Intra-GT Fatigue and Performance (pseudoscience)

[Ferminal]

I recall earlier in the year reading some comments about a potential problem of comparing climb times one year to the next due to differences in the difficulty of a GT to that point. You also might hear about strong performances in the third week being less “believable” than if the same occurred early on in the race (I have thought along these lines often). Now it would seem like good sense to consider this as one of several factors affecting performance, but thinking about it more there are plenty of recovery “techniques” available which may allow one to maintain output over the three weeks.

There are two points which need to be considered:

A) Can performance levels be maintained across three weeks using available legal and quasi-legal means.
B) Can performance levels be maintained (or even improved) across three weeks using illegal means such as O2 vectors, transfusions, steroids, hormones, peptides etc.

So if Floyd Landis does a 38’ time on Alpe d’Huez in the third week, should we think that he would have been capable of a 37’ in the first week? In my view this is flawed given that this is coming 24-48 hours after a transfusion. If we ignore the rest day then I don’t think he could really do any better at any other point in the race. With the rest day there it may even be better than what could have been achieved at any other point in the race.

I haven’t been able to find evidence in multi-climb data, but to keep it simple these are just single climbs (times are jens’, fastest three on the day). The difficulty of a GT could be measured by cumulative vertical gain (of substantial climbs) or cumulative distance, but those metrics should more or less track the number of days raced.

Time axis is inverted.
Green = following rest day.
Red = following “mountain” stage.
Ventoux is from Bedoin so usual disclaimers.

Clicky

In these samples there is no relationship to be found. It is not evident that there is an accumulation of fatigue as a GT progresses. That is not to say that there shouldn’t be one in theory or that there isn’t in reality, just that we can’t see it amongst the several other factors which influence time.

What I would say though, if conducting qualitative analysis on single data points, intra-GT fatigue is only worth minor consideration, at least when looking at the whole race. It's probably better value looking at the preceding few days. I suggest that fatigue is going to be less of a factor on Day 17 after a couple of flat stages or a rest day than it is on Day 8 after consecutive mountain stages.

 

[roundabout]

waaay too many variables to consider

 

[ScienceIsCool]

waaay too many variables to consider

Even if that were true, the fact that no significant correlation exists tells you some very important things. First is that "fatigue" due to number of previous days racing is not a driver of performance. Second is that there must be other factors that *are* significant. Time to start looking for those variables and isolating the ones that show strong correlations.

John Swanson

 

[skidmark]

Even if that were true, the fact that no significant correlation exists tells you some very important things. First is that "fatigue" due to number of previous days racing is not a driver of performance. Second is that there must be other factors that *are* significant. Time to start looking for those variables and isolating the ones that show strong correlations.

John Swanson

This is a very interesting problem to consider. As someone who has never really immersed myself to a fully comfortable degree in the aspects that make up fitness and performance (I mean, I can name the key aspects of oxygen vector doping and know what 'watts' are, but you know), but also as someone who has a more than passing understanding of research design, it seems to me like the two big aspects that would offset each other over the course of a GT would be fatigue and form. I always hear riders talking about peaking at the right time, like not overtraining for the first week and being fatigued by the third, but maybe riding into form after the first week. The problem is, in all the discussions I've seen here, 'form' is still something that is somewhat nebulously defined. If someone who knows more than me could shed some light as to what some indicators of peak fitness (other than, duh, beating everybody in a race) would be, that would be enlightening. And then further, whether the best indicators of increasing/peak fitness can realistically be measured in the midst of a 3-week GT.

That is, of course, outside of the factors of doping, length of stage, amount of time spent on the attack up an MTF once teammates have been shed, or even (shudder) wind. But hey, can't hurt to list some things, it's the offseason, right?

 

[D-Queued]

This is a very interesting problem to consider. As someone who has never really immersed myself to a fully comfortable degree in the aspects that make up fitness and performance (I mean, I can name the key aspects of oxygen vector doping and know what 'watts' are, but you know), but also as someone who has a more than passing understanding of research design, it seems to me like the two big aspects that would offset each other over the course of a GT would be fatigue and form. I always hear riders talking about peaking at the right time, like not overtraining for the first week and being fatigued by the third, but maybe riding into form after the first week. The problem is, in all the discussions I've seen here, 'form' is still something that is somewhat nebulously defined. If someone who knows more than me could shed some light as to what some indicators of peak fitness (other than, duh, beating everybody in a race) would be, that would be enlightening. And then further, whether the best indicators of increasing/peak fitness can realistically be measured in the midst of a 3-week GT.

That is, of course, outside of the factors of doping, length of stage, amount of time spent on the attack up an MTF once teammates have been shed, or even (shudder) wind. But hey, can't hurt to list some things, it's the offseason, right?

Setting aside that doping throws the whole relationship out the window, the relationship between fitness and form can be simplistically summarized as:

Fitness - Fatigue = Form

As doping should increase effective levels of Fitness, then the equation becomes:

Fitness + Doping - Fatigue = Form

If Ferminal were able to use watts or watts/kg as a measure, then we might have seen a better correlation than by using time or speed given the impact that wind, temperature and drafting can have.

Dave.

 

[blackcat]

recovery doping + motoman - nutella

 

[del1962]

One other factor you need to consider is how a climb was raced and how they got to that point on a stage.

Let say at the bottom of the climb there is a large group together with team mates there, this would suggest that the GC guys would be fresher than a small group of GC guys reached the bottom of the climb together. With the larger group for guys of equal ability you would expect the climb to be ridden quicker than a smaller group.

Then you have to consider how the climb itself was raced, did the GC guys look around at each other at the start of the climb with surges and slow downs, or where some domestiques of one team setting a steady pace, if you have a stady pace with domestiques from the bottom and this is maintained throughout the climb, you would expect a faster time for riders of equal ability than if no one is setting the pace.

You also have to then add in previous stages and wind etc.

This is why it is very hard to compare times on different days.

Even in athletics on the track in a 10000m race, you get different times for the same runners at different word championships and olympics dependent on how the race is ran, with the extra add ins at the end of a grand tour stage you would expect even more differences

 

[Dear Wiggo]

Access to power meter data would obviously be incredibly helpful.

Ferminal have you looked into the concepts used in training peaks? Specifically: http://home.trainingpeaks.com/articles/cycling/what-is-the-performance-management-chart.aspx

Starting with the threshold power, current ATL, CTL and TSB for a rider and then mapping their TSS throughout the 3 weeks, perhaps with a view to tracking (perhaps)

- ATL, TSB, etc
- kj burnt
- time in zone (especially threshold - below, at and above)

comparing the domestique and GT contender.

Would be interesting. Perhaps educational.

TSS (and hence its derivatives) is a very simple measure, and my gut feel is its makeup is as important as its value for a particular ride.

I am training at the moment and noticing different responses (PB or positive ride one day vs incomplete training session the next) to training stimuli, however have not tracked the data in TPeaks to see if there are any correlations between poor performance ("low form") and fatigue from previous day(s) efforts.

 

[D-Queued]

recovery doping + motoman - nutella

Hmmm. Pretty sure Nutella should trump doping for overall benefits.

Dave.

 

[Big Doopie]

waaay too many variables to consider

Bingo.

This is precisely why it is impossible to have a sense of true natural ability or hierarchy in a doped peloton.

That is also why predicting how riders will race in a doped peloton even within one season is also impossible (see Armstrong at Gila and soon after at TDF).

And it therefore follows: that is why cycling for the fan has been destroyed -- because it is precisely the ability to gauge natural talent, enjoy prognosticating, and then reveling in the expected outcome or the sudden collapse of a favored rider or brilliant ride by an unexpected source that gives cycling it's drama.

For example, 1989 is the cycling fan's dream tour. 1996, however, would be one of the very worst.

 

[Ferminal]

Even if that were true, the fact that no significant correlation exists tells you some very important things. First is that "fatigue" due to number of previous days racing is not a driver of performance. Second is that there must be other factors that *are* significant. Time to start looking for those variables and isolating the ones that show strong correlations.

John Swanson

My order is something like this:

- The capabilities of the different riders (what we actually want to learn)

- Tactics/Effort, how the climb is raced
- Weather
- Difficulty of the stage before the climb on paper
- Difficulty of the stage before the climb as its raced
- Difficulty of the preceding few days
- Difficulty of the race overall

Unfortunately the only other factor which can be quantified to some degree is the paper difficulty. It shows with a large sample size but not so much with only a few data points (it's not too bad for Alpe d'Huez if you remove the 2011 outliers).

 

[blackcat]

That is also why predicting how riders will race in a doped peloton even within one season is also impossible (see Armstrong at Gila and soon after at TDF).

forum member 131313 said Armstrong went backwards on the (queen stage?) ascent when he was in the same peloton and passed him. Perhaps he got blood out in Austin before New Mexico, but those 400ml of packed cells were significant. Reminds me of 2006 when Floyd had the jour sans at Dauphine a month before he won the Tour de France. I did lead the speculation he also did the withdrawal whilst at the Dauphine with an eye to the big prize in July.