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WJC/U23 Assessment: Norway and Russia

Continuing on in the vein of my post yesterday recapping the WJC and U23 results for the last several years for the US and Canada, this post will do the same for Norway and Russia. As before, I’m plotting the finishing rank, or place, of each skier and then tracking the median result in red. So “how far behind the leader” information is being lost here, but I feel like a lot of the discussion that happens surrounding WJC/U23 results tends to revolve around what place people finished.

Not surprisingly, pretty darn good, at least to my jaded American eyes. Some picky Norwegians may note that while the median men’s distance performance remained roughly the same as last year, they saw fewer top fives. As I noted before the competitions started, the Norwegian junior women have been doing very well in the distance events, with occasional results outside the top 15 or 20, but only occasionally. Interestingly, both the junior men and women from Norway had a bit of an off year (for them) in sprinting in 2007-2008. Continue reading ›

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Animated WJC Results History

I had fun making those animated charts for World Cup points the other day, so I thought I’d try using the same charts to look at World Juniors. All I’ve done is tally up “World Cup” points for each nation and each year, scoring each (individual) race using the traditional WC point scale. Then I divided each tally by the total number of such points awarded that year (since the number and type of races has changed over the years). So each point represents a single nation, with the x and y coordinates being the proportion of total “points” earned by that nation, that year.

As before, there’s really only a single data point for each nation for each year, but this Google chart API move the points smoothly between them. And they require Flash. Men first and the women below. Important: I’ve been noticing that the “Trails” option grinds the whole animation to a halt for me, so I’d recommend unchecking that option before you start playing around with these.





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WJC/U23 Assessment USA and CAN

This week is going to be pretty heavy on the WJC/U23 graphs, I suppose, as we wait for the World Cup racing to start up again.

One of the things that has struck me while writing this blog is how much importance and meaning is placed on WJC/U23s compared with how little data they provide in a given year. What I mean is that if we think of a ski race as a measurement of performance, WJCs provides only 2-4 “measurements” for each athlete. That doesn’t add up to a ton of data, given how variable skiers can be, even when they are racing well. That said, they are what they are: a World Championships, so assessments are inevitable. Let’s see what we can see.

Each below graph summarizes the performance of either the USA or CAN in either WJCs or U23s over the past six seasons. I feel like the quality of the WJC (and to a lesser degree the U23) fields are at least reasonably stable over this time period, so I’m only going to look at finishing rank. They show each individual result along with the median result for each year in red. We’ll get our feet wet with the WJC graph for the US:

This should give you a good sense for how, with so little data within each year, that simple summaries like the median don’t always reflect everything we’d like them to about the data. The two clearest trends here are in men’s distance and women’s sprint, with some steady drop-offs in the median over the past three seasons. The US women did have some strong sprint results this year compared to the recent past; they just also had some bad ones as well. Continue reading ›

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What Happens To Successful World Junior Racers?

This post appeared on FasterSkier several months ago, but I never posted it here, I don’t think. With World Juniors and U23s wrapping up, it seemed relevant. I edited the text slightly so it will differ somewhat from the original version. These graphs do not include this year’s WJC results or any results from the 2010-2011 season.

Identifying talent in endurance athletics at a young age can be a challenging task.  My goal here is to give you a sense of what different levels of success at WJC/U23s might indicate and how much variability there is between athletes in this respect.

Our basic tool will be a graph of FIS points versus age for distance results, broken down by their best result (finishing place) at WJC/U23s.  This gives us a total of eight panels representing the men and women who’s best results were between 1-5, 6-10, etc.

If you’re in the 1-5 group, that means your best result at any WJC/U23’s was between 1st and 5th.  For each group, I’ve plotted their FIS points (in distance races) versus age.  Each dot represents one race by one athlete.  The blue trend lines are for everyone in that panel.  The red lines are for only the American’s in that panel.

If an athlete’s name appears next to one of the red lines, that means they are the only American appearing in that panel.  Otherwise, the trend lines are averaging over multiple athletes.  These graphs are fairly large, so you might want to click on them for a larger version.

There’s a lot of interesting stuff going on here.  Let’s ignore the Americans for a moment and just look at the blue trend lines.  We’d expect the 1-5 group to have the most future success overall, and that is the case.  (More dots near the bottom.)  As we move right to the 6-10, 11-15 and 16-20 groups the cloud of points mostly creeps upwards, but less so by the time we’re comparing the 11-15 and 16-20 groups, suggesting that there’s a bigger difference between a top 5 and a top 10 than between a top 15 and a top 20 result.

We might also expect the trend lines in the groups to flatten sooner and at a higher level as we move rightward.  This would correspond to skiers who see less success at WJC/U23s not improving as much or leaving the sport earlier, or both.  This kind of happens, but with some weird caveats.  The men seem to follow this pattern until we get to the 16-20 group.  Why do the 16-20 athletes continue to improve past age 23 where the 11-15 athletes don’t?  The answer is likely our old friend, selection bias.

Success in ski racing serves as kind of a signaling mechanism as to whether you should continue racing.  Skiers who’s top WJC/U23 result is between 16-20 are more likely to stop pursuing an international racing career as their results have signaled that they won’t be successful.  The only ones who do continue are the ones who beat the odds and see some measure of success.

Another interesting aspect of these data is the evident plateau effect between ages 20-23.  Notice how many of the blue trend lines flatten out suddenly at these ages.  More so with the women, but we see it in the 11-15 and 16-20 groups for the men as well.  What might be causing this?  My best guess is that it’s another artifact of selection bias.

My guess would be that the ages 20-23 are crucial for deciding whether you’re going to be a successful international ski racer.  Athletes steadily improve up to that point and then have a decision to make.  Do I continue racing or hang up my skis and go to school, get a job, get married, have kids, etc.?  The plateau in the trend lines may come from those athletes that stop improving between those ages.  These athletes are likely to stop pursuing a serious racing career (or at least many of them do).  The ones who continue are, by necessity, the skiers who end up achieving some measure of success.

That’s why we often see this dramatic improvement from ages 16-20, a plateau from 20-23, and then continued improvement from 24 on.  It’s important to realize that this doesn’t mean that if you somehow push through ages 20-23 regardless of how much success you’re having, that somehow you’ll magically get faster simply by passing the age of 23.  The trend lines simply reflect the individual decisions different athletes are making about their likely future success.  I’d guess that a similar plateau effect is happening in the men’s 1-5 and 6-10 panels, but we don’t see it because it’s happening to a much smaller fraction of the athletes, so the trend line isn’t picking it up.

Now let’s look at what’s going on with the Americans.  Kris Freeman, Rob Whitney and Noah Hoffman are the only Americans in the men’s 1-5, 6-10 and 11-15 panels, respectively.  Each of the other red trend lines are based upon multiple athletes.  For example, the red trend line in the women’s 1-5 panel is based upon Liz Stephen and Morgan Arritola.  The truly bizarre looking red trend line in the women’s 6-10 panel is based upon Kikkan Randall, Nicole DeYong, Taz Mannix and Kristina Trygstad-Saari.  Both Randall and DeYong have significantly improved their distance results of late, which accounts for the line bending down suddenly past age 25.

Kris Freeman has been more or less “typical” for those athletes achieving a top result at WJC/U23s.  Rob Whitney had a very promising beginning, relative to his peers, but encountered some serious difficulties around age 22-23.  Noah Hoffman seems to be tracking the trend for his peers, or perhaps a bit better.

The most important thing I want to emphasize in these data is how variable they are.  Generally speaking, of course, it’s better to have good results (not just at WJCs, all the time!).  But if anything, this graph indicates just how crude a predictor WJC/U23s can be for future success on the World Cup.  There are plenty of athletes who’ve landed top results at WJCs but haven’t gone on to do much else.  Conversely, there are plenty of skiers who never cracked the top 15 at WJCs but ended up having a very long and successful career.  There are, as in the rest of life, many different paths to success.

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U23 Pursuit Recap: Women

Just a quick follow up to my earlier post examining some of the North American men in today’s U23 pursuit, this time for the women. I’ll just focus on three ladies: Sadie Bjornsen, Caitlin Patterson and Alysson Marshall.

Here’s the graph for Bjornsen:

Difference in % back between Bjornsen and the field.

Today’s race (blue) seems neither much better nor much worse than she’s performed against this group of skiers this season, although most of the data from earlier this season is comparing her to other North Americans.

Caitlin Patterson has somewhat less data for me to use, so things here are a little murkier: Continue reading ›

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U23 Pursuit Recap: Men

As before, with the U23 racers we typically have more data to work with, since these folks have generally been around longer and so are likely to have raced against each other more often. We’ll continue using the percent back difference plots, that examine how a particular skier has fared against each of their competitors in the past. So let’s get a sense for what some of the North American performances mean, starting with Alex Harvey:

Difference in % back between Harvey and the field.

Harvey was certainly a favorite to win coming into this race, given his strong results on the World Cup this season, and he didn’t disappoint. Today’s race is in blue, with the median from today’s race in red and a red trend line to give you a sense of how his performance against these particular skiers has changed (or stayed the same) over time. What this graph suggests is that his victory today wasn’t an unusually good or bad performance for him; it also suggests that the folks today that he’s raced against before he’s almost always beaten.

Moving on to Noah Hoffman: Continue reading ›

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Animated WC Points Tracker

A little fun using the Google Charts API, R and my WC points spreadsheet. Both of these motion charts require Flash.

It shows the progression of WC points for the top 30 athletes or so throughout this season. Distance points are on the x axis and sprint point are on the y axis. This does not include the “general” points awarded for overall stage wins. My main complaint about the way they implemented this is that I can’t find a way to exert finer control over how the time steps proceed. This results in the appearance of WC points accruing slowly over several days in a lot of cases, when really the dots should remain perfectly still in a lot of those cases. (Or maybe I’ve just messed something up, I’ll keep working on it.) Men first and then the women. Other than requiring Flash, I’m not sure how these will react to various browsers; at the very least they may load somewhat slowly on occasion.

There are various menus and options you can play with, including the ability to select some specific people and having their dots leave a trail as they move.




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