Search Results for: models and metrics

jalin hyatt

Jalin Hyatt: Where Fantasy and Reality Diverge

One of the most respected draft experts, Lance Zierlein, set off a Twitter firestorm this week when he placed Jalin Hyatt as his first wide receiver off the board, 12th overall, in his first mock draft.

He states:

“Let me first start off by saying I believe this draft is very similar to the 2016 draft in terms of wideouts. I didn’t see any WR as a true WR1 for a team. Here was how I graded them. Obviously, Mike Thomas ended up being a dude but the rest? Here is how I had it (old scale)”

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Using Regression and Neural Networks To Predict Fantasy Football

Modeling is the most powerful and underutilized tool in how we as a population analyze and understand football. Often I see people use metrics to try and understand/predict football. They use these metrics individually to understand small segments of a grand picture. For instance, one popular metric I see used is Market Share (MS), but …

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kirk cousins

Big Money Leagues vs. Small Buy-ins

Welcome back, DFF family! On the docket today, I wanted to discuss Dynasty strategy as it pertains to buy-in size. Dynasty leagues have differing annual dues, so strategy should be tailored to the specific buy-in cost of each league. “High stakes” is a relative term. I consider this to be annual dues of $100 or more. For others, this may be $50, $250, $500…you get the point. However you categorize your small buy-in vs. big money leagues is fine. The purpose of this article is simply to get you thinking about how strategy should change depending on the buy-in requirement each season. Many fantasy owners take the same approach for all the leagues they play in, which is not necessarily wrong, but I choose to go about things differently. Let me explain what I mean. 

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The WR1 Wide Receiver Prospect Model Ratings

For those new to the WR1 rating, this is a highly accurate proprietary forecasting formula I developed to provide a data-driven forecast of future dynasty value for incoming rookie wide receivers. The WR1 model scores rookies on nine predictive metrics and then combines those individual metric scores into a single WR1 rating. The goal is to provide a single easy-to-use score for those who don’t want to spend all the time dissecting different metrics. 

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Josh Downs WR North Carolina NFL Draft Scouting Report

’23 Rookie WR Analytics Spotlight Series: Josh Downs is That Dude

When analyzing wide receiver prospects, analysts such as myself, like to check boxes when a player eclipses a designated threshold for a certain metric. No prospect in this class checked more of these boxes across all metrics than Josh Downs. Downs was an uber-producer during his time at Chapel Hill. When Sam Howell or Drake Maye needed a big play, Downs was the unquestioned target. In this article, I will take you through the numbers and display why you should be targeting Josh Downs in your dynasty rookie drafts.

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Jaxon Smith Njigba

’23 Rookie WR Analytics Spotlight Series: Don’t Overthink JSN

At this point in the off-season, I prefer to write articles on prospects that aren’t in that elite tier so that DFF members have a value-added when reading. After all most have likely heard quite enough about the top prospects in the class to make their decision one way or the other. For that reason, I haven’t done a deep profile on Jaxon Smith-Njigba. In my mind, he is a no-brainer prospect. 

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The WR1 Rating Dynasty Rookie Wide Receiver Countdown (Post Draft Update): Part 2

For those new to the WR1 rating, this is a proprietary formula I developed to provide a data-driven forecast of future dynasty value for incoming rookie wide receivers. The WR1 model scores rookies on nine predictive metrics and then combines those individual metric scores into a single WR1 rating. The goal is to provide a single easy-to-use score for those who don’t want to spend all the time dissecting different metrics. 

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The WR1 Rating Dynasty Rookie Countdown: Part 2

For those new to the WR1 rating, this is a proprietary formula I developed to provide a data-driven forecast of future dynasty value for incoming rookie wide receivers. The WR1 model scores rookies on nine predictive metrics and then combines those individual metric scores into a total WR1 rating score. The goal is to provide a single easy-to-use score for those who don’t want to spend all the time dissecting different metrics. 

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The Pre-Draft WR1: Prospect Model Ratings

For those new to the WR1 rating, this is a proprietary formula I developed to provide a data-driven forecast of future dynasty value for incoming rookie wide receivers. The WR1 model scores rookies on nine predictive metrics and then combines those individual metric scores into a single WR1 rating. The goal is to provide a single easy-to-use score for those who don’t want to spend all the time dissecting different metrics. If data-driven rankings are not for you, I suggest my colleague @DocFFFN’s wide receiver review from a film perspective. 

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Against The Spread: Week 14

What is up DFF Army? It’s that time of the week for us to provide some insightful Week 13 suggestions. Although new information always causes us to reconsider things, we now have enough information to drive decision-making. As we discover trends through the season we will be able to make more determined analyses on specific picks. To go along with matchups and trends, we will look at key fantasy players who have the most beneficial or detrimental matchups.

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Against The Spread: Week 13

What is up DFF Army? It’s that time of the week for us to provide some insightful Week 13 suggestions. Although new information always causes us to reconsider things, we now have enough information to drive decision-making. As we discover trends through the season we will be able to make more determined analyses on specific picks. To go along with matchups and trends, we will look at key fantasy players who have the most beneficial or detrimental matchups.

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Against The Spread: Week 12

What is up DFF Army? It’s that time of the week for us to provide some insightful Week 12 suggestions. Although new information always causes us to reconsider things, we now have enough information to drive decision-making. As we discover trends through the season we will be able to make more determined analyses on specific picks. To go along with matchups and trends, we will look at key fantasy players who have the most beneficial or detrimental matchups.

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Against The Spread: Week 11

What is up DFF Army? It’s that time of the week for us to provide some insightful Week 11 suggestions. Although new information always causes us to reconsider things, we now have enough information to drive decision-making. As we discover trends through the season we will be able to make more determined analyses on specific picks. To go along with matchups and trends, we will look at key fantasy players who have the most beneficial or detrimental matchups.

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Against The Spread: Week 10

What is up DFF Army? It’s that time of the week for us to provide some insightful Week 10 suggestions. Although new information always causes us to reconsider things, we now have enough information to drive decision-making. As we discover trends through the season we will be able to make more determined analyses on specific picks. To go along with matchups and trends, we will look at key fantasy players who have the most beneficial or detrimental matchups.

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Against The Spread: Week 9

What is up DFF Army? After a week off due to a Nor’Easter shutting down the power in Massachusetts for most of the week, we are back to provide some insightful Week 9 suggestions. Although new information always causes us to reconsider things, we now have enough information to drive decision-making. As we discover trends through the season we will be able to make more determined analyses on specific picks. To go along with matchups and trends, we will look at key fantasy players who have the most beneficial or detrimental matchups.

A Guide to Creating Your Own Fantasy Database

After consuming fantasy content, do you find yourself keeping fantasy notes on your phone? Do you bring your own personal rankings to your draft? Are you making spreadsheets for important stats as you prep for your rookie drafts? Do you fill-up notebooks analyzing your league mates’ tendencies? Are you taking pages of notes as you break down film on Odell Beckham Jr. or DJ Moore? If this sounds familiar, making your own database could give you the upper hand over your competition.

How to use Classification Trees to Predict the Future

Classification and Regression Tree (CART) modeling sounds very boring, but it is actually one of the most interesting and intuitive modeling methods available. I have covered two types of modeling so far: Multi-Linear Regression and Neural Networks. CART Modeling is by FAR the simplest and most comprehensible. Cart modeling allows us to create a visible …

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