Effect of start order on women’s WSC 10k

This topic has been covered elsewhere but I thought I’d add my two cents, and it turned out to be slightly longer than Twitter could accommodate.

A lot of wacky things went on that day, as you’d expect when the weather and waxing are tricky and change dramatically during the race. I haven’t watched the TV coverage of the race myself, so I’m at a bit of a disadvantage here since I don’t have any sense of how things progressed and how the athletes looked except for what I’ve read online.

Basically, it started snowing shortly after the race started, which changed the conditions dramatically. This both made the conditions for later starters inherently more challenging and additionally some nations (e.g. Norway) just flat out missed the wax and had terrible, terrible skis.

So naturally we’re interested in whether we can see direct evidence of this start order effect in the results. My approach is actually quite simple (from the perspective of all the machinery I’ve built up over the years in the form of code written to push skiing data around). I’m just going to take the basic data in the graph I Tweeted earlier and rework it a bit.

The idea in that original graph is that I’m just taking each skier’s percent behind the median skier and showing a rough “confidence interval” for perspective (it’s actually just the 25th and 75th percentile of their races over the previous 1-2 years). It already suggests strongly that a lot of the people at the top of the results sheet had “surprisingly good” races, relative to their prior results, as shown by the gap between the red dot and the horizontal bar. We can just take the difference (scaled by the racer’s inherent level of variability, i.e. the width of their bar) and then plot the results relative to start order.

Voila:

wom_10k_fr

On the x axis, positive values are better than expected results, negative values are worse than expected. There were 4-5 athletes (no one notable) that I dropped entirely since they had so few results for meaningful numbers. The red dashed line is my rough guess-timate (again, based only on this graph; I didn’t watch the race) on where things changed. My placement is rather aggressively toward the back of the field; you could arguably say that between starters 25-40 things had stabilized somewhat, and then finally the conditions had really nosedived after that.

And of course as you would expect the relationship isn’t perfect. There are certainly folks at the back of the field that had good races, for them. But this seems like very strong evidence to me that it was simply a good day to be at the front of the field. Virtually all of those people had good to excellent races compared to their personal past performances.

The usual caveats apply here: this suggests there was an effect, but it can’t tease out the magnitude of the effect on a skier-by-skier basis. Different folks were impacted differently based on the specific wax they had, and how they responded in race to having a great (or terrible) day, in addition to the regular “noise” in athletic performances.

Race Snapshot: Oslo 30/50k Classic

 

oslo_cl_men oslo_cl_wom

Race Snapshot: Drammen Sprints

Men:

drammen_spr_men

Women:

drammen_spr_wom

Race Snapshot: Lahti 10/15k Freestyle

Men:

lahti_fr_men

Women:

lahti_fr_wom

Race Snapshot: Lahti Freestyle Sprint

Men:

lahti_spr_men

Women:

lahti_spr_wom

US Olympic Assessment

So, how did the US do overall at the Olympics this year?

Well, as usual, I’m going to mostly ignore the team events. As I did before, here’s some historical context for our results this time around:

us_sochi_grade

 

That’s all WSC and OWG results for Americans stretching back to 1992. It’s still kind of hard to swallow the women’s sprint results as a significant improvement, but there you go.

The men’s and women’s distance results both ticked slightly in the wrong direction. However, my suspicions held true and the women continued their steady improvement at the low end. The men are really just in a holding pattern. Basically nothing has changed on that front for about a decade, really.

A friend phrased the question to me in terms of a grade. Personally, if I’m being objective, I’d give the results a B+. Kikkan’s sprint race was a huge disappointment, to be sure, but four women in the top twenty is still quite good and we did put Sophie in the finals. Liz could certainly have had a better 30k, but beyond that I don’t really think anyone significantly under-performed in the distance events compared to what I expected, or thought was reasonable.

On the other hand, (and it’s very hard for me to say this publicly, because Kikkan Randall has been nothing short of revolutionary for the US skiing community), I find it hard not to consider these Games a pretty huge disappointment. But that’s my heart talking, not my head.

Race Snapshot: 30/50k Freestyle

Men:

sochi_fr_men

Women:

suchi_fr_wom

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