Race results are often given in tables of data that are none too interesting, and a little hard to do much with for anyone wanting to know some things from it not given as part of the results. I recently did some visualization and analysis with some traditional running race results, on Tableau Public software as a self-learning exercise, to show how running race results could be presented in a feasible manner of a few hours’ work now that a model has been created. I’d show it here except I’m not able to use JavaScript on WordPress to embed it. However, you can see what I mean through these links.
- 2017 Dartmouth Natal Day 6 Mile Road Race results visualized and analyzed
- 2017 Dartmouth Natal Day 2 Mile Road Race results visualized and analyzed
- 2016 Dartmouth Natal Day 6 Mile Road Race results visualized and analyzed
- 2016 Dartmouth Natal Day 2 Mile Road Race results visualized and analyzed
Aside from the visuals, play around with the selection menus that are like filters to get customized results. Highlight certain groups of runners among that. Select by division, geography of where runners call home, among other customization. Hover your mouse cursor over dots, bars and such, to see much more information about what they represent. You can also select dots, bars and such to highlight them. It is called “interactive” for a good reason, you know! π
If you want a description of what each dashboard was for, and to see what I saw in some of the results, you can read a long blog post about the 2016 6 miler race results here.Β It is long because not am I trying to describe 15 pictures, I’m trying to tell you what’s in each! It’ll serve as a tour guide in the future for these things, should I need to refer to it later.
I chose the Dartmouth Natal Day road races because they were recent, local to me and popular among runners I know. I did the two distances to see the effort required to change parameters for difference race distances, which involve different times. Then I did last year’s races to see the effort required to swap in very similar data sets.
It takes about a couple of hours to replicate what I have above for another race. While it is interesting, I’m not sure anybody would care much for it. However, I have a concept to show here that this is what racing results could feasibly look like today, rather than just rather blah tables of data which are usually presented. I created the sets of interactive dashboards above with only the raw data of a typical set of race results, without a split time, even! Maybe one day, when this can be even more automated, it could be visible that running race results could all be like this!
Stay tuned for something similar for marathon results, with a split time to add new dimensions for analyses, like how did individuals and the field run their second halfs compared to first halfs, and what were the placing change consequences from the half way point to the final ending! π