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2022 NFL Draft: Using text analytics to evaluate the 2022 wide receiver class

College Park, Maryland, USA; Penn State Nittany Lions wide receiver Jahan Dotson (5) runs a fourth quarter touchdown as Maryland Terrapins linebacker Ahmad McCullough (19) defends at Capital One Field at Maryland Stadium. Mandatory Credit: Tommy Gilligan-USA TODAY Sports

We are back with another positional writeup of draft prospects, this time focusing on the wide receiver position. We previously delved into the quarterbacks and (old) running backs.

Thanks to math and feature engineering, we can use natural language processing to compare prospects to their contemporaries and those from the past before tying in advanced descriptive stats that we have built previously to gauge how well a prospect fits within a certain mold performed in the NFL. 

For this analysis, we took prospect write-ups from The Athletic's Dane Brugler, who is one of the best football film analysts out there, over the past eight seasons (including 2022) and used latent semantic analysis (LSA) to derive similarity scores between the text in prospects’ scouting reports.

After building our dataset to span eight seasons, we can create a prospect's score in a number of ways. We decided to use a weighted average of similar players’ WAR (wins above replacement), using the similarity score derived above as the weights. For example, if a player has a 0.60 similarity score with a player who has earned 7.0 WAR since being drafted and a -0.3 similarity score with someone who has earned 4.0 WAR, his overall score would be +3.

Using the analyses above, we can look at 2022 prospects in a couple of ways. First, we can examine player comparisons for notable prospects. Second, we can rank the players in each position group by the score derived above. These scores have correlated well with draft position and future WAR generated at the NFL level, although a more robust analysis using more seasons and data sources is beyond the scope of this article.

Let’s start by looking at the most successful NFL wide receivers' text comparisons so that we can then see what that means for prospects in the 2022 class.


SUCCESSFUL TEXT ANALYTIC TRAITS

BAD TEXT ANALYTIC TRAITS

PLAYERS EXCEEDING THEIR DRAFT PEDIGREE

SKYY MOORE, WESTERN MICHIGAN

Moore has one player who is over a similarity score of 50 — Vikings receiver Justin Jefferson, a player who many wondered, like Moore,  whether he was “just a slot receiver.”  Other notable similar receivers are Anthony Miller, Donovan Peoples-Jones and Marcell Ateman.

TREYLON BURKS, ARKANSAS

Burks’ closest comparison, with a similarity score over 60, was Brandon Aiyuk, who was selected close to where Burks’ draft slot prop is currently on DraftKings Sportsbook(23.5).  Other close comparisons are Laviska Shenault, Michael Pittman Jr. and Austin Carr.  

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