The NFL Combine and college Pro Days are behind us while the NFL Draft is right around the corner. There has been no shortage of coverage for these prospects, but I wanted to bring a different spin on player comparisons. To do this, I use a technique called clustering, which allows me to bucket these players into several statistical profiles and compare one to another. In the clustering, I included a combination of production, efficiency, athleticism and usage metrics in hopes of capturing who these players are.
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NFL Draft 2024 Prospect Comparisons
This article will cover the methodology with commentary on some of the standout players from the 2024 class. Once again we have a seemingly loaded wide receiver draft class set to shake up the fantasy football landscape. There’s a trio of receivers set to be taken in the top 10 picks of the draft with another four possibly drafted in the first round. This class offers a mix of strong X receivers along with slot role-players. So, no matter what your team needs, they’ll find it in this draft class.
Methodology
Before I get into the analysis, I want to explain the methodology and techniques I used along with delineating what this analysis is and, more importantly, what it is not. Let’s start with the latter.
This analysis is a descriptive way to compare a player’s college stats and athleticism to historical results. This is not a predictive indicator of future NFL and fantasy success or that a player with similar athletic and production stats will have the same career.
In terms of the methodology, I used a principal component analysis (PCA) using data since 2016. If you’re unfamiliar with PCA, it is a way to “squish” several variables (in this case, each of our statistical metrics), into just a couple of variables – our principal components – thus simplifying our dataset and reducing noise. Put another way, PCA helps us find fewer features that will represent our data (or prospects) in a more compressed way.
This also allows me to visualize the results on two axes using the first two principal components, which I wouldn’t be able to do easily with the several metrics we have. This is also where we can see player comparisons – players that appear further away from the center of the chart are more unique in their results and fall into a more distinct category.
For wide receivers, below are the weights for the metrics for each of the two principal components. To calculate a player’s principal component, you can read these as linear equations. So. for principal component one, a player’s score is calculated as (-0.39*Height) + (-0.31*Weight) + (-0.08*Forty-Yard Dash) + (0.39*Receptions/Game) + (0.20*Rec Dominator) + (0.31*YPRR) + (0.422*TPRR) + (-0.23*Yards/Rec) + (-0.35*aDOT) + (0.34*Slot Rate).
I also calculated similarity scores between each prospect’s metrics profile – I only used the metrics used in the PCA above. For this, I calculated the Euclidean distance of each metric between each player to get the Cosine similarity, resulting in our similarity score. Below each player, I’ll give a brief list of the players whose statistical profile is most similar to the prospect, along with the similarity score. These scores are in a range of 0 to 1, with 1 meaning a player’s statistical profile is an exact match.
With that, let’s get into some analysis.
Wide Receiver Prospect Comparisons
Adonai Mitchell (WR – Texas)
Most similar players: Terry McLaurin (0.903), Tyquan Thornton (0.829), DK Metcalf (0.822)
Adonai Mitchell is a deep-play merchant. The problem is that once Mitchell catches the ball, he seems to… stop moving. Across his three-year career, his 15.6-yard aDOT is in the 91st percentile, yet his 3.0 YARC per reception is in the first percentile (that’s not good). However, many will point out that the quarterback play Mitchell was working with, especially at Texas, was less than stellar as he had just a 66.5% catchable target rate, per PFF, just a 20th percentile mark.
The bonus is that Mitchell is an athletic freak (but also makes it more confusing that he wasn’t able to separate after the catch). His 9.99 RAS score is the sixth-highest all-time among wide receivers. Mitchell’s teammate stole the show at the combine, but a 4.34-second 40-yard dash is nothing to slouch about. With this skill set, Mitchell will have a lot of developing he’ll need to do to expand his repertoire and become an every-down receiver.
Xavier Worthy (WR – Texas)
Most similar players: Quez Watkins (0.877), Calvin Austin (0.800), Garrett Wilson (0.785)
Xavier Worthy is, in a word, fast. In case you missed it, Worthy broke the NFL Combine record with a 4.21-second 40-yard dash. This effort singlehandedly pushed Worthy back up to being a fringe round-one receiver in Thursday night’s draft:
Unlike his teammate, Worthy was able to do damage after the catch with a career 7.3 YAC average. But, Worthy isn’t as polished of a receiver. His 72 PFF receiving grade last year was in the 28th percentile. Speed kills in the NFL, so a team will certainly be enamored by that, even at just 170 pounds.
Ladd McConkey (WR – Georgia)
Most similar players: Anthony Schwartz (0.749), Mecole Hardman (0.680), Garrett Wilson (0.672)
Ladd McConkey is not going to wow you with his production profile. He failed to reach 800 receiving yards in a single season and scored just 14 total touchdowns. McConkey was also never the primary target in his offense (that belonged to Brock Bowers). An ankle injury cut his final season short, but what McConkey lacks in production he makes up for with speed, efficiency and elusiveness.
Among 285 receivers with at least 30 receptions last year, McConkey’s 0.3 missed tackles forced per reception ranks 29th (and his 0.25 career rate is quite solid, too). McConkey also has a stigma attached to him as a slot receiver (probably because he’s small), but he spent the majority (70%) of his snaps lined up out wide. Finally, his 3.26 yards per route run from last year ranked very highly, demonstrating his efficiency on a per-route basis.
Troy Franklin (WR – Oregon)
Most similar players: Garrett Wilson (0.822), Chris Olave (0.776), Quez Watkins (0.775)
If you look at the first two comps for Troy Franklin, it’s easy to get excited. The Chris Olave comparison resonates not only from a production standpoint but also from a play-style perspective. Franklin had a phenomenal final season at Oregon, leading the Ducks in receiving yards with 1,383 and touchdowns with 14. He was also an explosive play waiting to happen as he was fifth in the league with 37 explosive (15+ yard) plays last year.
One concern with Franklin is his size. While he stands tall at 6-foot-3, he weighs just 183 pounds. This may have impacted his career 37.8% contested catch rate, which ranked 194th out of 248 wide receivers in my database. If he can put on some weight and improve his strength, he has the tools to be a solid receiver at the next level.
2024 NFL Mock Drafts
- 2024 NFL Mock Draft: Matthew Jones (1.0 | 2.0 | 3.0 | 4.0 | 5.0)
- 2024 NFL Mock Draft: Andrew Erickson (1.0 | 2.0 | 3.0 | 4.0 | 5.0)
- 2024 NFL Mock Draft: Kent Weyrauch (1.0 | 2.0 | 3.0 | 4.0)
- 2024 NFL Mock Draft: Derek Brown (1.0)
- 2024 NFL Mock Draft With Trades: Mike Fanelli (1.0 | 2.0 | 3.0 | 4.0 | 5.0)
- 2024 NFL Mock Draft: Russell Brown (1.0 | 2.0 | 3.0)
- 2024 NFL Mock Draft: PJ Moran (1.0 | 2.0 | 3.0)
- 2024 NFL Mock Draft With Trades: Marco Enriquez (1.0 | 2.0)
- 2024 NFL Mock Draft With Trades: Dennis Sosic
- 2024 NFL Mock Draft: Two-Round Writer Collaborative
- 2024 NFL Mock Draft: First Round Picks & Predictions
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- 2024 NFL Mock Draft: Early Picks & Predictions
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