance realm the thing that drives the majority of the adaptation is the time that you spend underneath the intensity not necessarily the

intensity itself so keep that in mind the second thing to keep in mind is as you are calibrating that out there you can absolutely do so using rating of perceived exertion even if you are a cyclist as adam mentioned even if you have the most precise way to measure intensity out there which is a cycling power meter and it absolutely revolutionized the sport in the early 2000s even when you have that tool you can absolutely use rating of perceived exertion extremely effectively to determine what intensity you need to be at and one of the best ways to do that is to go out and do a 10 out of 10 workout go and do 20 minutes as hard as you can do go do a workout like six by three minutes hard three minutes easy to its maximum use that as your 10 calibration point and however you determine how you want to calibrate underneath that nine eight seven six five four three you'll learn the most if you just go to 10 first and foremost that is an absolutely huge part of the entire equation the third part is is if you are using any of the automated ways to determine intensity whether that's functional threshold pace functional threshold power or functional threshold heart rate that is useful within training peaks is app or any of these other associated apps or you happen to use a field test or even physiological testing you still need to validate those precise intensities out in the field with

actual workouts you need to take that information and say does it actually make sense for me to do the work that i need to do at that intense at this intensity and can i handle the duration that i should be able to handle according to those tests even the most precise ones require field validation in order to make them valid those are the three hero points i hope you guys learned that that as well as any of the associated banter that adam and i happen to have throughout this podcast one more uh moment of thanks here i put out last week that i am making some alterations to the format of this podcast i'm making it a little bit longer i'm adding a little bit more depth to it that's some of the commentary that i just gave you guys right now and i'm also trying to organize it in a more effective fashion to kind of play off similar themes throughout the course of the year i also provided some color commentary within the uh within the content space in general i have been absolutely overwhelmed by the positive response that i have received from you the listenership so thank you very much and if anything that is going to give me fuel to double down on this philosophy of providing insightful accurate scientific content that you can take into your training day to day i'm extremely humbled by it thank you thank you thank you very much that is it for today folks i appreciate the heck out of each and every one of you and as always we will

see you out on the trails you