Before diving into any of the several topics of discussion and analysis regarding my previous work in clustering NFL receivers into "receiver types," I realized I would first have to figure out just how many receivers could be reliably categorized. In addition to player size, my clustering model uses player target depth and location (per …
Last fall, I used my first exposure to generalized linear models to answer a few questions regarding NFL receiving production. Some of those analyses never quite made it to this blog, but the first that did was an attempt to predict which rookie wide receivers would eventually break out. Beyond understanding the theory underlying the …
Continue reading Predicting breakout NFL rookie receivers (Update)
For the last five years (four of which have been at Dynasty League Football), I have 'scouted' NFL Draft prospects at the offensive skill positions, primarily running back and wide receiver. I use the term generously, but almost anyone who watches as much receiver play as I have in that time takes note of the …
Continue reading Using clusters to better understand and distinguish NFL wide receivers
Previously, I have written about my analysis that uses generalized linear models to predict whether rookies entering their first year will ever have "breakout" seasons. In that case, I used a logistic model, and because logistic models are cool (or, because I am investigating a similar question), I will do that again today. This article's …
It is 2019. If you are plugged into the online dynasty fantasy football community at all, you probably know that: Receivers with strong draft pedigree are more likely to be successful Receivers with strong production in the passing game in college are more likely to be successful, especially when considering context Receivers with strong athleticism …
Continue reading Predicting WR production with generalized linear models, part 1 – Breakouts
This article is an installment of a series in which I use my Observational Rushing Numbers (ORNs) to shed light on just how good the 2017 rookie running backs were at carrying the ball. You can find each previous article about these numbers on the series’s hub. If this is your first time reading one of these, please, …
This article is an installment of a series in which I use my Observational Rushing Numbers (ORNs) to shed light on just how good the 2017 rookie running backs were at carrying the ball. You can find each previous article about these numbers on the series’s hub. For different reasons, plenty of 2017's top-drafted rookie backs struggled. Christian …
This article is an installment of a series in which I use my Observational Rushing Numbers (ORNs) to shed light on just how good the 2017 rookie running backs were at carrying the ball. You can find each previous article about these numbers on the series’s hub. To this point, none of my articles have claimed …
For the rest of my ORN content, visit the series's hub. Before fully kicking off this summer's continuation of my rushing study, I've got to get some things out of the way. The first, and simplest, of them is to make this whole thing more accessible. A new name! Above other things, improving that approachability …
When I began this series last offseason, I was frustrated that I couldn't watch more backs, and in turn have a larger sample to speak from. I only got to watch over 200 carries for 10 players, all of which were in the good-to-great running back tier. As a data addict, it bugged me that …
Continue reading Steve’s Rushing Study, Part Five: Offseason steps
twitrsports 