Python on Bitfern

Can an AI algorithm win fantasy football?

Wed, 27 May 2015 11:11:01 +0000

If you’ve heard the term Moneyball, then you’ll know that in 2002 the Oakland ‘A’s Major League Baseball team began to use statistical analysis to identify and sign undervalued players, in order to compete against their richer competitors. The approach is credited with getting them to the playoffs in both 2002 and 2003 and has since been adopted more widely.

In the football world, Brentford FC are reportedly embarking on a similar journey using the data-driven approach proven at their Danish sister club.

Intro to HTQL with Python (2)

Sat, 20 Sep 2014 03:18:07 +0000

Following on from part 1, here is an example of using HTQL to pull data from a table on a webpage.

We’ll use the Wikipedia list of most expensive football transfers as our source web page. You can check out the list here. On viewing the page and the HTML source you’ll see that the first row of the table is a header row and that the “player”, “from” and “to” columns contain quite a bit of HTML in order to provide a link to the player/team and a graphical link to their country. Our HTQL will need to cut through this to just get the data that we want.

Intro to HTQL with Python (1)

Sun, 07 Sep 2014 07:03:11 +0000

HTQL – Hyper-Text Query Language – is a language for querying and extracting content from HTML pages. If SQL is a language to get data from tables within a database, then HTQL is a language to get data from webpages on the internet. It is useful when you need to pull data from the web and there is no web service available to use. An example might be to pull population statistics from Wikipedia.