I kept wanting to check this on my iPad so went ahead and hacked together a cron job and static Google AppEngine site for it. It’s the daily probability that any given team will win the world cup, visualized over time.
Enjoy!
it's not as hard as you think
formerly coderoom.wordpress.com
I kept wanting to check this on my iPad so went ahead and hacked together a cron job and static Google AppEngine site for it. It’s the daily probability that any given team will win the world cup, visualized over time.
Enjoy!
I’ve been having fun looking at the betfair market odds of a team winning the world cup over time. The interesting thing isn’t the wins and losses, although those are very clear, but how they affect the other teams chances.
The vertical axis is the % chance of winning, as predicted by the betfair market after the end of play each day.
In some cases a team wins but their performance was so unconvincing that their chances of winning the title barely increase. Relative to the points they received, they might actually decrease - witness Brazil’s early matches.
Germany goes from strength to strength, the only team that’s consistently impressed so far.
It’s also surprising how few teams are considered to have any worthwhile chance by the market - and these are getting fewer all the time. Judging by the size of the increase seen when the Netherlands thrashed the reigning world champion, the market’s really really convinced that one of the favourites will win.
Of course, I’m hoping England will have found the perfect way to build Rooney into their forward four and will put in a blazing performance tonight. Come on England!
Whether the market is rational and efficient is also interesting, especially if you like writing trading bots. Some of the movements suggest it might not be, but I really need to annotate the graph with match results to make them obvious.
I hacked this together a few nights ago using Python 2.7 (oh, python 3, I’ll start using you one day), Selenium+ PhantomJS (who has time to sign up for APIs?), Chart.js, Chart.js.legend, Linode, Ubuntu, GNU screen, Chrome (I like the profiling chart) and my beloved Vim.
Truly we stand on the shoulders of giants!
Anyone interested in seeing this online?
P.S. If you’d like to rewrite the graphing using something more interactive (d3.js would be my choice) then drop me a line, it’d be fun to collaborate!