A Look At Skier Speeds

I was following Andrew Gardner’s twitter feed a while back during the USSA spring meetings, and he mentioned a comment by James Southam that American courses are far easier than those in Europe. 1

That got me thinking about whether there was any way I could look at this question using, you know, data.  The short answer is that I can’t.  At least not very well.  But the data I looked at are interesting in their own right, and serve as a good example for the sorts of ambiguities and mysteries that can pop up when you’re analyzing data.

My basic idea was to look at skier speeds (in sec/km) and compare these speeds between some domestic races and some international races.  I didn’t have particularly high hopes for anything meaningful to fall out.  There’s just way too much variability in skier speed due to weather, snow conditions, inaccurate course length measurement, etc.

What follows is the “cleanest” look at this kind of data I could manage, at least as a first attempt.  The first problem to overcome is data subdivision.  I can’t mix techniques or race distances, for obvious reasons.  That means I’m limited to a single race format at a time.  I settled on 10/15km interval start races, mainly because they were the format I had the most examples from among World Cup and domestic races.

Still, I don’t have a ton of domestic races in my database (just those from FIS, essentially).  Setting a cutoff of the 2004-2005 season gave me around 20 women/men 10/15km interval start races in the US that weren’t World Cup or Olympic races.  Then you have to split them by technique, leaving only ten in each category or so.

The other complicating issue here is the natural variability in skier speed, within a single race.  That’s probably going to swamp any differences between domestic and international races, so I just grabbed the top ten times from each race.

That means I’ve got the top ten times from a bunch of international and domestic 10/15km interval start races, which I can then convert into average speeds by just dividing by 10 or 15.

What I expected to see was that the distribution of top ten speeds in domestic races lags behind the top ten speeds in international races.  No brainer, right?  In the off chance that the speeds are comparable, that might (maybe, possibly, kinda) be taken as evidence that US courses are on the easy side.

Instead, what I saw was this:

Huh.  The women are behaving pretty much as I expected.  Men’s domestic classic races are slower, too, but less than I thought.  Then you have the men’s domestic skate races, which match up fairly well.

Now, if we were stupid (which we’re not, right?) we might jump to the conclusion that the top men in domestic skate races are actually skiing at the same speeds as the top World Cup skiers.  Until they actually go to Europe, of course.  And then suddenly they slow down.  Or the courses, and just the skate courses, for only the men, are very easy in the US.

Yeah, that doesn’t make much sense to me either.

The domestic race distributions here aren’t based on very many races; only about 10 in each panel.  About half are SuperTours, a handful of western collegiate races and a handful of US Nationals.  If there were a small number of outlying races in this group of 10, we’d see it in the distributions.  But we don’t.  So either the data are “right”, or somehow nearly all ten of these men’s skate races were unusually fast.

I asked around with some skier friends of mine, and it turns out that many of the domestic men’s skate races here were in fact unusual.  Many were held in low snow conditions on alternate courses that were unusually easy.  There might be a 15km mass start race in there that’s been misclassified by FIS.2

At this point, I was feeling pretty good.  Anomaly explained.

But then I started thinking.  Why weren’t the corresponding women’s courses also unusual enough to make the women’s skate races look fast too?  Why is it only the men’s skate races?

Currently, I don’t have a great explanation for this, except the catch-all “Not enough data.”  Which is fair enough; I’m stretching the data pretty thin here.  Still, it’s weird.  And bothering me.  So here’s the list of races:

DateGenderTechniqueLengthStart TypeCategory 1Category 2
2006-01-07MenC15IntervalNC
2006-11-25MenC15IntervalUST
2007-01-28MenC15IntervalUST
2008-01-03MenC15IntervalNC
2008-11-28MenC15IntervalUST
2009-02-08MenC15IntervalUST
2009-12-06MenC15IntervalUST
2010-01-17MenC15IntervalUST
2004-12-17MenF15IntervalNAC
2006-12-16MenF15IntervalUST
2007-01-04MenF15IntervalNC
2007-01-14MenF15IntervalFISCollege
2007-01-20MenF15IntervalUST
2007-12-09MenF15IntervalUST
2008-02-02MenF15IntervalFISCollege
2009-02-01MenF15IntervalUST
2009-11-27MenF15IntervalUST
2010-01-04MenF15IntervalNC
2004-12-29WomenC10IntervalNAC
2005-01-29WomenC10IntervalNAC
2005-11-26WomenC10IntervalNAC
2006-01-07WomenC10IntervalNC
2006-01-22WomenC10IntervalNAC
2006-11-25WomenC10IntervalUST
2007-01-28WomenC10IntervalUST
2008-01-03WomenC10IntervalNC
2008-02-01WomenC10IntervalFISCollege
2008-11-28WomenC10IntervalUST
2009-01-24WomenC10IntervalUST
2009-02-08WomenC10IntervalUST
2009-12-06WomenC10IntervalUST
2010-01-17WomenC10IntervalUST
2004-12-17WomenF10IntervalNAC
2005-01-22WomenF10IntervalNAC
2006-01-21WomenF10IntervalNAC
2006-12-16WomenF10IntervalUST
2007-01-04WomenF10IntervalNC
2007-01-14WomenF10IntervalFISCollege
2007-01-20WomenF10IntervalUST
2007-12-09WomenF10IntervalUST
2008-02-02WomenF10IntervalFISCollege
2008-11-29WomenF10IntervalUST
2009-01-25WomenF10IntervalUST
2009-02-01WomenF10IntervalUST
2009-11-27WomenF10IntervalUST
2010-01-04WomenF10IntervalNC
2010-02-06WomenF10IntervalFISCollege
2010-02-07WomenF10IntervalFISCollege

I suspect there’s at least one or two classification errors in this list of races.  Anyone have any better explanations?

  1. I’m paraphrasing here; it was something to that effect.
  2. I still need to check this.

Related posts:

  1. Another Look At Skier Variability
  2. Gadflies & Punching Bags
  3. How I Learned to Start Worrying and Hate the F-Factor (Part 1)
  4. How I Learned To Start Worrying and Hate the F-Factor (Part 2)
  5. How Well Prepared Are World Cup Rookies? (Part 1a: Distance)

About Joran

Comments

5 Responses to “A Look At Skier Speeds”
  1. Benji Uffenbeck says:

    If we assume that the FIS points awarded during a particular race are at least a reasonable indicator of skier ability on a world-wide scale, then it would stand to reason that races with higher FIS points should exhibit slower per-kilometer speeds. If the gap between FIS points is large enough, it’s quite possible that the lower ranked skiers ski slower on easier courses than the top ranked skiers ski on difficult ones.

    If you look at the top 10 or 20 US men and women and compare FIS points the men tend to have lower point values as a group. This may explain why US men are able to ski at near international race pace on easy courses, while US women still lag behind a bit.

    Another issue is the accuracy of the courses involved. It’s unusual for domestic race courses to measure out at exactly 5000m, 15000m, etc. It’s far more likely that the distances are accurate on the world cup, where courses are scrutinized quite rigorously. Your per-kilometer calculations have to assume that the distances listed are legitimate, but it’s quite likely that they are only accurate within +/- 5% or so. In cases where snow problems cause a last minute course change, the distance may not even be within 5%.

    • Joran says:

      Yeah, mis-measured courses is one of the things I listed as a potential problem in the post. And you’re right that this is more likely to be a problem when (as I confirmed for several of them) they are held in low-snow conditions are potentially altered courses.

      I agree as well that the top US men generally have lower points than the top US women, although I’d have to check if they are lower relative to their international counterparts. The women’s distribution of FIS points among all skiers is just different than for men, so you can’t always compare them directly.

      • Boredin Ramsau says:

        One thing that is interesting is that harder courses ( with more climbing and thus descending and recovery) usually yield faster times. At least that is my experience. Maybe you could look at that…

        • Joran says:

          Good point! As I was just discussing with a friend of mine, the easy/hard and the slow/fast dimensions for ski courses don’t necessarily correspond. But even if we decided that more climbing = harder course, I’m kind of stuck because total climb isn’t very easily scrapable from web sites. Often it’s buried in pdfs somewhere.

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