Fantasy Football Articles & Model Guides

I got a lot of requests to analyze kicker streaming. So I crunched a whole bunch new simulation programs, to try and find out whether it's better to hold or stream kickers. There were some mixed inputs from discussions h

In 2022, I started using my weekly game score forecasting models for a new purpose: generating advice for Survivor Pools. What’s different about the Subvertadown Strategy? Main features: The main input is from my own for

As covered in my Survivor strategy article, my algorithms seek to optimize the expectancy value of “#weeks survival”— in other words, the Expected Longevity. The meaning of that figure is easy to explain: it is the avera

Here’s a mathy post to improve your understanding of the game, with a stats breakdown that I had searched for but never found. The goal is to give some perspective on how predictable / unpredictable fantasy is, in order

Fantasy point distributions One way to visualize a position’s impact on your roster score is to look at the distributions of scores. (The below curves have been smoothed within 1 point.) It is also interesting to see the

Before this study, I was not completely convinced QB streaming was usually a good idea. Below I discuss some of the arguments and counter-arguments for streaming (vs. drafting+holding). TL;DR Of course I hope some of you

This post is about exploring how well projection models might improve the points we get from the QB position. Plus some commentary exploring how predictable/unpredictable QBs are. Some key questions were: What's differen

In extension of my "QB-Kicker Pairing" analysis, here is a look at all the fantasy positions. Why is this interesting? Especially for critical matchups, people often ask about the effects of using players from the same t

While making all my kicker model improvements, I have had my eye on this particular accuracy number. A correlation coefficient of 0.3 is sometimes considered an unofficial "cut-off" for what is reliably predictable. You'

Here is an illustration of how random fantasy football is. It is a high level view of the predictability of different football-related and fantasy-related variables. Kind of a summary of my research, with a good deal of

What factors of kicker performance are predictable-- and what is not? Fantasy kicker scoring is most of all linked to the production of field goals. I have made an analysis of different components, and how strongly they

The idea of focusing on this specific position pairing (QB+Kicker) was partly based on columns I had read years back (one example is here). For some time, I've been wanting to investigate this methodically, and I hope yo

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

Randomness of Spreads: expected values vs. outcomes One of the "a-ha moments" for me was realizing how much error betting lines have, relative to results. You should pretty much expect Spreads to be wrong by 10 points ab

Randomness of O/U: Expectations vs. outcomes of game Total Totals are more random (harder to predict) than spreads: Interesting side note, that the O/U error is not centered at the mode, and there is a longer tail of ove

This is a reference for those of you who are: Wondering how much trust to put in accuracy grades (either from FantasyPros or from here on Reddit) Trying to make your own accuracy assessment of different ranking sources O

The point of this post is that I've put a lot of thought into making stats more understandable for fantasy. The focus here is correlation coefficients (CCs), which I often use to describe both positional predictability a

Explanation of Overfit (Cause of recent model updates) Some of you requested me to describe what is "overfit". So here's ...really probably... more than you really wanted to know! Anyway, I hope like 3 of you out in the

One of the deviously fun parts of developing predictive models is the feeling of defying what they said about stats in school: Correlation is not causation. With predictive modeling, we turn the idea on its head and bend