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

Marvin Harrison Jr. (WR – Ohio State) 

Most similar players: Cedrick Wilson (0.906), Courtland Sutton (0.822), Rashod Bateman (0.812)

Not only is Marvin Harrison Jr. considered the top-ranked wide receiver prospect in this class, but many also consider him the best overall prospect across all positions. It’s tough to poke holes in a receiver’s profile who put up 1,200 receiving yards and 14 touchdowns in back-to-back seasons and a career 2.98 yards per route run that puts him in the 91st percentile. Some of Harrison’s best traits are tough to capture with the data and can only be seen watching him on film.

The one area where analysts have criticized Harrison (at least compared to Malik Nabers) is after-the-catch stats. His career 5.1 yards after the catch (YAC) per reception was in just the 32nd percentile of receivers. It’s also worth noting Harrison didn’t participate in any offseason testing. But, when you’re a consensus top-five pick in the draft, what do you have to gain by doing so?

Malik Nabers (WR – LSU)

Most similar players: Jerry Jeudy (0.820), Skyy Moore (0.795), Justin Jefferson (0.790)

Malik Nabers, similar to teammate Jayden Daniels, had a meteoric rise in his fame this past season. In his final season, he recorded an astonishing 1,569 receiving yards and a 99th percentile Pro Football (PFF) receiving grade (93.1). Nabers is most well-known for his explosiveness after the catch — in his three years at LSU, he posted a 6.6 YAC per reception mark. What makes this more impressive is his 12.0-yard average depth of target (aDOT). So, not only did he get targeted downfield, but he also put on the burners to gain even more yards.

Throughout his career, Nabers played primarily from the slot (2022 was the only year where he lined up out wide more often) and got most of his production when lined up there. This could be seen as a signal to some that Nabers may not have the experience to play as a true X receiver. However, according to Matt Harmon’s Reception Perception, Nabers had a 78th percentile success rate against press coverage. Plus, he’ll have plenty of time to develop as he doesn’t turn 21 until late July and is the youngest receiver in his class. I think he’ll be just fine.

Rome Odunze (WR – Washington)

Most similar players: Andrei Iosivas (0.826), Courtland Sutton (0.806), Michael Pittman (0.774)

Rome Odunze rounds out the top three consensus receivers in this draft. He likely has a floor of being picked in the top 10 as there seems to be a decent-sized tier drop after Odunze that’ll make teams want to pounce, and rightfully so. Last year, Odunze had an FBS-leading 1,640 receiving yards, which out-produced his previous three years at Washington (they say Rome wasn’t built in a day, right?). Though it may have been more a consequence of who was throwing him the ball, Odunze had a deep 15.5-yard aDOT in his final year. Still, he caught 21-of-28 contested targets.

Running a 4.45-second 40-yard dash at 6-foot-3 and 220 pounds, Odunze had a 9.92 relative athletic score (RAS), second in the class, and fits the bill as having the prototypical wide receiver build. The question remains if Odunze’s final year was a flash in the pan or something to build off of further.

Brian Thomas Jr. (WR – LSU)

Most similar players: DK Metcalf (0.844), Tyquan Thornton (0.778), Chase Claypool (0.730)

To use lingo from my F1 fandom, Brian Thomas Jr. is considered the best of the rest. Thomas was overshadowed by teammate Malik Nabers but still had an outstanding final season. He recorded nearly 1,200 receiving yards while having a nose for the end zone with a team-leading 17 receiving touchdowns. Not only did Thomas find the end zone often, but he also had a knack for moving the chains:

Highest percentage of targets to result in a 1st down or TD among all Power 5 WRs with 50+ targets in 2023:

1. Roman wilison (58%)
2. Brian Thomas Jr. (56%)

– Ian Hartitz (@Ihartitz) April 9, 2024

Like Nabers, though, Thomas was a bit of a one-hit wonder as he failed to top 4o0 receiving yards in each of his first two seasons at LSU. Accordingly, we should be equally encouraged by Thomas’ profile as he was charted as having an 83rd percentile success rate against press coverage, per Matt Harmon. Thomas spent 87% of his snaps split out wide, so the team set to draft him could be getting a bonafide WR1.

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.

Keon Coleman (WR – Florida State)

Most similar players: Collin Johnson (0.900), Isaiah Hodgins (0.895), Auden Tate (0.883)

In college, Keon Coleman was a Sportscenter Top 10 play waiting to happen. The issue, as you may notice in those clips, is Coleman’s lack of ability to create separation. According to PFF, Coleman’s separation against single coverage last year ranked 449th out of 450 qualifying players — not great, Bob. Furthermore, when looking at Coleman’s charted stats he falls short in a lot of areas (photo via Reception Perception):

After transferring from Michigan State to Florida State for his final season, Coleman led the Seminoles in receiving yards while his targets per route run rose slightly from 22.9% to 24.9%. Also, despite running a 4.61-second 40-yard dash at the combine, Coleman reached a top speed of 20.36 miles per hour during the gauntlet drill, the fastest speed by any receiver over the last two seasons. Whether or not I like Coleman’s profile is a complex battle between my head (his production and efficiency are poor) and my heart (the dude can ball), so I think landing spot and development will matter slightly more than some of the other receivers.

Xavier Legette (WR – South Carolina)

Most similar players: Jonathan Mingo (0.907), DK Metcalf (0.835), Chase Claypool (0.831)

In his fifth season at South Carolina, Xavier Legette burst onto the scene with a 1,200-yard receiving season along with seven touchdowns. The problem is that makes up the vast majority of his production as he recorded a combined 42 receptions for 423 yards and five touchdowns in his first four seasons. He wasn’t efficient at all in those seasons either with 0.75 yards per route run and 3.6 YAC per reception. But, with a final season that impressed many, it makes Legette a difficult player to project to the next level.

Legette’s size and athleticism are enticing, though. He ran a 4.39-second 40-yard dash at 222 pounds, giving him the eighth-best speed score (119) in my database of 295 receivers. Unfortunately, Legette turned 23 a couple of years ago, which may take him off of some teams’ boards from the jump.

Roman Wilson (WR – Michigan)

Most similar players: Mecole Hardman (0.852), Jalin Hyatt (0.809), KJ Hamler (0.807)

Like many pieces of the Michigan passing offense the past couple of years, Roman Wilson struggled to see meaningful volume. He only eclipsed 500 receiving yards once in four years (798 yards in his final season). That said, he did have a penchant for scoring with a career 18.9% touchdown rate. Additionally, Wilson had an 81.9 PFF grade for his career, which is solid and what you’d want to see for someone with fewer reps.

For an undersized receiver at 5-foot-11 and 186 pounds, Wilson’s career 52.9% contested catch rate is quite impressive. It also helps that his 4.39-second 40-yard dash was tied for the sixth-best in this class. Wilson played most of his snaps (73.4%) from the slot in his final two seasons at Michigan, so he could offer some PPR value early on if that’s his role.

Ricky Pearsall (WR – Florida)

Most similar players: Freddie Swain (0.834), Devin Duvernay (0.730), Jalin Hyatt (0.710)

Ricky Pearsall’s profile has a lot of similarities to Legette as he’s an older, more athletic prospect. The benefit Pearsall’s profile provides is a bit more consistent production. Pearsall transferred from Arizona State to Florida for the last two of his five seasons in college and had at least 650 receiving yards in each season, but failed to top 1,000 yards. Still, his totals were good enough to lead the team in both years.

Pearsall’s 82.9 PFF grade in his two Florida seasons also ranked in the 95th percentile. He didn’t earn targets at a great clip overall as evidenced by his career 19.1% targets per route run rate. But, like I said, Pearsall is very athletic as evidenced by his 9.91 RAS score, which was good for third-best in the class. He should fit in nicely as a team’s WR3, continuing to develop and polish his route-running.

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
• 2024 NFL Mock Draft: Top 20 Picks & Predictions
• 2024 NFL Mock Draft: Top 10 Picks & Predictions
• 2024 NFL Mock Draft: Early Picks & Predictions
• Early 2024 NFL Mock Draft with Trades: Picks & Predictions

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