Here are some highlights:
You'd notice a similar pattern in 2010 as in 2007. The yellow jersey pretty much stays in the front of the pack throughout... the green jersey (sprints) eventually fades away while the polka dots jersey (mountains) improves as the tour continues.
From the design perspective, one decision concerns whether the colored lines track the jersey or track the current owner of the jersey. Over the course of the tour, jersey change owners, possibly multiple times. What to do?
Notice that the top of the chart slopes downwards, and that is due to withdrawals of riders during the course of the race.
In the second chart, Joran brings this out by tracking each withdrawn rider until the stage they dropped out, and we can see their then ranks when they faltered.
This shows good use of foreground/background to bring out aspects of the data. In the original post, when you mouse on the red dots, a label appears showing the name of the rider.
In this next chart, a small multiples format is adopted, with the riders from each team plotted together and each team in a separate plot. This allows us to see the relative performance easily. Joran tried using one plot, and many colors -- and not surprisingly, discovered that the resulting chart is unreadable. The small multiples format is a solution to this problem.
As someone not too familiar with the race, I find the high variance of the ranking within each team to be unexpected. Can't explain why this would be. In particular, even when a team (Saxobank) has a highly ranked cyclist, it's interesting that the other members of the team are much lower ranked. I thought that team members try to cluster together and protect the team leader. Well, you may be able to make more sense out of this than I can.
I think these charts are ranked alphabetically by the name of the team -- I'd order them by the rank of the leading cyclist of each team.
Another improvement is to label the stages as Mountain vs. Sprint. This can be done by coloring the column for the respective stage... sort of like those economic charts where they color the periods of recession. This helps explain what we are seeing, why some riders achieve drastic improvements (or reductions) in ranks over some stages.
What is clear is that having domain knowledge is an important asset to making good charts. Research is key. This is something Joran also realized, and it's useful to read his commentary about the issues of interpreting the data, being able to recognize typos, etc.