12:30 am - Wed, Jul 23, 2014

The Life Span Project

Who’s up for the macabre?

That entire pizza will be delicious. 

It will literally send a wave of feel good neurotransmitters surging through your entire body.

High cholesterol?

Eh there are pills for that.

Heart attack?

Cath labs. 

Diabetic peripheral neuropathy?

Rascal scooter and handful neurontin. 

But what if on your wrist was a running clock.

A timer counting down the seconds to your death.

So that you could literally see the drain speed up exponentially as you put in some ass time on the couch?

Yes it was a movie starring Justin Timberlake.

But before you groan and roll your eyes youtube “Dick in a box” and try to tell me your are still not a fan.

Won’t happen, guaranteed.

Point is this. 

It is hard to choose long term gains over all the glorious potential indulgence that is literally bombarded at you every waking second.

It might be just the slightest bit easier to make that choice if you had some real time immediate feed back showing the lifespan that you just gave up for a donut. 

The algorithm would be a based on your current medical history, adjusted for running mean projections based the lifestyle choices from the past hour, day, week and month.

Best part is, since it would be an FDA approved medical device you could charge pharmaceutical company style premiums for it.

Needed are a data scientist, software and hardware engineers, and someone that can sell concepts to investors. Let me know if you are interested. 

And if you are skeptical about these types of start-ups, take a look at http://swaymedical.com/ basically a bunch of young geeks about to explode onto the concussion scene. 

Also note, that since the concept is publicly obvious to anyone who has seen the movie it is not patent-able. Effectively that makes this project a first to market rather than first to file type of endeavor.

10:03 pm - Tue, Jul 22, 2014
3 notes

Fitness-Fatigue Models and pVAM

pVAM is a fitness-fatigue model at it’s heart.  While not a subjective fitness-fatigue model, it sets a general baseline of expected VAM performances of the top general classification riders in grand tour stage races.  Poor showing on pVAM doesn’t mean a rider is not doped and a great showing on pVAM doesn’t mean a rider is doped.  The relation of pVAM residuals to doping is the clear delineation from the “doping” era and now in the predicted values of VAM.  The long component of fatigue should show itself over the course of a 3 week race, doped or not, just as the long component of fitness rears will show itself over 3 weeks.  The pVAM/dpVAM chart for stage 14 is disconcerting, while the stage 16 results offer some solace and hope, but they may also point to deeper darker secrets still left in the peloton and the possibility that the tour podium is only achievable in a doped state or a clean rider’s very lucky and very good fortune on flatter stages or possibility to get a long breakaway which gains a lot of time.

One day of the main GC contenders exceeding pVAM and dpVAM should never be a concern, that it happened on Stage 14 should be a slight concern despite the effect of wind and that it is a 9% difference probably can’t be attributed solely to wind.  Without this coming off as a defense of Bardet’s and TJV’s struggles on stage 16, Bardet and TJV have near identical profiles with Bardet showing slightly better ability on the climbs.  Is it odd the riders who show near identical profiles lose time on final climb of stage 16?  No, we must assume as top GC riders they have near the same ceiling in terms of fitness and ability and possibly came into the tour with similar fitness-fatigue profiles.  The oddities here are Nibali, Valverde, and Peraud.   Not so much so far for Pinot, who of Bardet and TJV was the one who looked to have the best fitness profile related to climbing.   However, was Stage 16, Pinot’s swan song.  If Pinot’s not doping, it likely is his swan song this tour and Stage 17 becomes brutal.

What remains to be seen is how much fatigue both Bardet and TJV suffered on today’s climb.  The rider who pushed the limits the most today will suffer the most tomorrow.  Bardet may very well be able to climb back into the white jersey, but it very much depends on how much Pinot pulled out of the tank on Stage 16 as one should expect Bardet, TJV, and Pinot to be shed by the 7th km up Pla D’Adet with Nibali, Peraud, and Valverde making things very tough.   Although we should see a decline in fitness from the cumulative fatigue in the race so far and from the profile of tomorrow’s stage it is possible for Nibali, Valverde, and/or Peraud to crack (doped or not) and for Bardet, Pinot, and TJV or possibly Konig to climb into podium positions (doped or not).  There should be some adherence to the fitness-fatigue model inherent in either dpVAM or pVAM by all of the top GC riders.   One must remember the short components of fitness and fatigue will always play a role over the course of a race.  The key for each rider is what did they take out of the tank the stage before and how much are they going to take out of the tank on the current stage.

We should expect the top finishing rider of the GC contenders to finish ahead of pVAM and below dpVAM for the next two stages, but the other riders should be hovering around pVAM or below it, but no one should be close to dpVAM. 


fantastic submission, thank you
9:59 pm
7 notes

stage 17 preview

6:53 pm - Mon, Jul 21, 2014
2 notes

5 W/kg is the New Normal (get over it!)

"Tejay pushed 338 average watts up the final climb for over 50 minutes. His cadence average was 84rpm and he maintained an average speed of 21kph. Racing at 1m85 with 68kg, Tejay averaged 228 watts with an average cadence of 76rpm."

Calculating that out, Tejay averaged 5 W/kg for the climb. This number could be evidence of very human levels of performance in this years Tour de France.

It could also be the nail in the coffin on the pseudoscience debate as the model estimate of 5.7 W/kg is a huge 14% off.

But there is an issue here.

Take a look at the model break down for Tejay:

4.86 W/kg are needed to overcome gravity

0.27 W/kg are needed to overcome rolling resistance


0.59 W/kg are needed to overcome wind resistance

Of those components 4.86 W/kg is nearly certain as gravity does not change and it was a long climb so timing and elevation change error will be negligible. Similarly rolling resistance is unlikely to be a major source of error of total error since it is such a small fraction of total resistance.

This of course means that the likely source of the error was from wind resistance due drafting or a tailwind (note that I say or rather than and since the tailwind diminishes the benefit of drafting). Starting off drafting can be eliminated as the source of error since a perfect draft would not assist against gravity or rolling resistance which alone add up to 5.1 W/kg. So therefore it must have been a tailwind. And in fact, there was a tailwind on the day. Measured at 10 m above the ground the average wind was 5 km/h. According to calculations by Fred Portelau this translates roughly to about 2.5 km/h at 2m or cyclist height.

For arguments sake, lets say that the wind was a perfect tail wind for the entire climb (in reality it can’t be) that would drop the the wind resistance from 0.59 W/kg down to 0.45 W/kg. So even allowing for an impossible “smart wind” the estimate would only come down to 5.6 W/kg.

To get down to the SRM site reported 5 W/kg there would need to be a cyclist level “smart wind” in the neighborhood of 30 km/h so that Tejay was literally blown up the mountain and that would certainly be not normal.

The point here is the methods for estimating performance aren’t perfect, but they are certainly good enough to pick up that something is way off here.

12:48 pm
Q: Millar's salary dropped by 300 percent? He was paying the team two year's salary just to ride?

the odd places logic leads if we bother to go

12:46 pm
Q: Are the guys in the 2014 TDF on xenon gas?

I don’t know, guys ?

12:07 pm

Rest Day Rebuttals ?

As I did last year I am inviting counterpoints to the estimates and DpVAM models.

Tearing things down is a healthy part of building them up stronger.

Coherent submissions will be published un-edited.

Blanket GIGO statements are GIGO themselves.

My personal rebuttal will focus on wind.

11:12 pm - Sun, Jul 20, 2014
1 note

2014 Tour de France Stage 13 and 14 brief analysis

Sorry about slacking on this post but I’ve got sidetracked into making animated Power Duration curves… more on that later. 


Diving right in to the Power Duration curve going from left to right we now have data points from stages 10, 14, and 13.

If stage 14 (sorry had to fix that) jumps out at you as the out-lier, go ahead and pat yourself on the back. Nibali’s nW/kg came in at 6.2 nW/kg (6.1-6.3) and gets tweaked upward for the plot above for altitude. But, notice that the whole group of top 5 looks fast. Tail gunning Valverde estimates in at 6 and the others at 6.1. Compare that to stage 13 were Nibali came in around 5.9 nW/kg with the rest of the top 5 slotting in from 5.7 - 5.8 nW/kg. Complaints of heat taking its toll may account for some of the difference. But there may also have been a bit of a STRAVA sniping effect on stage 14 where riders hit the bottom of the climb at 50 km with a good amount of drafting going on. It would be interesting to look at the estimates at the splits along the way. Fred Portelau has been working on a model to estimate the wind effect which looks quite good so that will be interesting to take into account as he gets his data out. Overall, the picture that is emerging from the numbers is that Nibali is every bit yellow jersey worthy regardless of the absense of Froome and Contador.

Now listen, if you are enjoying this Tour de France and you want to keep enjoying it just stop here and leave it at that.







Just making sure you actually want to see this…

8:50 pm
26 notes


Tour de France stage 15- Tallard to Nimes 222km

Out of the Alps.

Breakaway of Jack Bauer, Garmin Sharp, and Martin Elmiger, IAM Cycling, escaped the peloton at the start of the stage. Bauer held off the peloton to the last 50 meters when caught by the sprinters. 

Alexander Kristoff, Katusha, claimed his second stage win after the peloton caught Bauer and Elmiger.

It was a cruel outcome for Bauer. 

shoulda worn a proper aero helmet .

(via kyle-lm)

1:58 pm - Sat, Jul 19, 2014
1 note

Got to wonder what the peleton’s local prevalence of anti-biotic resistance given routine over prescription?

“At follow-up, there was no difference in participants described as being clinically improved between antibiotic and placebo groups (11 studies with 3841 participants, risk ratio (RR) 1.07, 95% confidence interval (CI) 0.99 to 1.15”
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