The most frequent question I get asked is how can I get started in quantitative analysis when it comes to sports betting or DFS? I often recommend a bunch of skill sets that you need to learn. Among them, learn a scripting language to build web scrapers; learn basic data analysis skills. Typically, I recommend googling around to find information on both. However, for those interested enough, I strongly recommend taking a couple of summer classes from MIT (yes, Massachusetts Institute of Technology). For those of you not in the Cambridge, MA area this summer, the edX series will let you take the classes for free!
edX is one of a growing number of online learning sites. If you're not currently using the internet for higher education, it's time to start. edX partners with prestigious universities to offer quality classes for free. If you want to receive a certificate to impress someone down the line, you can pay $50...but I think the skills you learn will impress the people that really matter. These aren't cake courses...this is the actual curriculum taught at MIT. This won't be easy...but it should be rewarding.
The scripting language I most frequently recommend is Python. Python is extremely flexible and powerful. There are many add-ons that will make web scraping and data analysis very easy for you once you learn them. You can take Introduction to Computer Science and Programming Using Python from MIT beginning May 30. There's still time to enroll. Again, this course is no joke. You need to have some basic knowledge of how computer programming works before you tackle this course. It's a 9 week course and they estimate 15 hours/week of effort. That number will depend on your current computer programming prowess. This won't teach you everything you need to know, but it'll give you a good start to build on via other web tutorials.
Next you'll want to learn some basic data analysis. This course is titled The Analytics Edge and again, it is a real course taught at MIT. The course features applications of different methods of data analysis. If you ever wanted to learn about how to use linear or logistic regression or what tools to use to visualize data, this is a great course. The course will also give you exposure into R, which is a great programming language for analyzing data. Ideally, after these courses you'll gather data in Python and analyze it with R. This is a 12 week course and they estimate 10-15 hours/week of effort. If you've got the time, you can do both at once. However, learning Python and R concurrently may prove to be frustrating.
If you don't think you can cut it at MIT...
If you think this all may be more work than you have time for...and you'd rather approach this at bit more casual pace, here are two alternative classes which I haven't taken or sampled...but looking at the syllabus for each I think will probably provide some useful knowledge with far less effort:
CS For All: Introduction to Computer Science and Python Programming from Harvey Mudd College.
14 week class, 5-7 hours/week. Self-paced class. This appears to be a good choice for someone who might find the whole concept of programming intimidating.
Math in Sports from Notre Dame University.
This course seems to discuss everything from fantasy football team creation to hot hand theory. 8 weeks; 4-7 hours/week. Seems like a pretty easy course.