Yesterday I showed which players were 2016’s most- and least- efficient pass catchers from the perspective of yards per target over expectation (YPTOE). YPTOE situationally adjusted a player’s efficiency based on down, distance, and yard line. Today, I will depth-adjust those numbers, because not all passing depths are created equal.
Last offseason I introduced my metrics YPCOE and YPTOE, which stand for Yards Per Carry/Target Over Expectation respectively. I used them to identify season-long regression candidates for rushing and receiving efficiency, and it successfully identified Davante Adams and Dez Bryant as bounce-back candidates, while also correctly identifying Tyler Lockett and
This weekend’s DraftKings NASCAR Auto Club projections once again included my Sim Score projections. For a primer on those see the primer article.
Last year I created a model to predict quarterback success at the NFL level for prospects. The model was useful in that it helped identify traits that transfer to the NFL level, but it was certainly overfit and didn’t bring in enough data. I’ve updated the model for
rThis weekend’s DraftKings NASCAR Phoenix projections once again included my Sim Score projections. For a primer on those see the primer article.
This weekend’s DraftKings NASCAR Las Vegas projections are amped up. I’ve included my Sim Score projections, which I talked about in the DraftKings NASCAR Las Vegas strategy article. Also, the NASCAR DFS Multi-Lineup Optimizer is updated with the machine learning model projections, and the NASCAR Splits App will help you find statistics
In preparation for the RotoViz Radio 2017 NFL Draft series of podcasts, I was going through some different prospects trying to figure out which running backs had a successful combine. When I was perusing the data, one name jumped out at me for his combine measurables, and when I went
Before we dive into NASCAR DFS strategy for Las Vegas, including the new sim scores I’m introducing, let’s recap Atlanta.
With qualifying and practice over, it’s time to dive into the DraftKings NASCAR Atlanta picks, fades, and model projections. I’ve updated the NASCAR DFS Multi-Lineup Optimizer with the model projections, and the NASCAR Splits App will help you find the statistics for each driver’s history at
Atlanta Motor Speedway is a 1.54-mile quad oval with a 20-year old racing surface. The aged track is extremely abrasive, causing significant tire wear early into a fuel run. Thus, pit strategy often comes into play, which is how Jimmie Johnson took the race win last year. However, this year