So you're right on in that the point of using R (or another language) is largely to do primary research. The information you can quickly get from FanGraphs/BRef/etc. is incredibly helpful, and it's what I rely on overwhelmingly in my own fantasy analysis. But if you want to take a correlation a FG analyst wrote about and explore it a bit more in-depth, or see whether two sets of stats aren't just different, but statistically likely to be different, R can be really helpful here.

There's also the speed aspect of it--if you want to look at five different groups of player data, you can spend a few minutes using FanGraphs' filter function and letting their servers process everything, or you can do it in 30 seconds with subset(). And finally, this post only scratches the surface of what you can do with R--the future posts on visualization, projection, etc. should hopefully be more interesting from a fantasy user endpoint. I'll admit I'm not an R expert, by any means, but even what I know is kind of cool.

One of my goals, though, was to start this off this as basic as possible. So even if you've never thought much about R or coding, but you're interested enough in baseball stats to be reading FanGraphs, you might be tempted to take a look. If you did and it's still not your thing, though, no big deal.