Micro-Periodization Strategies with Luca Filipas, PhD #230

Luca Filipas is a coach, researcher and exercise physiologist based out of Milan Italy. He is the coach of TotalEnergies Pro Cycling Team, Owner and Coach of Endurance Academy and Researcher at the University of Milan.

Paper discussed-Beyond the classical periodization: the new frontier of micro-periodization for endurance disciplines

Previous podcast with Luca

The use case for HRV in ultrarunning with Marco Altini

Additional resources:
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Episode Transcript

Speaker 1 (00:07):
Trail and ultra runners.
What is going on?
Welcome to another episode ofthe coop cast.
As always, I am your humblehost, coach jason coop, and this
episode of the podcast is withrepeat offender luca felipas,
who's coming to us all the wayfrom Milan, italy.
Luca is also a coach of theTotal Energies pro cycling team.

(00:28):
He is the owner and coach ofEndurance Academy over there in
Italy and he is a researcher atthe University of Milan, and I
wanted to bring Luca on thepodcast today to discuss an
editorial that he recently wrotein the Journal of Sports
Medicine and Physical Fitnesstitled Beyond the Classical
Periodization the New Frontierof Micro Periodization.

(00:51):
For Endurance Disciplines, howone periodizes their training
has been a subject of debate andconsternation and a lot of
dialogue in the coaching and theathletic community.
Do we use some of theseclassical periodization models,
such as linear periodization orblock periodization, what works
best depending upon thesituation that is in front of

(01:13):
you, and what works best forparticular sports?
Well, luca has described veryeloquently in this really simple
paper that I will link up inthe show notes, a new feature
that we are starting to seeemerge within particularly the
elite endurance athletes, wherethey are using a more
individualized, periodizedapproach to determine when

(01:33):
they're going hard, when they'regoing long and when they
shouldn't be doing either ofthose and going easy.
That is the subject of today'sdiscussion.
We bring in both of ourpersonal coaching anecdotes to
this as well to try tocontextualize some of the topics
that we discuss, all revolvingaround periodization.
All right, folks, with that outof the way, I am getting right

(01:56):
out of the way.
Here's my conversation with LucaFilippos, all about micro
periodization.
So, luca, welcome back.
I appreciate you taking timeout of your busy schedule in the
middle of the season, middle ofthe cycling season, middle of,
I'm sure, athletes and teams andthings like that running around
to talk about this.
It's also interesting timingbecause normally when we talk

(02:19):
about periodization, the middleof the racing season is probably
the worst time to talk about it, because all the training is
kind of transpired.
But nonetheless, we're going totalk about a really cool area
here and, as you and I weretalking offline, this is
something that athletes andcoaches are trending more and
more towards.

Speaker 2 (02:36):
Yeah, Thank you.
Thank you for the invitation.
It's a pleasure to come backhere and, yeah, probably not the
best moment, but yeah, forathletes or for coaches that are
listening, I think it could bea perspective for the next
season.
I hope so.

Speaker 1 (02:52):
Exactly, exactly, make you think about everything
that you probably did wrong thisseason and how you're going to
set up next season correctly.
So with that as a little bit ofa caveat, you know we're going
to talk about.
I can see this unfolding on twodifferent fronts One where
we're at, within this current,what you and I have been calling
a trend of what you'vedescribed as micro periodization

(03:15):
, and whether or not thatdefinition or not holds.
You can take credit for it, Iguess, or take some credit for
it.
But then also the landscape ofhow we design training as a
whole, given the fact that wehave more into, a lesser extent,

(03:35):
better I was being very carefulthere we have more into a
lesser extent, better, insightsinto how the athletes can
perform on a day and how wellthey're recovered and how ready
they are and things like that.
I think that this will take onboth of those themes.
But to kind of take a step back, a lot of athletes are used to
hearing the word periodization.
A lot of coaches are used tohearing the word periodization.

(03:57):
Let's kind of describe, likewhat that means and how you view
it through your lens, and thenthe different kind of like
flavors of periodizations thathave emerged over the years.

Speaker 2 (04:07):
Yeah, basically, periodization is a way where you
can guide your training througha season.
There are a couple of reallywell known type of periods.
The most common type ofperiodization are linear
periodization and blockperiodization.

(04:28):
Linear periodization isbasically a way of dividing the
season in some periods, somecycles of training, where you
have some weeks high loads andweeks of lower loads.
The duration of each cycledepends on goals and so on.

(04:50):
But basically doing aperiodization implies that you
go up with the intensity throughthe periodization and then to
go a little bit down with thevolume to the periodization just
till you arrive to the goal ofseason.
And block position is a littlebit different because you

(05:10):
divided the season as well insome cycles.
But I call blocks because onthat block you can put all the
some specific workouts that youwant to develop.
On that specific block.
I mean, there are somehigh-intensity blocks where you

(05:32):
put all the high-intensityworkouts, maybe within a week,
and then the following week youdon't do any high-intensity
workouts, whereas in the linearperiodization it's like more
equally distributed through thecycle, the high intensity and
the low intensity exercise.

(05:53):
So basically this is thedifference between linear and
blocks.
So in one case you have, yeah,tendency to increase.
Linear periodization tend toincrease intensity through the
season, going down a little bitwith volume, but the
distribution of the highintensity and low intensity
training are almost equallydistributed through the entire

(06:18):
cycles.
On the contrary, with blockperiodization you have specific
micro cycles that are onespecific qualities that you want
to develop, or like somespecific intensity that you want
targets for that block.

Speaker 1 (06:35):
Coaches and athletes and physiologists have kind of
had this.
It's not a pedantic debate, butit gets too nuanced in my
estimation.
You and I are kind of grinningright now because you know you
probably know where I'm going totake this, about which one of
these is better and you knowwhich produces this more
superior physiologicaladaptations, or which is better
for certain types of races andthings like that.

(06:57):
And I think another way to kindof encapsulate the differences
that you are trying to describestructurally, like how the
volume and intensity flowsbetween those two types of
periodized models, is I'd liketo kind of view it from a
philosophical standpoint, interms of what the practitioner
or what the coach is trying toaccomplish kind of at the level

(07:20):
of physiology.
And in a linear periodizationmodel, your kind of working
assumption is that things arebuilding off of each other, that
you do something first and thatgives you a greater capacity to
do the next step, and then theydo the next step, and then that
gives you a greater capacity todo the third step.
And the way that naturally kindof emanates is, as you

(07:43):
mentioned, the intensitygenerally goes up as the season
goes along and the volumetypically goes down.
I'm going to use a word that alot of really high quality
coaches are going to cringe at,but I think a lot of people
identify.
It is that the quote unquotesystems build on one another,
that you're building thispyramid, so to speak, where you

(08:04):
have to have a big aerobic baseand then you build something on
top of that base and then youbuild something on top of that
and you contrast that with thephilosophy behind a block style
periodization and your workingassumption.
There is you need a certainamount of stress to produce an
adaptation.
A lot of high-end athletes willgravitate more towards a block

(08:27):
style periodization becausethey've just been training for
so long and they're just so goodand they need that amount of
stimulus in order to improve.
These things don't exist inisolation.
You can have a Venn diagram,overlap of kind of both, but
from a philosophical level, whenI look at those two, that's
what I have kind of come toreconcile in terms of the

(08:50):
differences of them.
Yes, I understand thestructural part, but I kind of
look at it more from a what areyou assuming is going on at kind
of the level of physiology, andthen you can choose to deploy
more of flavor A or less offlavor B or some kind of
combination of it, or we'regoing to talk about flavor c in
a little bit, but you can chooseto do that just based on the

(09:12):
situation and the athlete that'sin front of you.
If you know what's going onunderneath the hood, so to speak
yeah I totally agree with that,with your explanation, I think
it's.

Speaker 2 (09:21):
it's basically what is the reality in terms of two
different periodization.
It's almost impossible to haveone and not having the other at
all.
I assume, as you say, that manyhigh-level athletes are doing
right now some sort of bloodperiodization, but not extreme
periodization, like probably allthe entire work hours at that

(09:46):
specific goal in like one metrocycle, but the sort of mix of
the two different periodization.
But yeah, from the, especiallyfrom the high level athletes,
it's interesting too.
Too, I know you have mentionedsome other episodes.
There are one interesting studyon Marit Bjørgen on
periodization, on Marit Björgen.

(10:06):
That was on her most successfulseason of her career and this
study may show that basicallyboth kinds of positions were
good for her.
She needs when she moved toBlackbridge she won was one of
the most successful season ofher career and basically also

(10:30):
they mentioned that also notonly for physiological
perspective they moved to bloodtransition but also for mental
changes to their routine.
So I think for high levelathletes, something where you
are at the top of the tier youneed something different,
sometimes not onlyphysiologically but also

(10:53):
mentally, to develop somethingmore and change something in
your routine, to be even higheron your performances.

Speaker 1 (11:02):
I referenced that study in a presentation I gave
just a couple weeks ago.
I'm pronounced to you, luca,and I've probably sent that
study out.
It's not a new one.
It's been around for a while.
Just recently, for whateverreason, I've sent that study out
to about I don't know five oreight of our coaches.
Just as a point of, just as apoint of discussion.
I will link it up in the shownotes.
It's a great study.

(11:23):
Your point on novelty is reallywell taken, because at the kind
of the most elite level they'vebeen training for so long that
sometimes if you just change thestimulus to anything, you'll
see an adaptation becausethey've been training for so
long.
And the novelty is, it's notthat it's a secret or anything
like that, or it's not thatyou've unlocked some special

(11:45):
sauce, it's just that thestimulus is novel and that leap
in performance is normallyattributed to the change.
And there's, you know, I thinkthat's a worthy assumption to

(12:13):
take when, whenever, that's thetake, whenever that's the case.
That happened in the Tour deFrance this year and there was a
lot of, there was a lot ofdialogue.
There was a lot of dialoguearound that.
But sometimes we have to take astep back and say there's a lot
of dialogue around that, butsometimes we have to take a step
back and say, well, is it bothdifferent and a better stimulus
that's creating this adaptation,or is it different, or is it

(12:33):
singularly different and orbetter, and that's a whole, you
know debate to kind of like uh,to to kind of weed out.
But nonetheless, I'm notsitting here and I think you and
I'll take a really pragmaticapproach to say any one of these
approaches are definitelysuperiorly better for every
single use case, but we need tolook at them as tools in our

(12:56):
toolkit that we can deploydepending upon the athlete
that's in front of us.

Speaker 2 (13:00):
Yeah, that's basically what we need to do as
a coach.
So we need to understand theathletes we have in front and, I
think, also understand what theathletes have done in the past
to understand what physiologyneeds to change for improving
their adaptation.
So we basically, as coaches, welook a lot at the data of the

(13:23):
previous year to understand whatare the yeah, the key stimulus
and the key periodization toarrive and to elicit some, also
some other marginal gain thatprobably some high-level outlets
have, just for like a smallpart of their physiology.
So, yeah, basically I thinkthere are no right to respond if

(13:48):
it's better one of the other,but yeah, it's better to the
best physicians, the best forthat outlets.
So is there the one thatdeveloped the physiology of the
happiness?
So it's not a, it's not a.
You cannot say I do blocktransition, I'm going, I'm doing
rare, I'm doing linearperiodization, doing rare.
But it depends on what you aretrying to do and what are your

(14:13):
goals and, of course, mainly andmainly what I have done in the
past.

Speaker 1 (14:19):
Yeah, well, okay, so we're going to stick on what you
have done in the past before wego on to microprioritization.
I told you we would go off therails with this pretty quickly.
This is a big point of emphasisthat I always bring up with our
coaches whenever they get newathletes, and especially when
they get new athletes with arobust training history that is
described and well encapsulated.

(14:39):
And that is not always the case.
Sometimes, even at the veryelite level, you get athletes
who it's hard to decipher whatthey have actually done in the
past.
It's hard to figure out whattheir previous training has
actually looked like.
But when you have that, it'ssuch an incredibly powerful tool
to look at that through thelens of what has worked and what

(15:00):
has not worked, and you canreally bifurcate it that simply
and look at training in the pastand say, okay, well, when this
training was going on, you wereperforming really well.
When this training was going on, you weren't performing well.
And what is missing?
Are there components oftraining that are missing?
Is there a period of highintensity that is missing?
Is there even a modalitycross-training, modality,

(15:23):
straight training or somethinglike that that is either missing
or, I would actually say beingoveremphasized.
Sometimes, taking those reallybig picture themes from previous
training and not doing anythingdifferent from an annual
training volume perspective,just rearranging some of those
pieces is an incredibly powerfulthing and can actually make you

(15:44):
look like as a coach.
It can kind of make you looklike a genius, because you're
literally getting more out ofthe same out of the same amount
of work by looking at it throughthis context of a really big
picture four, five, three,three-year lens, four-year lens,
five-year lens, six-year lensand trying to pick out the
patterns, that kind of can thatyou can then leverage to gain

(16:06):
things in the future yeah, Itotally agree on that,
especially because there's somany coaches that don't do that
and they just start withtraining immediately after the
coach arrived, the athletesarrived to, to their laboratory,
their training and they juststart coaching.

Speaker 2 (16:24):
The atlas as a new one, but probably this atlas has
a long history and you can just, if you're just checking your,
just checking his past trainingprograms and training history
just one year, two year andthree years to go, and then you
can understand immediately okay,I have to go in this direction,

(16:47):
because they are developingtheir entire career doing
polyvolume, no high intensity orthe opposite, just high
intensity, not just really lowtraining volume and you can
understand many things about it.
I think it's a big part in mytraining approach.
So it takes a lot of time forme to analyze that and also I

(17:12):
think for the athletes and forthe coaches it can continuously
come back and check becausesometimes you didn't see
something and you can see itafter because of course you are
human.
So as a coach you cannot seeeverything, maybe analyzing it

(17:36):
in details, or it takes a whileto understand sometimes some
training patterns in the pastthat could have led to some
specific good adaptation or somespecific bad adaptation and you
can see maybe after two orthree months.
So I try to continue thisanalysis in the past, even if I

(17:56):
have already started coachingwith someone.

Speaker 1 (18:00):
To give the listeners a little bit of perspective on
that, because you and I arepractitioners and I think that a
lot of times what we do getscut and maybe necessarily so
gets lost in the weeds.
It takes me about six or eighthours to go through an athlete's
previous training history whenI first start working with them.
Just as kind of a go forward,because when you're prescribing

(18:23):
training you're looking at sucha short time.
When you're initiallyprescribing training you can
kind of look at a shorttimeframe and just propagate
that in the future to kind ofbide your time.
But when I'm doing a reallyrobust review of training
history with a new athlete thathas, say, three or four years or
even greater of training behindthem, that's well encapsulated,

(18:45):
it's well, it's well documented.
The training notes that arearticulated by the athlete and
also if they were underneath aprevious coach or whatever.
That process takes me a longtime.
Six, eight, maybe even 10 hoursif it's a whole, if it's a
whole lot of data.
But it is absolutely 100% worthit to do that and at the end of

(19:06):
the day, at the end of all ofthat, that time suck.
That I've been, you know thatI've been drawn into.
I kind of come away with thethemes that you have just
mentioned.
When was athlete trainingreally good?
When were they training reallybad?
What has been overemphasizedand what has been
underemphasized, those thatthose kind of like polarized
themes are the.
Those are usually thehighlights in the notes that I

(19:29):
have.
I'll create three or four pagesof notes, but the things that
kind of come to the top are thereally like obvious ones and
sometimes aiming training withthose kind of big picture themes
in mind.
It's like the easiest thingthat you can do year one to get
improvement out of an athletethat has a really robust
training history.
So, needless to say, my pointwith all that is is, if you're

(19:52):
looking for ways to improve andyou have been training for a
long period of time, look at thepast.
It's a really neat window intohow you can improve, how you can
improve going down the lineDefinitely.

Speaker 2 (20:03):
Definitely.
I totally agree with that and I, as you said, I spent a lot of
time on that, I know.
So you can do it from differentperspectives overall annual
data.
You can do monthly, weekly,daily, so that takes time.
So, yeah, it's alwaysunderestimated by athletes and

(20:25):
also I saw some coaches thatdon't do that.
I think because they have theirI don't know how to say it in
English they have their magic,they have their magic touch for
the athletes and they starttraining without knowing
anything about the athletes.
So I prefer to spend some timechecking.

(20:46):
I can start as well immediatelywith training with some base
training.

Speaker 1 (21:09):
And then I will adjust my training as you say,
going down in the pot andchecking what was wrong, what
was okay and I think that thisis true in a lot of endurance
sports coaches who have foundsuccess with one or two or three
athletes.
They will use that same or asimilar blueprint with a larger
cohort of athletes as they startto build their business out and

(21:29):
kind of capture new athletes,and they immediately go to the
thing that has worked with otherpeople because they're familiar
with it.
They can usually articulate itvery well, which actually is a
really important point, becausethey've done it over and over.
They're usually have some sortof clever way of describing why
they are doing what they werewhat they are doing actually

(21:51):
works and then, unbeknownst tothe athlete, just start
propagating that training ontothat athlete without much of a
robust history.
That actually happens a lothere in the US and I mean I'm
just as guilty of it as anybodyelse, especially early on in my
coaching career.
That's why I always take a stepback and before I get too hot
and heavy with the trainingprescription is, I just try to

(22:13):
gather as much data as possible,if it's, if they're okay.
So we're going to talk aboutmicro periodization.
Should I give you credit forthis term, or did you come up
with?
Did somebody this?
Does somebody else deserve alittle bit of credit for this?
Why don't you walk through thehistory of the, the paper that
I'll link up in the show notes,and then what you're describing
in it?

Speaker 2 (22:32):
I think the micro periodizationization has been
used in different situations, Ithink not only in endurance
sports.
I'm describing it like a moreshort-term pilotization.
So I don't know if I'm takingsome credit about that, but yeah
, for sure I think that it's agood way of thinking the

(22:54):
transition process.
So I don't think that this typeof determination will remain
under my name, but it's for sure.
I think it's good for thecoaches and for the practitioner
to understand which level thisdetermination is.

Speaker 1 (23:14):
And it's an interesting one of the things
that there's a few things thatkind of like caught my eye with
it.
The first one is we normallythink about periodized
approaches with a long term lens.
So I have 12 or even maybe 36months of training, with
Olympics are happening right nowas we're recording this.

(23:36):
I have four years right, 48months to get an athlete ready
for the Olympic games.
How am I going to organize thenext four years and use a
periodized approach to get thatperson ready for the summer
Olympic games in 2028, right,the?
When we think aboutperiodization, it's usually that
long of a timeframe this is thename implies micro kind of

(23:58):
turns it on its head.
Right, we're not thinking somuch long term.
You can always have that in thebackground, but we're really
using things that are kind ofright in front of us in order to
organize the architecturewithin a day or a week or kind
of a shorter term time frame.
That's one of the things thatwas kind of fascinating for me
to think about and I wanted toget your thoughts on what, like

(24:21):
what is enabling that right now?
Because we do have the capacityto look at things kind of
almost in real time.
I wake up every morning and Ihave kind of a standard workflow
for my athletes to eitherchange what I've prescribed
which happens a lot or kind ofstay the course.
What has transpired in the pastseveral years that makes this
just even pragmatic to do in thefirst place?

Speaker 2 (24:45):
Yeah, I think with the modern technology we are
basically having more data andmore possibility to extract the
studies, the biological studies,the athletes, so we can
understand in a way better thanin the past at which point of
this adaptation process theathlete sees If it's in a weak

(25:06):
stress situation, if it's in agood situation for adaptation or
if it's a really stressfulsituation and we cannot stress
the others anymore because it isgoing in an overreaching
situation or an over-trainingsituation.
And basically I think in thepast the problem was that we

(25:29):
started from thesupercompensation process and
supercomp pattern.
That means that when you, whenyou like, stress an athlete with
the trainee, you expect aresponse and then it's, it's
normal and and then you adaptfrom the stress positive,

(25:52):
positively after the recovery.
And basically in the past thisprocess that is like
physiological process where youput a stimulus to an outlet and
then for having some adaptationyou need time to recover from
that stimulus.
Basically the problem was thatwe cannot track exactly the

(26:16):
stress of the athlete during thelight supercompensation process
.
So you cannot exactly say, okay,the athlete is ready to do a
high-intensity workout, theathlete is really stressed, so
the athletes are in recoverybecause we didn't have some

(26:37):
really high, specific, reallyspecific tools for tracking,
like these stressors.
So basically the point was thatwe in the past we did like two,
three weeks of like normaltraining, high loads, and then
we basically need one week oftapering because we to make sure

(26:59):
that the athletes recover fromthis stress, because we in the
past we were not sure about this.
This, uh, is biological statusevery day and so to make sure
not to go in an overreachingovertraining situation, we kept
some tapering weeks to make surethat everything goes well, the

(27:23):
athletes recover and we can goahead with another step in the
pyramid, as you say.
But now we are in a differentperiod of technology so we can
track some important metricsfrom the athletes and, of course
, we are not in the body, so wedon't understand exactly where
the athletes are because we arenot there and see the

(27:45):
mitochondria, muscle or level,what's happening right now.
But we can understand what fromdifferent metrics, what the
situation globally of theathletes at that moment.
So basically, this kind ofapproach allows you to
understand when the athlete ismore ready in terms of

(28:09):
biological stimulus, to be readyfor adaptation, ready for good
adaptation and not ready for badadaptation.

Speaker 1 (28:17):
Luca, what you're describing is something.
I've actually tried toarticulate this in presentations
that I've given on trainingstructure.
As coaches, we're always tryingto make educated guesses around
a few fundamental pieces.
How much acute load can theathlete handle?
So that would be like in atraining session, one single

(28:39):
training session.
Can they handle a five hour runor ride?
Can they handle one hour worthof intervals, whatever you're
trying to put in front of theathlete, how much load they can
handle?
That's an educated guess.
Use a lot of differentcomponents to determine to or to
, to to make that educated guess.
But let's be frank, you justmentioned we can't look inside
of the body.

(28:59):
We're making an educated guesson how capable or how much
capacity all of those differentthings have in order to handle
the workload that we prescribethem as coaches.
The second thing we're makingan educated guess on is how
frequently and how long to applythat load for before taking a
recovery period.
And most coaches and athletesdefault to this very

(29:22):
prototypical pattern that hasdecades worth of legacy behind
it, where they go three weekshard in one week easy, roughly
three weeks hard in one week,one week easy.
And the interesting thing aboutthat is if you ask yourself
well, why is it three weeksright?
Why is it not six weeks or twoweeks or one week, or 17 days
and four days off?

(29:43):
You know, 17 days hard and fourdays off, like, why is it three
weeks in one week?
A lot of that legacy actuallyhas to do with doping and it it
it started, it started to getpropagated kind of in the old
Soviet and East German trainingstyles for all sports, not just
endurance sports, andparticularly around the women's
menstrual cycle, because theywould show the most adaptation

(30:06):
to a lot of that era's dopingprotocols.
And it just happened to be,they would dope them up with
male hormones revolving aroundtheir menstrual cycles, which is
roughly three weeks on and oneweek off.
And so we have this entirelegacy of periodization based on
not entirely based off of, butwith a large influence off of

(30:26):
this kind of like false premisethat you can actually kind of do
that with an athlete.
And so whenever I see these newmodels and describe well, it
doesn't have to be three weekshard in one week, easy, right,
which falls.
It also happens to fall into aprototypical month, but it
doesn't have to be that, becauseyour physiology isn't kind of
neatly organized around this onething it's been manipulated to

(30:50):
have this legacy that we nowlike look on with the hindsight
of a few decades and we need tothink about it a little bit
differently.
So your point of is now we'dhave some tools and we're not
going to.
We're not going to adjudicateall of the tools.
I've done that in previouspodcasts with Marco and um, our
girl teeny, who I'm sure you'refamiliar with, and other people

(31:10):
in terms of what can we, whatdata is worth extracting and
what type of situation.
And mainly we're talking aboutthe wearables.
So the things that we can getfrom our watch or power meter,
things that we can take uponwaking whether it's heart rate
variability or whoop strap or aring, and things like that,
harnessing that data and usingthat to influence this cycle of

(31:31):
I'm going to go hard, and howlong am I going to go hard for,
and then I'm going to go easy,and how long am I going to go
hard for, and then I'm going togo easy and how long am I going
going easy for?
That's fundamentally whatyou're talking about when you're
kind of describing this microperiodization model is you're
using things that we can thendeploy to determine this hard
easy cycle that doesn't have tonecessarily default to three
weeks hard, one week easy yeah,basically we can have some

(31:53):
really high level metrics, bothin training, coming from
training, and both when we arein the college in the morning
after the training or before thetraining.

Speaker 2 (32:07):
So basically in training I think some things
that are really worth looking atis HR response to some maximal
exercise, so this one is a goodmetric to track your stress.
Sometimes I usually do thatlike some maximal step in the

(32:27):
warmup routine of my athletes tounderstand if they are ready or
they are high on or they are.
Or they are high on or they are, yeah, like over stress, or
they are fine for the session,and sometimes I prescribe some
different workout based on whathappens on that.
That's a maximal test.
So sometimes I saw that theheart rate is in the range that

(32:50):
I want.
So, yeah, from that outlet it'sme.
Every metric that I'm playingis highly individual, so I
cannot say that range is goodfor you and for everyone, but I
usually try to have some rangesfor each outlet.
I estimate that the recovery isgood based on the
power-arthritis relationship andif the athletes fit in that

(33:14):
range, range I, yeah, the otherscontinue with the training,
with the high intensity training.
Otherwise they they just needto do a low intensity training
and then they postpone the highintensity session to the next
next day.
So during the training Iusually use that for the
athletes to track that byyourselves.
I also check after there totrack that by yourself.

(33:37):
I also check after the as well.
The heart rate power response.
Of course you have to do someadaptation based on the weather
because, yeah, high weather, hotweather, cold weather, yeah,
change your heart rate.
So you have to do someadaptation on that to compare
the data properly.
And after the training you havemany recovery metrics that you

(34:00):
can use.
One of the most important inthe data that I use it's, of
course, hrv Markwell, as Tókiowrote probably about that.
So I'm using that.
I'm using also all these threeparameters that I think they are
also extremely good and we arealso developing some with the
team.
We are also developing some newsimple blood tests for

(34:25):
extracting some inflammationfrom the blood in the morning.
So just one blood sample andyou understand like CPK response
.
So it's like really reallylight, similar to lactate, but
yeah, you can like one, oneblood, the noise that they have
to say drop one blood drop oneblood drop and and you can

(34:48):
understand your immediately,your CPK response.
And then you go, of course, withthe high level acid because
it's still a little bitter, alittle bit, it's not so.
So it's not possible to buythis, this tool at the moment
for the general population, butI think there will be in the
future many of them.
To understand also theinflammation response in your

(35:12):
body in the morning, your bodyin the morning and also, if you
have the possibility, anotherway to understand better your
stress studies is to track, ofcourse, your nutrition, of
course, in the previous day tounderstand if the athlete has

(35:32):
recovered well from a glycogenpoint of view.
Of course, this one can be doneonly using diaries.
You cannot measure glycogen inthe money.
So basically I don't use any ofthem more than the others.
I try to put everything togetherand understand what's the

(35:55):
biological subject of the artist, because I think Marco has
already talked about that withyou more in the case about the
HRV.
But if I saw low HRV on thatday, it's not a clear sign that
you are in an overtrainingsituation, overreaching
situation, just a normal biology.
So sometimes you don't have tolook at one tool, you have to

(36:20):
understand maybe, the overallstatus of the other, looking at
this time point Sleep I wasasleep, I was.
The nutrition is everythingokay?
I check also with theinflammation, with the CPK
response, with the bloodanalyzer and I check also
resting heart rate.
In the morning I go for somemaximal exercise at the

(36:43):
beginning of high intensityworkout and check if the
response is okay or not and thenI adopt my training based on
that and I think it's a goodpoint to start my competition
and I think I think it's it's agood point to start my
competition to think of trainingin a different way than monday

(37:03):
high intensity and friday highintensity and that's it.

Speaker 1 (37:06):
Yeah, I so.
So you I'm glad youencapsulated it at the end
really quickly, as you're usingbiological status to determine
when the big stressors are, whenthe hard are not necessarily
their day, that they fall duringthe week, or even the frequency
that you have per week.
I mean going back to justrandomness why is it two hard
workouts in a seven-day period?

(37:27):
What's magic about that ratio?
There really is nothing magicabout that ratio.
If you're trying to push andpull physiology, you might as
well use the athlete's initialstarting physiology as the basis
point to determine how hard orwhat the session should actually
look like.
So I've heard a number ofdifferent practitioners, such as

(37:47):
yourself, describe theirmonitoring systems, and I have a
monitoring system with myathlete that I shared with you
in internal continuing ed.
If you get a chance to take alook at it, I'm sure none of it
will be surprising to you.
But whenever I hear a versionof that whether it's coming from
you or whether I'm articulatingmy own or I talked to another
coach about, kind of abouttheirs I always think that we

(38:10):
were trying to hedge our bets.
We're trying to collect all ofthis information, right, and
it's almost like a.
I'm going to use a financialanalogy here.
It's almost like a financialadvisor telling you to diversify
your assets.
You shouldn't have everythingin real estate.
You shouldn't solely basethings off of heart rate.
You shouldn't have everythingin the stock market.

(38:31):
You shouldn't base everythingoff of blood lactate.
You shouldn't base everythingoff of sleep.
You shouldn't have everythingin physical assets like gold.
You should have a little bit ofeverything and then you can
choose how, depending upon whothe athlete is, you can kind of
choose where to push and whereto pull, what things to put more
, what things to put more weighton.
I'm always come away with that,with a similar type of analogy,

(38:55):
when I think about thesemonitoring systems.
We're gathering a lot of thingsto get multiple direction
arrows.
We apply a different weight toeach one of those directional
arrows.
At the end of the day, they'revery rarely all pointing in the
same direction with the samestrength, and this is where the

(39:17):
art of it really comes throughis trying to figure out which
ones of those directional arrowsare we going to listen to,
where some hard and where someharder, like stopping points,
like.
I absolutely see this and so Iknow every time I see this, or
90 of the time I see this, I'mgoing to take 180 degree
approach.
The day goes from hard to easy,something like that.

(39:39):
But I guess my point with thatis is there's always going to be
new things that are emergingand it's kind of up to us to
like make sense of it all, eventhough they're not going to all
tell you the exact same story.
There's going to be somethingthat goes along and you've seen
this in your monitoring systems.
There's going to be somethingthat doesn't jive with the rest
of the, with the rest of the,with the rest of the patterning

(40:01):
that's actually going on.
So for the athletes and coachesthat are out there that are
like they want the answer, right, they like tell me the protocol
.
That's always big in the podcastworld right now.
Right, give me the protocol.
We're not going to have one foryou because I've developed one
that I think works okay for theathletes that I work with, but I
don't use it universally acrossall of my athletes.

(40:23):
I have like different kind offlavors of it, so to speak, with
each athlete, based on a numberof different factors the way
the athlete collects the data,how comfortable I am with it, my
history with the athlete howthey have reacted underneath
different kind of like aphysiological profile in the
past.
Going back to our the past willtell you a lot about what you
could do in the future dialogueat the earlier part of this

(40:45):
podcast, so I'm not going tohave a magic answer.

Speaker 2 (40:50):
I basically say to everyone that is asking for a
magic protocol, I always say, ifwe have a magic protocol,
probably artificial intelligencewill replace us in a minute.
Sure, they can analyzeeverything and they can do a
program better than us.
But it's really good for coaches, the good of the coach, the

(41:10):
ability of the coaches toanalyze everything, understand
which one of these parameters isgood for that outlets and which
makes sense more for anotherone, and understand why you have
.
Maybe you have some alarms orlike worry advice for the let.
Maybe you choose by your own togo ahead with the high

(41:35):
intensity.
Even you need to have warningbecause maybe you want to check
if they might respond better tolike more long stimulus and then
they adopt in a better way witha higher load.
So you don't see the warning ofyour tools, your parameters,

(41:58):
and then you go ahead with theone, maybe more session high
intensity to check what happens.
And I think it's also theability of the coach to
understand everything and tomanipulate the program in a
proper way.
And that's why I think thatthere will be always, also in
the future, a human coach thatcan play a big role and cannot

(42:23):
be, we cannot be replaced byjust general trends of the data
and automatic settings of theirof the trading program well, let
me get.

Speaker 1 (42:33):
I'll give the listeners so that.
So, so that it's actuallypractical.
I'll give the listeners anactual practical example of how
this decision making processlike comes through in my
monitoring system and and I'vespoken about this in a number of
different formats, so none ofit's, you know, super secret or
proprietary, but I use Marco'sHRV for training pro as not the

(42:57):
exclusive part of my monitoringsystem, but it's kind of become
the cornerstone.
And so for the listeners outthere, the way it works is you
wake up, you get in a seatedposition, you take your heart
rate, you take your morningheart rate variability using the
phone on the back of your orusing the camera on the back of
your smartphone.
You then fill out a subjectivequestionnaire how well did you

(43:20):
sleep, are you sore, things likethat and it uses this little
slider system to kind of gothrough that and then it turns
through all that data and itgives you basically a stoplight
system style of advice Greenproceed as planned.
Yellow would mean to take iteasy to limit your intensity,
and red would be to take a restday or to take an easy day, and

(43:45):
I would say in about 70 to 80%of the total amount of days that
I'm analyzing, I'm taking thatadvice wholeheartedly, meaning
most of it's green because I'mdoing a good job load managing
on the front end.
But in the times where it'syellow or red, sometimes I'm

(44:05):
taking that advice andoftentimes I'm not.
And I don't have a magicformula to say well, underneath
these conditions I'm absolutelytaking the advice and under
these conditions I'm not,because I have to go through the
whole thing.
What happened the previous day?
Were they traveling?
Is it a really importantsession?
Is there no intensity on thesession and it's just really
hard or it's just a long?
It's hard because of theduration of the workout and I

(44:28):
want them to continue as planned.
Or maybe we have more spacebetween when they're working out
now and the race and I want tosave that workout for a day
where they're kind of like moreprimed for it.
But I guess my point with allthat is is, even within that
monitoring, and even though I dohave an answer on what to do,
an algorithmic type of answer onwhat to do, I'm still taking in

(44:50):
the context and I can't and Ihaven't been able to at least
come up with an algorithm, and Ihave tried to do this.
Come up with an algorithm thatwill tell me okay, I'm going to
take the advice in thissituation and not I'm always
adding some sort of humanelement to it, based on the
context of the entirety of thesituation.
So my kind of like counsel toathletes and coaches out there

(45:14):
is to start with something thatyou're going to continually do
and then do it consistently andthen see what actually happens
and use those previous learningsto like to go forward.
Because, to going circling backto our original point,
sometimes an imperfectmonitoring system done
consistently when you can learnfrom it, is more powerful than

(45:35):
the perfect monitoring systemthat you can put in place that
might be impractical to actuallydeploy and the key with it is
just determined, is just lookingat it from a past perspective
and figuring out when it's givenyou good information and when
it hasn't.

Speaker 2 (45:49):
Yeah, that's usually the best approach, I think, is
this one.
So, yeah, I have a similarapproach like you.
So probably we are.
We are going in a sort ofparallel way to this one.
Yeah, this one kind of metrics,but they are, we just need to
say, shall be as well.
But, yeah, the approach oftraining is, it's really similar

(46:12):
, even with the high level ofthis, with the professional
cyclists, we are using a similarapproach, of course, with maybe
like more tools and morecontrol life, because, yeah,
also another point that it'soften happens with the amateur
it's like that, it's likecontrol life less than

(46:32):
professional athletes.
So they have some, maybe somemultifactorial stressors.
That happens.
And so sometimes you, yeah,maybe you can check the alcohol
effects on hrv and maybe it'snot a big problem for the next
session for me, but it'saffecting HRV.
So you see a red point, butit's maybe not a big red point

(46:55):
because you can go ahead.
It's just for your respondersto alcohol it matters that they
are really good responders toall stimuli and so, yeah, they
just go, they just go ahead, andthen after one day they go back
to normality.
So I think, yes, the approach isthe best and I think, with this

(47:19):
micro-organizational approach,I think we can sometimes keep
some I don't know, say some notuseful long tapering process.
That happens in the past, Ithink, because we can almost
every time track your biologicalstudies and so, even if it's

(47:40):
not 100% clear, it's like 90%,and so we can maybe sometimes
keep some like long taperingprocess because they are not
useful, simply not useful in thetraditional 3 plus 1, 2 plus 1
block yeah, let's try to putsome of this monitoring stuff

(48:04):
into categories, into buckets,because I've been taking notes
here and I think that they'refalling into relatively neat
categories that we can discussand try to describe so that
everybody can learn somethingfrom this.

Speaker 1 (48:18):
So the first category of monitoring would be just the
subjective category.
How are you feeling?
How did you feel yesterday?
How do you feel when you wakeup?
That's easy.
You can put that in a notebook,you can have a format for it,
you can have a Googlespreadsheet.
The HRV for Training Pro that Iuse has some subjective element
of it, but it doesn't requireany device other than a pen and

(48:43):
some paper.
Right, you can use that to tryto monitor things and I think if
you just did, that's a reallygood starting point.
How did you feel during yourtraining?
How do you feel today?
You consistently monitor that.
Use one to ten scale or you canuse some sort of likert one to
five scale or something likethat and I think that would give
you a good direction arrow,fundamental.
I think these pointsfundamental.

(49:04):
The the second one and this isthe one that you described right
from the onset is you're doingsomething active and you're dose
testing the active componentwith a harder type of interval
and you're looking at thephysiological response to that
Heart rate response.

(49:25):
We can measure other thingsgoing on physiologically, but
fundamentally you're using thevery beginning of the workout to
determine what is actuallygoing on and interestingly
enough so I have a GarminPhoenix seven on my wrist right
now.
If I went and I started to runwhen started my run this morning
, after about five or sevenminutes it will give me some

(49:47):
readiness score.
It's from negative 10 topositive 10, I think, is the
scale.
I can't I don't even profess toknow what the scale is, nor
what goes into it, but my pointwith that is is some of the
device manufacturers are tryingto do something similar where
they're using the beginningportion of a workout and they're
capturing something.
In this, in my wristwatch'scase, they'd be capturing speed

(50:08):
and heart rate and the way thatit changes over the first
several minutes, and it's usingthat as an input, right?
So you're using the verybeginning part of it, you're
taking that to an amplifiedlevel and you're doing some hard
thing during the quote unquotewarmup, during the early stages
of the workout, to determine howthe athlete's physiology is

(50:29):
responding.
Am I describing that correctly?

Speaker 2 (50:32):
Yeah, it's not like maximal, but it's like some
maximal stat, incremental, solike it's below the LT2.
So it's like between LT1 andLT2.
And then I tracked the HR atdifferent maximal power

(50:54):
intensities and I yeah, Iunderstand it's the athletes is
a really low response in termsof heart rate, it's normal
response in terms of heart rate.
It's over response to heartrate for that power.
And then I, especially with thehigh level outlet, I have some
bands, like when you have likethe one that you have for HRV,

(51:18):
and if you are on the bands youcan proceed with the workout.
If you are way far from thebands, you can go ahead with
easy training and skip and movethe hard session to the next day
yeah.

Speaker 1 (51:31):
So my point with that is is it's active, right,
you're doing something withinthe warm-up, you're looking at
the physiology that's going onduring the warm-up and you're
using that as a directionalarrow.
That's another bucket, andthese buckets are in no
particular order.
They're just as I was thinkingabout them.
The next one is if we wouldthink about our chronologically
it's kind of in between thefirst two that I just mentioned

(51:53):
and that's taking somephysiology at rest.
So most people will do thiseither via a nighttime heart
rate they're waking heart rateis the thing that most people
are familiar with.
When I was a young athlete, Icould wake up and I had a
wristwatch by my bed and I wouldjust physically take my pulse
for six or 10 seconds orwhatever it was.
And now we have all thesesophisticated things to where
we'll do it overnight.

(52:13):
We can get nighttime averages,we can get the lowest during the
night, we can get heart ratevariability during the night as
a nighttime average or in themorning.
But it's something at rest.
I guess is my point with thisfinal bucket You're looking at
physiology at rest before youactually go and work out.
The cornerstone of themonitoring that I use uses that
as a big component of it.
And then the fourth category,which might be the most exotic

(52:41):
one, is we're using some sort ofblood profiling to determine
the periodization concept,micropurization or kind of
whatever we want to call it,whether that's what you had
described, where you're taking avery small sample of blood and
looking at inflammation markers,or you're just using lactate,
which is I know a lot of othercoaches use.
They will use lactate evenduring, kind of the first

(53:01):
submaximal parts of a workout,as you were describing.
Yeah, you, so that's part ofyour system as well.
But then also, if you want totake a bigger lens approach,
there are there, there areperiodized schemes that I have
seen out there that do, that areinfluenced by blood profiling,
that you're getting eitherbi-weekly or monthly or whatever

(53:23):
the frequency actually is, towhere you can determine, or you
can use to help determine howmuch and or what type of
training you actually want todeploy on the athlete.
So those are the four bucketsthat I've come up with the
subjective bucket, the restingbucket, which is heart rate
variability and things like that, while you're actually just

(53:44):
sitting down.
The active bucket, so you'redoing something and then you're
measuring physiology based on anactive state.
And then the bylaw, the usingblood biomarkers.
Yeah, it's getting complicated.

Speaker 2 (53:57):
It's getting complicated but, yeah it makes
clear to the, to someone that isusing the podcast, that it's
really complicated for the coachto understand the real
biological statistics of theatlas.
We need four buckets tounderstand it.
We don't understand everything,so it's really complicated,

(54:20):
it's really difficult tounderstand, but at the end I
think it's a more modern andaccurate approach to track
biological adaptation toexercise than doing just check
anything in the, just checkingthe exercise, physiological
studies and not checkinganything else, and then taper

(54:43):
for a week and then everythingis okay, and then taper for a
week and then everything is okayand all things for adaptation.
I think it's better to trysomething to understand what's
happening in the body additionallevel, as you say.
And of course you are stillmaking some errors it's normal
and mistakes.
But I think you cannot strainlight in 1960.

(55:08):
You have to train light in 2024.
So you need to train with themodern tools.

Speaker 1 (55:15):
You have to use modern tools.
You have to use modern tools,yeah.

Speaker 2 (55:19):
I came up with a few, but just to say another thing
you have to understand whatthese tools mean, because
otherwise, if you don'tunderstand what the meaning of
that one, it's better not to use.
Otherwise, yeah, it's justlooking at the data and without
understanding anything.
So that's why, of course, Ithink it's crucial to let you

(55:40):
understand better what'shappening in your body.

Speaker 1 (55:43):
Yeah, and that's where an educated eye comes in.
Yeah, and that's where aneducated eye comes in.

(56:08):
And I mentioned algorithm atleast currently, that will tell
you that accurately.
There are a lot of ones thattry.
I mentioned the Garminreadiness indicator that I see
every single day when I start arun.
I don't think that is evenclose to the best way, to the
best one out there.
As we were discussing this,though, I got to go back,

(56:28):
because there are going to besome coaches that are going to
get mad at me if I don't mentionthis.
There's a fifth category thatboth of you and I probably use,
but sometimes we can neglect it,and that's the actual training
data.
And sure, that's a laggingindicator because they've
already done the workout andthen you're analyzing the file
or the workout to determinewhat's going on in the future.

(56:49):
But that is certainly somethingthat you can look at in terms
of your entire monitoring systemand just comparing effort to
effort and what is that and whatis actually going on.
We'd be remiss if we didn'tmention that, because they've
actually got to go and doworkouts at some point.

Speaker 2 (57:03):
Yeah, it's probably the more common and easier to
understand.
Yeah, so we mentioned aboutthat.
But yeah, it's probably themore common and easier to
understand.
Yeah, so we mentioned aboutthat.
But yeah, it's, of course, theswift one.
Yeah, yeah, yeah, well, youwere right.
So we tend not to go aheadwithout mentioning the most
important one.

Speaker 1 (57:21):
But even I know coaches now and this is I think
that this is more prevalent inmy world and ultra running than
it is in your world and cycling,because cycling has a couple of
decades where thesophistication that uh, trail
and ultra running is kind ofcatching up to now, because the
data is so good with onboardpower meters, it's been the
predominant catalyst uh,predominant catalyst for that.

(57:42):
I do know a lot of ultrarunning coaches that don't care
to look in athletes, that don'tcare to look at their training
data.
They go, do the workout.
They might skip to thesubjective part how did that
feel?
And not couple it withsomething analytical in terms of
how did the workout actually go?
Much like we do on the cyclingside, maybe to a fault, or maybe

(58:05):
we analyze it and get tooprecise with it.
To a fault with different powerranges and power duration,
curves and you know and thingslike that that you're quite,
that you're quite familiar with.
I do know a lot of coaches andathletes that just skip that
step on the trail running sideand they look at something as
coarse as their Strava segmentsto tell them if they had done a

(58:25):
you know good workout or not.
But actually, looking at thefiles if you can kind of see
through the data and you knowwhat you're looking at can be a
really important component ofhow to periodize things for the
future, because it gives you avery good gauge of how the
athlete actually performed andhow much fatigue that they may
actually have on their system,based on not only that workout

(58:48):
but also the entirety of theworkouts previous to that yeah,
that's certainly.

Speaker 2 (58:52):
I think it's probably for because it's, like, I think
, a more easy to analyze it incycling, because you have some
bands and so, yeah, I don't knowwhy they don't do it, but
probably because it's moredifficult.
You have more different thingsto see in running and with the
trade, but then in cyclingbecause we yeah, of course, you

(59:14):
don't have, like our meters, so,yeah, it's a little bit more
tricky to understand and tocompare the data, but I think
you can find somethinginteresting from that Also.
Yeah, just, quite that's quitesimple.
It's a after.
It responds to the duration.
It's really easy to track andto plot and to analyze and

(59:35):
understand what's happening inthis final part of the session.
And yeah, I don't know why theydon't do that, but yes, I did
plays a big role in themonitoring process of the art.
It's, if you don't do that,it's, I think, a missing part of
the entire puzzle.

Speaker 1 (59:52):
So I started out predominantly coaching cyclists
and when I transitioned tocoaching more trail runners,
what I tried to do is to takehow I would analyze a file from
a cyclist and use that samestrategy to potentially analyze
the same things on a trailrunner.
I'm choosing that language andthat vocabulary very

(01:00:13):
deliberately because we don'thave as good of an intensity
surrogate as we do on thecycling side with cycling power
meters, which is a very good nota perfect, but a very good
intensity surrogate.
We certainly don't have that onthe trail running side and the
closest analog that we have tothat would be the training peaks
vocabulary, for that, which isthe tool that we use, is

(01:00:34):
normalized graded pace.
The Strava analog to that is agreat adjusted pace and they
both fundamentally do most ofthe same, most of the same
things.
But it gets obscured primarilybecause of the surface or the
technicity of the trail.
But if the trail conditions areall relatively or roughly the
same, you can use it as a prettygood intensity surrogate and

(01:00:57):
compare interval to interval andcompare from first half of the
run to the back half of the run.
There's a number of differentways that you can do it, but
just starting off with thatfundamentally and try to see
through.
That is a is.
It's an important problem tolook at, but it's a difficult
one to solve simply because theterrain is obscuring a lot of
what you're looking at, and soyou might only get 70% usable

(01:01:19):
data or 60% usable data, andthat's fine, that's better than
0%, but you got to know whatyou're kind of getting into, but
, but.
But I think that, back to theoriginal point there, using
normalized graded pace is theanalog for the on the cycling
side of things, and looking atthat as part of your monitoring
system is absolutely in figuring, and using that to kind of

(01:01:42):
periodize what's going on in thefuture is an absolutely
critical part of everything.

Speaker 2 (01:01:48):
Yeah, I'm using also that on my analysis with the
wheelchair runners.
So, yeah, I think it's the most, most shots, yeah, the more
important parameters that youcan track more, most of the
easiest one that you can track.
And also, I think, honestly,when you, when you, yeah, maybe

(01:02:08):
sometimes you have not like thepossibility to analyze only
percent of your data in thetrail or which are running,
because, yeah, as you said, forthe terrain on the surface, but,
yeah, the rest of the data aregood.
So, yeah, maybe you definitelyneed to analyze some section
that you know are good for dataanalysis.

(01:02:28):
Maybe, when it's too difficultbecause for the GPS it's not
taking the right segment and theright track, yeah, you have
just to skip and clean that partand then maybe consider another
part for your analysis.
But, yeah, when you see thedata, it's the data are good or
not.
It's.

(01:02:49):
Sometimes you see I sawsomething also in dry running or
in also in cycling.
Sometimes GPS is not workingwell, yeah, and so you check
something and you see scores.
In cycling, the orange is notthere because you have the power
, so you can analyze power and,yeah, and internal response at
the same time, but in running,if you don't have the right

(01:03:11):
running speed because it'soverestimated or underestimated
by the GPS problem.
You can overestimate it orunderestimate the fatigue of
your tablet.
So, yes, important also in thissituation to check if the data
are good extremely important.
And yeah, sometimes you're justchecking track on on the on the

(01:03:31):
side and checking where theathletes are.
You can understand if thenormalized data can be good or
not.
For that analysis sort of startsomewhere.

Speaker 1 (01:03:40):
That's what I encourage athletes to do is to
take one of these.
Start that that do itconsistently and even if it's
just as simple as I'm going togive myself or give my coach,
subjective feedback on how Ifeel every single day, don't
discount how powerful thatactually is as long as you're

(01:04:01):
doing it every single day, andthen you can go back and pick up
on the patterns.
Going back to what we originallytalked about when were you good
, when were you bad, whattraining worked, what training
didn't and what was thesubjective feedback revolving
around those times.
That, in and of itself, we'dlike to talk about monitoring
blood biomarkers and things likethat, which is definitely an
advanced tool and can be verypowerful, but sometimes, if you

(01:04:24):
just start simple, you can makea big dent in what you're
actually doing day to day.
I'm going to let you go, luca.
I know you got a busy seasoncoming up or it's in the middle
of a busy season, so I won'ttake up any more of your time.
If anybody is around Milan,which I know where your offices
are where can they come find youand find more about you, even
in an online capacity?

Speaker 2 (01:04:44):
Yeah, if you come to Milan, you can visit me in my
Endurance Lab.
It's called Endurance Academy.
It's again near Milan, near theMalpensa airport, and you can
come and visit me and visit mylaboratory, visit my training
outlets, also my EnduranceAthlete.

(01:05:05):
And yeah, online you can findme wherever so Instagram, I have
a page also.
We have also a page forEndurance Academy on both and
also on Twitter, via email,wherever.
I'm always available and if youhave some questions, don't

(01:05:27):
hesitate questions, I canrespond to everyone.
It's always a pleasure to sharesome knowledge to everyone.

Speaker 1 (01:05:37):
You're busy man.
I appreciate you.
I'm going to come and check outyour lab next time I'm in the
area.
I might be able to make it overthere when I'm there for UTMB.
We can connect about thatonline.
But, yeah, I'm alwaysappreciative of what you do.
You're a good follow on all thesocials and I'm going to leave
a link in the show notes to theeditorial that you wrote that
kind of catalyzed thisconversation.

(01:05:59):
I encourage people to checkthat out as well.
So thanks for coming on thepodcast man.
I really appreciate it.
Luke Keenum, PhD.

Speaker 2 (01:06:04):
Thank you, thank you and thanks for your answer all
right folks.

Speaker 1 (01:06:10):
There you have it.
There you go.
Much thanks to luca for comingon the podcast today and
describing more in detail andenlightening us more on what he
means by micro periodization andthe impact that it might
actually have with athletes.
As we mentioned during thepodcast, this is something that
I have started doing a lot morewith my athletes, where we are
looking at things on a one day,two day, three day, four day

(01:06:33):
rolling basis and, althoughthere might be some general
strategy that we are applying tothe entire phase, using what is
going on in real time todetermine are we going hard, are
we going easy, are you goingfor a really long run, and what
does that data actually mean atthe end of the day for improved
performance?

(01:06:54):
I'm going to keep exploringthis area further because it
does seem like the very tip ofthe spear is starting to deploy
these types of monitoringsystems and these types of micro
periodization models more andmore.
But I will fully admit that ittakes a keen eye and I'll also
fully admit that sometimes we'rejust taking educated guesses as
coaches.
We're looking at the data infront of us and we're trying to

(01:07:15):
make best decisions based off ofthat.
So if you wanted one really bigtake home point, that is,
capture the subjective feedbackaround your training.
There really is no betterwindow into how you're
performing and how you are doingthan the good, simple,
old-fashioned how did you feeltoday?
If you capture that over thecourse of an entire year and

(01:07:39):
then go back after your seasonis over, look at the times where
you felt you were trainingreally well and the times that
you felt that you weren'ttraining so well, I bet that you
can start to derive somepatterns from that.
So if you're not doing that,start doing that today.
It's something that can paydividends and pay a lot of
dividends in the future.
All right, folks, that is itfor today and, as always, we

(01:08:02):
will see you out on the trails.