LeMond / Shermer / freakonomics
ronaldo_jeremiah
notable that Shermer doesn't seem to count LeMond's virtual TdF
victories.
I tried to find a URL for this (I get it in e-mail), but it looks like
these are posted to www.skeptic.com a few weeks after they are sent
out, so it isn't there yet, so here it is below:
What the Numbers Can Reveal
a book review by Michael Shermer
In a quarter-century of serious cycling I have heard all the rumors
about performance enhancing drugs, from stimulants in the 1970s, to
steroids in the 1980s, to blood boosters like Erythropoietin (EPO) in
the 1990s. A friend who knows my penchant for exposing fraud suggested
I track the winners' speeds from the Tour de France to note the
increase after 1991, the year he says EPO was introduced. Since my
friend won the Tour three times, I figured it was worth checking.
>From 1949-1962, the Tour winner's average was 34.7 kilometers per
hour. From 1963-1976, the winner's average increased to 35.4 kph, a
2% difference. From 1977-1990, the winner's average increased
another 2% to 36.2 kph. From 1991-2004, the winner's average speed
jumped to 39.5 kph, a 9% increase. Something happened in the 1990s to
trigger such a leap in speed.
EPO? Maybe. But there are other factors. Composite materials led to
lighter and stronger bikes. Clothing was more aerodynamic. Nutrition
and training were more scientific. The racing field grew in size, from
an average of about 120 in the 50s, to about 190 in the 90s (more
riders accentuates drafting and increases speeds on the numerous flat
stages). The race was shortened by almost a thousand kilometers over
the past half century. And with sizable increases in prize monies,
sponsorships, and endorsements that came with the Tour's elevated
international fame (especially in America) in the 1980s (when my
friend, who helped to instigate these changes, was racing), the
selection pool of elite bicycle racers deepened, thereby elevating the
average quality (and thus speed) of the Tour as a whole.
Are these factors enough to account for the statistical spike in the
90s? Additional tests could resolve the matter, such as comparing the
split times on crucial mountain stages between top riders and average
riders, pre- and post-1991, under the presumption that the top riders
would be employing the best performance enhancing drugs under the
direction of the most knowledgeable sports physicians. A significant
difference between top riders but not between average riders, pre- and
post-1991, would be compelling evidence of artificial performance
enhancement.
My model and inspiration for this exercise in data comparison came from
Steven Levitt, an economist at the University of Chicago who is shaking
up his profession by employing standard methods from the social
sciences to very nonstandard questions from the real world. A 2003
article in the New York Times Magazine about Levitt by journalist
Stephen Dubner led to their collaboration on a book with the improbable
title Freakonomics (so named for the freaky subjects they explore). An
expanded version of that essay, Freakonomics was primarily written by
Dubner and is a hodge-podge of Levitts polymathic interests. Although
the authors eschew any central theme, I took from it two messages:
Science can answer the broadest range of questions (even freakish ones)
about human behavior.
Incentives and motivations are intimately linked in driving human
behavior.
For example, Levitt devised a clever algorithm to analyze data from
Chicago public schools to reveal that some teachers were helping their
students cheat on state exams by filling in answers to later harder
questions in a very predictable fashion (always the same block of
correct answers). Further, there was a spike in the scores one year,
followed by a decline to earlier performance levels. Retests on these
same students proved that they did not know the answers to those harder
questions. The teachers were fired.
In a related computation, Levitt discovered that Sumo wrestlers were
fixing some of their matches. In order to rise in rank and earn more
money, a wrestler must finish a tournament of 15 matches with a winning
record. Levitt found a pattern of cheating whenever a 7-7 wrestler
(with a lot to gain) was pitted against an 8-6 wrestler (with little to
lose) on the final bout of a tournament. A 7-7 wrestler's predicted
win percentage against an 8-6 opponent is 48.7%, whereas the actual win
percentage was 79.6%. The next time these two wrestlers met when there
was nothing at stake, however, the 7-7 wrestlers won only 40 percent of
the rematches. "The most logical explanation," Levitt concludes,
"is that the wrestlers made a quid pro quo agreement: you let me win
today, when I really need the victory, and Ill let you win the next
time."
Levitt has also exposed real estate agents who sell their own homes for
much higher prices than the homes of their clients; and he discovered
that although top echelon drug dealers are wealthy, the vast majority
live with their mothers because the pay works out to only seven bucks
an hour.
Levitt's most controversial computation to date involves the dramatic
drop in crime rates in the 1990s. The reason, he says, was not tougher
gun control laws, capital punishment, decreasing unemployment, or a
stronger economy. The cause was Roe v. Wade. Research shows that
children born into impoverished and adverse environments are more
likely to grow up to become criminals. After Roe v. Wade, millions of
poor, single, teenage women had abortions instead of future potential
criminals; 20 years later the pool of potential criminals had shrunk,
along with the crime rate. Levitt's syllogistic logic is as follows:
"Unwantedness leads to high crime; abortion leads to less
unwantedness; abortion leads to less crime." Of course, Levitt is
quick to add that the solution is not more abortions, but "providing
better environments for those children at greatest risk for future
crime."
Correlation does not always mean causation, and explaining crime is an
extremely complex and multivariate problem. Nevertheless, Levitt shows
that the five states that legalized abortion two years before Roe v.
Wade witnessed a crime fall earlier than the other 48 states. Further,
those states with the highest abortion rates in the 1970s experienced
the greatest fall in crime in the 1990s, and the entire decline in
crime was among the post-Roe younger age group, not among older groups.
More generally, and as an further test of his hypothesis, Levitt
demonstrates that shrinking the pool of criminals decreases the rate of
crime through three additional factors: increased rates of imprisonment
accounts for a third of the drop in crime (compared to capital
punishment, which accounts for only 1/25th of the decrease), increased
number of police (who remove criminals from the system) accounts for
10% of the crime drop, and the bursting of the crack cocaine bubble
caused profits to collapse along with the incentive to sell it (and
thus the accompanying violence declined), accounting for another 15% of
the crime plunge.
The kind of statistical tools that Levitt employs are simple yet
elegant. He cuts to the core of a question, and he picks problems that
are damn interesting, even if some of them seem trivial. All social
scientists should read this book and ask themselves if the problems
they are working on are as interesting or important as those in this
superb work, and if they are using the best available methods for
understanding them.
Robert Chung
> What the Numbers Can Reveal
> a book review by Michael Shermer
>
> In a quarter-century of serious cycling I have heard all the rumors
> about performance enhancing drugs, from stimulants in the 1970s, to
> steroids in the 1980s, to blood boosters like Erythropoietin (EPO) in
> the 1990s. A friend who knows my penchant for exposing fraud suggested
> I track the winners' speeds from the Tour de France to note the
> increase after 1991, the year he says EPO was introduced. Since my
> friend won the Tour three times, I figured it was worth checking.
http://anonymous.coward.free.fr/rbr/tdf.png
Sandy
Robert Chung <m...@address.invalid> a réfléchi, et puis a déclaré :
I actually had instant recall of this graph, especially where the answer is
obvious.
I wonder how today's stars could cope with 500-600 km stages ?
--
Bonne route,
Sandy
Verneuil-sur-Seine FR
Robert Chung
> I actually had instant recall of this graph
> I wonder how today's stars could cope with 500-600 km stages ?
Hmmm. People who have instant recall of my graphs have deeper things to
worry about.
Stewart Fleming
ronaldo_jeremiah wrote:
> Thought this may be of interest to r.b.r. At the very least, it's
> notable that Shermer doesn't seem to count LeMond's virtual TdF
> victories.
To borrow from Fark.Com, "This article is useless without graphs."
Stewart Fleming
Sandy wrote:
> I actually had instant recall of this graph, especially where the answer
> is obvious.
Whent he whole story is known, it would be interesting to plot events in
blood manipulation against the data, especially for the period 1989-1996.
ronaldo_jeremiah
-RJ
Tom Kunich
news:3f3tsmF...@individual.net...
I think that team tactics are what caused the large increase in average
speed and that the shorter stages amplified it.
In the 70's Eddy Merckx could afford to buy the best team and he ground
everyone else into the dust. In the 80's La Vie Claire was the team to beat
and it took bad luck for them to lose. Frankly, there's no other Tour team
around like Postal/Discovery and it shouldn't come as a giant surprise that
they provide the winner.
LeMond's famous 1989 win led to a HUGE increase in the top salaries and with
the advent of Big Mig the teams started to make more as well. That meant
that there was a LOT more to lose if you lost your place on the team.
The question is: Has there been a significant increase in average speed in
the last 10 years? Well, according to Robert's charts, there was a much
larger increase in average speed between the 1947 and the 1956 Tours than
there were between the 1989 Tour of LeMond's and the fastest Tour on record
(2003).
Are there DRUGS in the peloton? I'm convinced there are. I'm NOT convinced
that they make much difference nor that they are all that wide spread since
other methods such as altitude tents, altitude training and maybe those
cherry flavored tootsie pops seem to work.
Robert Chung
>> http://anonymous.coward.free.fr/rbr/tdf.png
>
> there was a much larger increase in average speed between
> the 1947 and the 1956 Tours than [snip]
The cool thing about the graph is that it shows how much cherry-picking
you had to do to make that comparison.
Stewart Fleming
Tom Kunich wrote:
> The question is: Has there been a significant increase in average speed in
> the last 10 years? Well, according to Robert's charts, there was a much
> larger increase in average speed between the 1947 and the 1956 Tours than
> there were between the 1989 Tour of LeMond's and the fastest Tour on record
> (2003).
Check for the effects of phasing out rationing and rebuilding of roads
in Europe as well as population re-establishment after WW2...
ronaldo_jeremiah
What is the correlation between year and average speed if you partial
out distance?
-RJ
Robert Chung
http://anonymous.coward.free.fr/tdf.csv
Hint: partials are easier to calculate (it's 0.6ish, btw) than they are to
interpret.
Robert Chung
ronaldo_jeremiah
-RJ
Tom Kunich
news:428e3d76$1...@clear.net.nz...
What difference does that make? The important factor is that you can pick
several 10 year periods and see a larger difference in speed than Lemond and
Armstrong.
Robert Chung
> Indeed - what is your interpretation?
Rather than look at partial correlations, look at the residuals of speed
on distance and think about the things that influence that pattern.
Sandy
Robert Chung <m...@address.invalid> a réfléchi, et puis a déclaré :
I wonder about the climbing stats, and whether they would influence the
results.
--
Sandy
Verneuil-sur-Seine FR
*******
La vie, c'est comme une bicyclette,
il faut avancer pour ne pas perdre l'équilibre.
-- Einstein, A.
Robert Chung
>
> I wonder about the climbing stats, and whether they would influence the
> results.
I wonder the same thing. Do you know where climbing data are available?
b...@mambo.ucolick.org
I got your Chung Charts RIGHT HERE buddy:
http://www.ucolick.org/~bjw/misc/rbr/tdf.distance_speed.png
http://www.ucolick.org/~bjw/misc/rbr/tdf.year_speedresid.png
http://www.ucolick.org/~bjw/misc/rbr/tdf.year_speedresid.names.png
Some conclusions if you take the second plot literally:
1) If speed = doping, whatever shit Anquetil was on was almost as
good as the EPO era.
2) Merckx and Hinault suck.
3) I wouldn't say LANCE quite sucks, but there is a bit of fall-off
in speed from the 1990s; for a guy who spends a lot of time in a
wind tunnel he is a disappointment. That said, Antoine Vayer
owes LANCE an apology.
Or, the time variation could be mostly down to changes in the way
the Societe de TdF designs the course, with some additional effects
of evolution in national/trade teams and team strategies.
That seems like at least as plausible from the data as le dopage.
Course changes, for example, could explain the time variation: from
the data it's just as easy to call the 1970-1990 era abnormally slow
as it is to call the post-1990 era unnaturally fast.
Ben Weiner
Sandy
Robert Chung <m...@address.invalid> a réfléchi, et puis a déclaré :
Data ?? (blank stare ...)
Robert Chung
> http://www.ucolick.org/~bjw/misc/rbr/tdf.year_speedresid.names.png
> Or, the time variation could be mostly down to changes in the way
> the Societe de TdF designs the course, with some additional effects
> of evolution in national/trade teams and team strategies.
> That seems like at least as plausible from the data as le dopage.
> Course changes, for example, could explain the time variation: from
> the data it's just as easy to call the 1970-1990 era abnormally slow
> as it is to call the post-1990 era unnaturally fast.
Yeah. That was the same conclusion I'd come to, and it seems pretty robust
no matter how you specify the model. That's why I wonder about
characteristics of the course over time.
Nice graphs. Easier to see a pattern from graphs than from partial
correlations.
Kurgan Gringioni
ronaldo_jeremiah wrote:
> Thought this may be of interest to r.b.r. At the very least, it's
> notable that Shermer doesn't seem to count LeMond's virtual TdF
> victories.
>
> I tried to find a URL for this (I get it in e-mail), but it looks
like
> these are posted to www.skeptic.com a few weeks after they are sent
> out, so it isn't there yet, so here it is below:
>
>
>
> What the Numbers Can Reveal
> a book review by Michael Shermer
>
> In a quarter-century of serious cycling I have heard all the rumors
> about performance enhancing drugs,
<snip>
Dumbass -
I never realized the Michael Shermer of skeptic.com (does quite a few
Scientific American articles) is the same Michael Shermer of FRed
Across America (FRAAM).
It's ironic how he calls FRAAM riding "serious cycling".
thanks,
K. Gringioni.
crewi...@gmail.com
Do you have a graph of average speed against total climbing height I
would imagine that would fit fairly well.