I learned a lot about baseball and the Python language. Thank you for the great course.

An excellent way to develop Python skills to interesting topics.

Good

Some baseball concepts are complex for european people. But the content of the course is really interesting and very well explained.

I could not have been more disappointed in this course. Its lack of depth, both mathematically and from a sports analysis perspective, shocked me. This course spends almost no time at all on WHY any of the statistics presented are used. Nor on how to develop models to evaluate sport performance. Rather, it focuses almost entirely on prescriptive steps on how to calculate basic stats models. And, given all the time that is spent just walking through the code, one might expect that it is instructive and well-written. Sadly, that is not the case. The code for the course DRAMATICALLY under uses the power of the libraries included (Pandas and Numpy). Effectively, the first 4 weeks of the course are just tediously walking through dozens of convoluted lines of code, to do something that could have been 2 lines by simply using Pandas built-in functions.

So, if you are interested in learning about statistical analysis methods for sports, you can literally watch the first video from week 5 and get 95% of the value of this course without having to slog through 4 weeks of (badly) coding up basically 2 regressions, only to prove that when two different people do the same math, they will arrive at the same result.

If you are interested in learning how to use Python to do sports analysis, AVOID THIS CLASS COMPLETELY!! The lectures contain no information about how to apply any of what’s covered to anything outside of the one example given. AND, the code is so needlessly convoluted, it’s clear that whomever wrote it did NOT know how to use the tools available to them. So, if you are newer to Python, this course would be a little like trying to learn how to cook in an Italian style, by listening to someone read a recipe for canned spaghetti.