We began with the candidates ranked No. 15 through No. 11. In that article I presented an evidence-based methodology for finding RB gems in the middle and late rounds. We then continued our countdown with No. 10 through No. 6 and found three rookies with a chance to pay immediate
One of the cool things about the new composite projections we’ve been working on is it allows us to sort the players by rank in a given category. Even cooler, we can sort players by the difference between their ADP and projected finish to see who are the biggest bargains
I like to build my draft board taking into account a variety of evidence-based approaches. In trying to determine picks at the very top of the draft, this means making sure as much evidence as possible points in the same direction. For this study, I wanted to use the RotoViz
I think the Similarity Scores App is pretty amazing, and it tends to get overlooked around here, among all the other great tools and content. I recommend you read this post by The Douche, which tells you everything you need to know about how the app works. But here’s the
A few years ago, I played a handful of Draft Champions leagues through the NFFC using Zero RB. I came out slightly ahead and felt like Zero RB would certainly work in the draft-only format. But I also came out thinking that the opposite approach would work better.
I recently published lists of seven running backs to target in MFL10s and six RBs to avoid in MFL10s, but neither list contained a single rookie RB. That does not mean that I am ambivalent on the matter. If I’m good at anything, it’s having an