Brexit, Bremain, the world did not end so dataviz people can throw shade and color
Dot plots are under-valued, that's all

Lining up the dopers and their medals

The Times did a great job making this graphic (this snapshot is just the top half):

Nyt_olympicdopers_top

A lot of information is packed into a small space. It's easy to compose the story in our heads. For example, Lee Chong Wai, the Malaysian badminton silver medalist, was suspended for doping for a short time during 2015, and he was second twice before the doping incident.

They sorted the athletes according to the recency of the latest suspension. This is very smart as it helps make the chart readable. Other common ordering such as alphabetically by last name, by sport, by age, and by number of medals will result in a bit of a mess.

I'm curious about the athletes who also had doping suspensions but did not win any medals in 2016.

Comments

Ken

I think there were about 100 athletes with past doping, so about 70 didn't win medals. However you look at it, the dopers did much better than the average athlete with 30% winning a medal. This may be because top athletes are more likely to be tested but there is a more worrying possibility, that the effects of using steroids are longer term by increasing muscle and muscle type. As a consequence anyone who has used steroids should be outed for life.

The comments to this entry are closed.