As most of you know, because of my background and training I approach performance analytics in soccer from a more rigorous foundation. (I like doing the back-of-the-envelope stuff as well and manipulating data from various statistical categories, but for many analytics problems that kind of work is no longer sufficient.) To this end, I'm always seeking to expand my knowledge base in applied mathematics and statistics — add more tools to the toolbox, if you will.
To this end, I am posting a link to a Convex Optimization course taught by Professor Stephen Boyd at Stanford University. Stanford has archived videos of the lectures from the 2007-08 Winter Quarter on their website, and you can also retrieve them at iTunes. Stephen Boyd is a legend in optimization research, and I regret not being able to have him for a class while I was a grad student at Stanford (I took his Linear Dynamical Systems course, but he was on sabattical at the time so a postdoc taught it). The material in his course has broad applications to many fields, and perhaps to sports analytics as well.
I should mention MIT's OpenCourseWare as well. They have course syllabi, notes, homeworks, and in some cases, video lectures on a majority of courses offered there. It is truly a treasure trove of knowledge. With respect to material that might be related to sports analytics, I would recommend that material in Mathematics and Business (the lecture notes on linear regression are awesome), but really, it's all good.