Statistical Skier

With the modern chip timing tools used today ties should be fairly rare. They do still happen, though:

This shows the number of ties per race of each type for WC, OWG, WSC and TDS races for men and women. As we might have expected, there are considerably fewer ties in mass start style races. Amusingly, this is almost certainly entirely psychological. In a mass start or pursuit race you can see the person who’s going to finish with nearly the same time right there next to you! In an interval start race it’s harder to motivate to sprint the last 10 meters when there’s no one around. It shouldn’t be harder, but it is.

Don’t read too much in the Pursuit Break line. That format is really only used in stage races these days, and even then it’s quite rare. The seemingly big jump in 2001-2002 is not terribly ‘significant’, since that format was only ever used ~2 times a season for each gender. With such a small denominator, a small change in the number of ties can make the rate seem to jump a lot.

What’s more interesting to me is the apparent increase in the rate of ties in interval start races. The trend is more noticeable among the women, but the fact that the rates for both men and women have jumped up somewhat may be significant. I can’t think of a good ‘story’ to explain why this may be, though. It could always just be noise, of course, but it’s interesting to ponder…

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Continuing with my series of posts looking at some split time data (kindly provided by Jan at WorldOfXC.com), we turn to identifying some folks who tend to ski better (as measured by their % behind the leaders) towards the end of a race than the beginning.

I actually fit a model on this one (gasp!) rather than just exploring the data and making a graph. So after a little bit of fun with some linear mixed effects models, here are the 12 skiers with the strongest tendency to ski closer to the leaders as the race progresses:

Once again, you can click through for a slightly larger version, and the y axis is a highly adjusted measure based on percent back relative to that skier in that race. You can go back and check some of my previous posts using this data for a more detailed explanation of what I’m measuring on the y axis. The basic story is that it’s a relative measure for each skier. So the actual numbers don’t signify anything across athletes, just the overall trends.

You’ll notice that several folks here appear to be dramatically further behind the leaders early in mass start and pursuit races. This is in part a function of how these races play out. Early on, there will often be a very large pack of skiers. If someone, say Alex Harvey, is just sitting comfortably mid pack, at 1-2k into the race he might be as much as 5-10 seconds behind the “leaders” just because the pack is so large and moving so slowly. That can easily translate into a fairly large % back given the small amount of time that has passed.

Still, this model included a variable that accounted for the global differences in race type (interval vs mass vs pursuit) so these skiers are still exhibiting a stronger trend than other skiers, even accounting for the overall differences in race type.

Teichmann’s tendency to pick up the pace during a race is fairly well known (my benchmark here being that even I know about that one!). But maybe some of the other’s are a bit of a surprise to some folks…

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