More Tour de France Data Visualizations
JunkCharts was nice enough to feature the Tour de France charts I’ve been playing with as a break from skiing data. I learned via one of the commenters there that (unsurprisingly) I’m not alone in this game. See here for a handful of similar charts, including ones from previous years.
Which Tour Stages Have The Biggest GC Shakeups?
My good friend, and general cycling expert, Cosmo recently tweeted about what he perceived as more GC (overall ranking) shakeups taking place in Tour de France stages with a downhill finish as opposed to uphill, mountaintop, finishes. He then followed that up with a comment to that effect, linking back to my bumps chart as evidence. Those charts do shed some light on this question, but if you read my first response I hedged a lot, since trying to visually assess which stages have the most jumbled, tangled lines in the bumps chart isn’t an exact science.
Of course, nothing I do here is really an exact science, but at the very least I owe Cosmo a better look at the data. I’ll leave it to him (and others) to say what it means vis-a-vis mountaintop versus downhill finishes. Read more
Tour de France Bump Chart: Stage 16
Another couple stages in the books, time for an update of the bumps charts. Contador’s still in yellow, Hushovd is back in green and Chartreau is still in polka-dots: Read more
Statistical Skier: 1, SVG: 0
Take that vector graphics animation! For an explanation, see my previous effort.
Reminder: This should work in Chrome, Firefox and Safari. But consider it experimental. Reloading the page should restart the animation. I confirmed that this won’t work in Firefox, and that the one SVG plugin for Firefox has been discontinued by Adobe (although apparently it relied on ActiveX, so maybe that’s a good thing). So Chrome, Safari and probably Opera are your only options.
Actually, this is a hack. The translational arithmetic that was being used by the code I grabbed was, well, opaque. Once I got it to push the actual names of the teams around, it became clear that all the translations were off by some mysterious, unknown scaling factor. Trial and error solved that problem pretty quick, but the solution is just based on eyeballing the graph, so this is certainly not exact.
I wonder what sort of skiing data I can animate…
Stand Back! This Graph Is Alive!
This was just too cool for me not to put up on the site, even though I’m not completely happy with it. The data are fairly simple: add up the sprint and mountain points across all riders on a Tour de France team for each stage. So for each stage, each team gets the ordered pair (mountain points, sprint points) where the points are cumulative.
The cool part is that I’ve managed to get it animated, so you can watch the team’s progress through the Tour. The bad news is that the animation tools I’m using are apparently limited to pushing dots around a graph. Otherwise I’d actually plot the team names and animate them. As it is, you’ll have to wait for the animation to end and then mouse over the dots to get the team name. (Unless you have stupendous hand-eye coordination and can hold your cursor in the same spot on a dot for several seconds while it glides around.)
Another hiccup is that you’ll notice sometimes the dots move down or left, which would indicate that a team lost points that stage. Actually what’s happening is that team lost a rider, who either quit or was disqualified. I’m going to treat those as “lost” points unless some cycling expert instructs me otherwise.
This should work in Chrome, Firefox and Safari. But consider it experimental. Reloading the page should restart the animation. Ok, I confirmed that this won’t work in Firefox, and that the one SVG plugin for Firefox has been discontinued by Adobe (although apparently it relied on ActiveX, so maybe that’s a good thing). So Chrome, Safari and probably Opera are your only options.
The truly glorious part (to me) is how little code this required. There’s a little bit of work shuffling the data into the right format, but once that’s done this is all I needed to do in R:
doc <- svgPlot(plot(sprint~mountain,D1,xlab="Mountain",ylab="Sprint",xlim=c(0,300),ylim=c(0,350),pch=20))
addToolTips(doc,levels(pts_merge$team),addArea=2)
animate(doc,data=D,which=D$stage2,dropFirst = TRUE,begin=0,interval=3,labels = levels(pts_merge$stage))
saveXML(doc,"tdf_animation1.svg")
Sweet!
Tour de France Team-Nationality Guide
If you’re like me, you follow bike racing enough to grasp the basics and be familiar with most of the big names. I’ll typically follow the TdF fairly closely, but other than that my cycling news consumption pretty much consists of whatever cool stuff Cosmo happens to write about.
That means that when the TdF does roll around, I’m embarrassed to admit that I have a hard time keeping the different teams straight. They all have funny names built around foreign companies and people will often just abbreviate them. And of course every few years, the sponsors change and so do the names. Keeping track of which riders are on which teams is a bit much for me, but a more manageable goal is to have a rough sense of what countries the riders are from on each team.
Like everything else I do around here, that calls for a graph:
Yeah, Euskaltel-Euskadi being Basque only I can remember. But there are always a bunch of “French” teams that just sort of blend together in my head: AG2R, FdJeux, Cofidis and Bbox Bouygues Telecom (Seriously? Bbox?).
Ok. Lampre is primarily Italian, Milram is mostly German and Footon-Servetto is mostly Spanish. Astana and Caisse d’Epargne are also mainly Spanish, but less than Footon-Servetto and Euskaltel-Euskadi.
Quick Step, Rabobank and Katusha are Belgian, Dutch and Russian. From here immigration policies apparently get considerably looser. Saxobank (not to be confused with Rabobank, dammit!) has a plurality of Danes.
Liquigas and Omega-Pharma-Lotto could be considered Italian and Belgian, but their immigrant populations are quite high: nearly half the team.
Then we have the open borders club. The remaining teams have a plurality of riders from nations like GBr, USA and Aus, but are generally quite diverse.
Is this all a bit silly? Maybe. But it helps me keep the teams straight in my head, at least a little.
Tour de France Bumps Chart: Stage 14
So I decided that updating these every day would get tedious. Here’s the standard bumps chart after stage 14 and the corresponding average speed bumps chart is below the fold:
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