I took a break today from the retiring skier posts, but they will resume next Friday…
Pete Vordenberg and Bryan Fish have an intriguing post up over at NCCSEF about the FIS point profiles of the top ten skiers in the world. The intention is to give developing skiers a rough tool to use to gauge their progress against the development paths of the best skiers in the world.
The FIS points awarded at any given race, of course, are intended to provide this sort of information, but that’s a comparison to the best skiers in the world right now, not the best skiers in the world when they were your age.
Also note that the term ‘FIS point profile’ means (I assume) the average of an athlete’s best five races over an entire calendar year that is used for generating the FIS point lists used in seeding. (Since this average is recalculated several times a year, I’m not sure which list they used at a given age; I presume they used the year-end list.)
My thoughts, as a stat-head:
Let’s see if we can provide some similar information, geared towards the same purpose, but maybe in a format that’s a bit easier to digest. My version will be different in several respects, but my aim is still to provide a rough guide to where you stand compared to the best skiers in the world at a given age.
Rather than just the current top ten skiers in the world (however you choose to measure that), let’s instead look a bit wider at anyone who has achieved a top ten result in a major international competition (WC, OWG, WSC). Also, rather than looking at an athlete’s best results, let’s look at all the results achieved by top-ten caliber skiers at a given age. Here’s the result in chart form: Continue reading ›
Tagged Analysis, development, fis pointsContinuing on from last time, now we move on to the women’s distance events. We’ll start out the same way, with a basic graph showing the number of results per race for various levels of performance:
The Canadian women built up steadily under the Beckie Scott/Sara Renner days, but haven’t quite found any replacement for these ladies (yet). The American women have generally bounced around flirting with mostly top-30 results, seeing a steady increase in these over the past few seasons. As recently as 2006-2007, the US women didn’t have a single top-30 result in 12 attempts. Since then they’ve progressed all the way to ~56% of their results being ‘in the points’ in 48 attempts. Obviously, Kikkan Randall’s been leading the charge here, along with Liz Stephen and Morgan Arritola.
Kikkan Randall’s 11th place finish at the Lahti pursuit this year was remarkably good. I can find a grand total of 9 top-15 results by US women in WC, OWG, or WSC races since 1992, Randall owns four of them and all of them are either 14th/15th except for this one 11th place. Her FIS points from the Lahti pursuit (50.96) were deceptively high, thanks to Johaug and Kowalczyk skiing away from everyone. If you use standardized percent back from the median skier, that race is, by a healthy margin, the best US female distance result since 1992. In fact, it is one of only two that are more than one standard deviation better than average. Randall scored a -1.33 and the next best result by this measure is Leslie Thompson’s 17th place in a 10km freestyle all the way back in Davos, 1993, which netted her a -1.17.
Here’s a look at some of the individual US women who did international racing this year: Continue reading ›
Tagged canada, Distance, kikkan randall, season recap, USA, womenI think most people generally have a sense for how the past World Cup season went for the North Americans. What I’m going to do over the next few posts is to simply show some data that hopefully provides some context for what you already know. I’m going to split them into four posts for men/women and distance/sprint. Today we’ll start with the men’s distance performances.
Let’s start with the simplest of metrics, finishing place, and a style of graph that I’ve used before that shows the number of results per race at a given level:
What a taxing week I’ve had…
Ha ha. Very funny. (It’s tax day in the US, for you foreign readers.) Thanks once again to Skaði Nordic for sponsoring this week in review:
Several talented sprinters are retiring this year, among them Arianna Follis. While she’s known as a sprinter, her results indicate that she wasn’t a terribly slow distance skier either, particularly later in her career:
This suggests that it’s been the previous four seasons where her distance racing has really been fairly strong, and in fact she seems to be ending her career with perhaps her strongest distance racing season yet. The 2010 race that stands out here is a handicap stage from the Tour de Ski in which Follis, Majdic and Kowalczyk gapped Saarinen in 4th, who herself was over 1.5 minutes ahead of 5th. The handicap start stage races can produce some unusual race tactics, for sure. In fact, her only two distance wins came in handicap start stages, the other in this year’s World Cup Finale.
Her distance results translated into a total of 10 podiums, spread across the Tour, WC and one WSC Bronze. All of these came in freestyle or pursuit races, so the following graph is only partially surprising: Continue reading ›
Tagged arianna follis, retirment, retrospectiveLast time we tackled the question of ‘home snow advantage’, but only for distance events. The methodology I’m going to follow for sprinting is nearly the same, though obviously we can’t use the same performance measure. I’m not going to repeat myself much, so go back and read Monday’s post if you think you need a refresher.
Instead of basing our measurement of performance on standardized percent back from the median skier, we’ll simply use rank, i.e. finishing place. This is crude, but there aren’t a lot of good options with sprinting. One nice thing about this, though, is that the results will be more easily interpretable, since the estimated (dis)advantage will be as a change in rank.
One other thing is different here. Unlike my percent back based measure, rank has a hard lower bound. You can’t place any better than 1st. This suggests that we should transform our measure into a proportional change in rank, or something like that. The hope would be that this would allow us to more easily detect a ‘home snow advantage’ in a skier who is already generally quite fast.
I tried this and the results were….disappointing. Whenever I fit a fairly complicated model like this, I make sure to go back and check that the results make some amount of sense. In this case, when compared to the skier’s actual race results, the model performed very poorly and gave rather nonsensical results. The skiers and nations it identified as having relatively large discrepancies between there home and away sprinting simply did not match up with their actual results. One option would be to do the proportional change in rank adjustment on the estimates themselves, after fitting the model. This is tricky, though, if you want to avoid assuming athlete’s performance levels are constant over their careers. I’ll let you know if I come up with a solution…
On the other hand, not using a proportional change in rank worked quite well. This is fine, as long as we keep in mind that what we’re modeling isn’t exactly what we’d like to, but it’s close. Having done my due diligence of checking this model, it is doing a decent job of picking out skiers and nations with genuine discrepancies between their home and away sprinting, but it will likely be biased. Specifically, a skier who tends to ski 2 places better at home than away will be treated the same whether that movement was from 20th to 18th or 4th to 2nd. So we’re more likely to identify skiers who aren’t always in the top 6 or so.
With that warning, here are the five skiers with the biggest home vs away splits in each direction: Continue reading ›
Tagged Analysis, home snow advantage