Basic Statistical Analysis, Part 1
Let me start this lesson with a couple of disclaimers. Ready? Here we go…
If you are here to learn about ERA, WHIP, and the fun categories that won you a season-long rotisserie fantasy league in 2005, this lesson is not for you. That stuff is ancient history.
Okay, now that I have lost 1% of you, hopefully I can maintain the rest of my faithful readers.
If you are here to learn about how much vertical movement there is on Adam Wainwright curveball, this lesson is probably going to disappoint you. A novel could literally be written about all the intricacies of advanced stats in baseball. After all, baseball is the most statistical-based sport imaginable. Admittedly, this lesson will only scratch the surface. If you are interested in learning more about advanced statistical analysis, especially as it relates to starting pitchers, let me know. That could be an idea for a future course here at RotoAcademy.
Okay, now that I have lost another 2% of you, hopefully I can prove my worth to the remaining 97% of the audience that has stuck with me. This lesson is going to be a basic introduction into how to harness the power of statistical analysis when it comes to evaluating starting pitchers on a particular slate. Of course, examples will be provided to make this a little bit easier to understand. Let’s get down to business.
In this lesson, I am going to break down a few of the more basic statistical measures that you can use to evaluate pitching talent as it relates to daily fantasy options. In the next lesson, I will dig a little deeper into some more advanced metrics. In order to really understand the importance of these statistics, it is at least relevant to touch on some of the “older” measures that I mentioned in the open, so let’s start there.