Fantasy Football Articles & Model Guides

“Upside” gets tons of talk for drafting strategy. I wanted to dig in deep and find out where to find it. I’m analyzing “where to find Upside” on 2 parameters, in this study: (1) Fantasy position (QB/RB/WR/TE) and (2) Dra

Introduction Here’s some analysis that might help your thoughts on strategy, even in the off-season. The theme of this post is "How predictable/random are the different fantasy positions?" (During the 3 years 2017-2019,

Every year I see different people attempting to make a statistical model of some kind. In 2018 there were 8 of us providing D/ST rankings... and nearly all of us had a different approach. What I'm writing here is a 2- or

I program algorithms in Mathematica, to develop models while working very closely with the data. Updated models are then programmed into Excel for day-to-day implementation. If I were younger and trained specifically in

D/ST is where I started, due to a slew of bad picks from other rankings. I thought rankers were assuming that certain statistics were predictive, without testing them. I was especially frustrated about the inability to i

Subvertadown models are built from a special version of multivariate statistical regression, with cross-validation. That means we don’t choose our favorite defensive stats from our own idea of what should be useful. Inst

Although I heavily guide the process, I don't choose what ends up into each model. Subvertadown is about a framework for developing the predictive models. For this, I test hundreds of variables for significance, and cros

I have always said that the kicker position is where I hope to make the biggest improvement. Kickers get overlooked, so there is room to improve accuracy—which in turn makes it viable to maximize points by streaming (ins

I originally did not expect the time intensity involved with creating and maintaining models. At first, I thought some clever tricks could find patterns and quickly “crack the code”. Unfortunately, I learned there are hu