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Predicting rookie WR Success Post-NFL Draft (2022 Fantasy Football)

The Fantasy Z-Score returns!! In it’s fourth season, the WR Z-Scores are here to serve you with a complete analytic view of your favorite prospects. All the knowledge you can handle below πŸ‘‡

Dynasty fantasy football rankings 2019

The Fantasy Z-Score returns once again! A statistical breakdown of what metrics matter most for predicting future fantasy production.

I hope that this model can provide you with actionable insight into each prospect’s profile, their pros and cons, and why it matters. The particular beauty of the Z-Score is in its transparency in process, categorical grades, and final overall projection of PPG to satisfy those who are thirsting for a quick summary of the analysis, deep explanatory insight, and everything in between. For detailed explanations of the process and categories used, please scroll down to the “Method Behind the Madness” section.

2022 Dynasty WR Rankings and Predictions

This class as a whole is very weak when compared to recent years. Still, wide receiver is the position that can hopefully carry it into the history books as significant for fantasy purposes.

Below you will find each player’s Fantasy Z-Score rating, a snapshot of their profile grades, and their current consensus ADP. A full summary of the 2022 class all in one chart is included here for your viewing pleasure:

Tier 1

1. Treylon Burks (TEN)

Projected PPG: 13.9

Consensus Rookie ADP: WR2

The #1 ranking wide receiver may come as a surprise to some after being the 6th WR off the board on draft night, but his all-around profile speaks for itself. While not reaching as high of an elite ranking as anyone in the past few classes, he’s the closest to having such a profile. The few things holding him back are a later breakout age and underperformance in film grades compared to previous elites.

Best-in-class career production, tied for top-in-class film grades, and efficiency metrics have the model barking for Burks. Whether that barking analogy makes any sense or not, what does make sense is placing your bet on the surest profile in college to be the surest profile in the NFL.

Burks was the heart and soul of the Arkansas offense and has often drawn comparisons to Deebo Samuel and AJ Brown among the film community. Funny enough, the Titans traded away Brown specifically to draft Burks. While comparisons are irrelevant to an analytic profile, it sure paints an attractive picture if his new team can capitalize on his talents in a similar fashion. His team dominance is showcased best by his 3.9 YPRR his final season, the best in class.

It is worth noting how close he is to our next prospects, so while he scores higher, the range of outcomes for the top-4 receivers are quite similar.

2. Garrett Wilson (NYJ)

Projected PPG: 13.2

Consensus Rookie ADP: WR3

There is a fiery debate in the fantasy community over who the better Ohio State receiver is coming into the season. Still, from the Z-Score perspective, there is no discussion to be had.

Apart from breakout age, Garrett out-scores his collegiate teammate ever so slightly in every category except breakout age, but more than makes up for it by being an early declare junior as opposed to a senior.

The Jets are seen as a murky landing spot, but I personally love everything they have been doing over the past few years as an organization. An all-around much-improved team this season will all hinge on the progress of Zach Wilson.

All three film grades had him as either their best or tied for best in class. And while he doesn’t score as an other-worldly talent in any other particular category, he is above average in every single one. When you hear him speak in interviews, he seems to have a deep understanding of the game, how to leverage his strengths, and what he needs to do to develop. He has the safest and highest projected floor of anyone in the class, having little to no concerns.

3. Jameson Williams (DET)

Projected PPG: 13.1

Consensus Rookie ADP: WR4

This is where things get exciting. Jameson has efficiency metrics of Yards Per Route Run and market share that are among the best possible for a player in any circumstance, let alone doing so while at Alabama. His Team Adjusted Efficiency puts him into a bin of which the lowest scoring player has averaged at least 10 points per game; talk about a good floor. He also did this:

In Detroit, he instantly slides into the WR1 position with Amon-Ra in the slot and Chark/Reynolds/Cephus as rotational pieces. Jared Goff can support a top WR, as illustrated through his career, but there is no doubt a lot of mouths to feed when we also consider Hockenson. I’ve seen some comps to Henry Ruggs and DeSean Jackson and think he’s somewhere in between.

It’s hard to ignore the eye-popping plays he displayed last year. He projects with a wide range of outcomes due to his underwhelming career and breakout age – and was notably beat out by both Wilson and Olave at Ohio State – but also comes with a ceiling that could be best in class. If you are shooting strictly for upside with no care about risk, Jameson is your guy.

4. Drake London (ATL)

Projected PPG: 13.0

Consensus Rookie ADP: WR1

Often argued as the best WR of this draft due to his early breakout age and production, this model dissents from public opinion a bit. The major factor being the Z-Score has learned to account for collegiate team prestige when factoring in a production profile. Players at less impressive schools need to really dominate to stand out. USC had an SRS of -0.46, aka one of the worst schools among this WR group. So while London’s market share and dominator are borderline amazing, it gets dinged quite a bit by his lack of surrounding talent to compete with.

Landing with the dirty birds in Atlanta gives him the untethered reins to be the WR1 of their offense, alongside unicorn TE Kyle Pitts. A primary concern is who is getting him the ball. Marcus Mariota isn’t exactly comforting for 2022, but we are projecting long-term and expect them to add someone much better by next year.

London still has an impressive profile, but temper expectations a bit when looking at his raw numbers.

Tier 2 

5. Skyy Moore (KC)

Projected PPG: 11.5

Consensus Rookie ADP: WR6

The small school standout looks like one of the Z-Score model’s favorite targets in late-1st, early-2nd rounds of your fantasy drafts. His attractive profile is led by his impressive career yards per team pass attempt at 2.7, top-3 in class. His monstrous 10.25″ hands and notoriety as having sure-handed catches are a nice added touch.

You could hardly ask for a better pairing than being locked into having Patrick Mahomes as your QB for the foreseeable future. This may bump Moore’s cost into unreasonable levels, but I’m comfortable having him at the top of my second tier.

The only heavy blemish on his profile comes from poor overall film grades, coming in below average from all three film sources for typical top-150 draft selections. Despite this drawback, he’s still my favorite value target in rookie drafts.

6. Chris Olave (NO)

Projected PPG: 11.3

Consensus Rookie ADP: WR5

Our first late declare WR makes his appearance at number 6. He had a strong early showing in his career that slowly diminished as the years went byβ€”culminating in a final senior season where he was out-produced by both junior Garrett Wilson and emerging star sophomore Jaxon Smith-Njigba.

His team-adjusted efficiency ranked worst among the first-round pick wideouts. This raises considerable concern for the model when paired with the late breakout, as most players should have their best year in their final season.

However, the film gurus still rave about his ability, especially as a route runner. He’ll have a chance for immediate volume in the Saints offense as the WR2, but as we said with most players in this class, it’s a pick your flavor type of draft.

7. Jahan Dotson – WAS

Projected PPG: 11.1

Consensus Rookie ADP: WR9

Dotson comes in as the worst-graded first-round pick of the class. This is heavily due to his being a late declare and scoring a “B-” or less in four of the remaining five categories.

His best feature is his film grade among his entire profile, apart from his draft capital. Film blurbs often mention how he has the best hands among all receivers, along with crisp route running.

His consensus ADP “nail in the coffin” is his landing spot in Washington. Wentz remains a big question mark, and he will very likely be second fiddle to McLaurin for the foreseeable future. While the Z-Score has him as a value at WR7 compared to WR9 ADP, his situation is a major turn-off for most fantasy players. He’s worth a shot if your leaguemates are overvaluing his landing spot and he continues to fall in price.

8. Wan’Dale Robinson – NYG

Projected PPG: 10.9

Consensus Rookie ADP: WR13

Back-to-back players with notably poor landing spots. Next comes undersized yet super productive standout WanDale Robinson. This guy has all the markings of what should have been a first-round selection in the NFL draft, barring one major hurdle: he’s tiny. Coming in at 5’8″, 178 lbs, and the shortest arms in the class by FAR at 27.63″, it’s the flag that scares most everyone away from a fantasy perspective.

I have long sided with production being far more important than physical metrics, and albeit his size flag is glaring, the new head coach for the Giants, Brian Daboll, doesn’t seem to be too concerned either. He was used as a WR/RB hybrid and do-it-all player for his collegiate career and put up a massive season despite transferring to tougher competition at Kentucky.

The Z-Score is notorious for liking small players far above consensus: KJ Hamler, Elijah Moore, Tutu Atwell, and now Robinson. I still think he’s a good bet and that Daboll will be creative enough to use him well.

Other concerns arise, however, in the Giants WR room, which is littered with competition in Golladay, Toney, Shepard, and more. In addition, we have another highly questionable QB in Daniel Jones, delivering the ball. But as I noted with the Jets, when they had other players and a new regime, it is wise to bet on the same players that the new regime is betting on. Among those WRs listed, only Robinson was hand-picked by this coaching staff.

Robinson remains my favorite 2nd round value at the WR position.

Tier 3 – with spark notes

9. Christian Watson (GB)

  • Athletic freak, small-school standout, and Senior Bowl standout
  • Best landing spot on Earth in a wide-open GB receiver room

10. John Metchie (HOU)

  • Solid production at one of the best schools in the nation at Alabama
  • Slides immediately into the WR2/3 role behind Cooks

11. George Pickens (PIT)

  • PIT is notoriously good at drafted WRs; best in class breakout age
  • Heavy competition with Diontae and Claypool

12. Jalen Tolbert (DAL)

  • Attractive profile and unreal dominance in production, but very little in competition
  • WR3 at best behind Lamb and Gallup?

The remaining receivers can be found in the overall chart listed above. They are all a solid tier below these top-12, and their projections can give you an idea of what to expect.

Method behind the Madness

Every year, I rerun the metrics in my database to ensure they are holding up consistently over time. This allows me to catch new trends in fresh data points and/or eliminate defective ways of thinking. Notably, I have found that Film Grades – from the right sources – provide a very effective balance to the Z-Score and, as such, are an added feature this year. Another is Yards Per Route Run in college, which will combine into final season grades with market share.

While some sections remain the same, the Z-Score is constantly evolving to give a holistic picture of a prospect’s profile. I have weighted each category’s grade appropriately with respect to its measured predictiveness of NFL success, but separating each grade out allows for transparency and the freedom to weigh them as you see fit. Below you will find each category, followed by a short explanation of why they are used.

Draft Capital

  • NFL draft pick placement.

Early Declare

  • Wide receivers who declare early – less than four years of college – have an increased rate of NFL success to the tune of about four more points per game on average.

Team Adjusted Efficiency (Final Collegiate Season)

  • Market Share of Receiving Yards Per Game of final season, adjusted for team strength via SRS (Simple Rating System)
  • YPRR (Yards Per Route Run) adjusted for team strength via SRS

Career Production

  • Measure of Average Receiving Yards Per Team Pass Attempt (college career – per game)
  • Dominator Rating per game of final two seasons, adjusted for SRS and SOS to get a full picture of the level of “dominance”

Breakout Age

  • The earlier they succeed in college, the earlier that success will typically translate to NFL

Physical Metric

  • Hand Size 
  • Arm Length
  • Height
  • Weight

Film Grade (aggregated from three film sources)

  • Correlated historical film grades from 3 sources, including DynastyNerds Nerd Score, into expected fantasy points per game

Each final letter grade is representative of what echelon of PPG that player falls into. (E.g., an age 18 breakout age grades as an A). Please follow the resources mentioned below if you want a more detailed explanation of these categories.

NOTE: Many of these sections have not changed from previous year articles as their effectiveness remains unchanged and strong. Notable sections that have changed are Team Adjusted Efficiency, Physical Metrics, and Film Grade as mentioned earlier.

Breaking down each category, we can understand their usefulness. As with any position, draft capital is self-explanatory. The higher the selection, the better the player likely is and the more investment from the team to ensure they succeed.

Early declare shows that the level of interest is strong for players considering omitting a final year of college to enter the NFL draft early. It’s also a testament to a player’s talent, as better players are sought after more fervently by scouting departments. This was a metricΒ @LordReebsΒ broke down in further detail here:

Career production

Career production is the most meaningful category in the Z-Score next to draft capital. Average Yards Per Team Pass Attempt had the strongest single stat correlation to fantasy points in my database, essentially tying draft position. These were collected from the database of Peter Howard foundΒ @pahowdy. I have also found that dominator rating per game of the final two seasons shows more meaning than traditional dominator (final season and best season), but often, these naturally happen to be the same. I then adjusted for internal team strength (SRS) and their opponent strength (SOS), found at sports-reference.com.Β 

Team adjusted efficiency

Team adjusted efficiency consists of blending two final season metrics and is good for identifying the players you did the most when on the field in their last showings before the big show. The team adjusted market share highlights players who dominated on their team and how good that production was relative to the overall team strength. Obtaining a 40% market share on LSU is far more difficult than a 40% market share on Liberty and should be rewarded as such. This metric was inspired by Underdog analyst Hayden Winks (found atΒ @HaydenWinks) and compiled once again through the database of sports-reference.com. The second part is Yards Per Route Run, the metric that has risen in popularity over the past 5 years. Luckily for us, the SIS data hub has been tracking this for college athletes as well. Once again, when adjusted for team strength, it pops as a strong metric in predicting their NFL careers, albeit it has a smaller historical sample size than nearly all other metrics in this list.

Breakout age

Next up is breakout age. While breakout age is somewhat baked into early declares and early college production, it gives another perspective because some players enter college older/younger than others. It also tells us the exact year they excelled, which may get lost in career arcs with hyper-efficient final seasons.

Film grades

Film grades are one of the new additions this year. Analysts from NFL.com, Dynasty Nerds, and others have shown that their work is becoming as reliable as draft capital as the years go by. The film grade in the Z-Score is a unique weighted blend of these grades so as not to become pigeon-holed into one group’s way of seeing a player’s potential on film. Sure enough, the combination of all three has shown stronger predictive power than any one by itself. This adds confidence to the metric, knowing it is only included the best by balancing each other out when needed and amplifying it when all align to see the same result.

Measurements

Last and, yes, the least, are physical measurements. Physical measurements alone surprisingly carry more weight than combine athleticism for wide receivers. But all in all neither is that important. People of any shape and size can succeed. Hand size, height, weight, and arm length are the measures used, and the final grade is more of a tiebreaker or red flag in the grades than a stand-alone use.

As years progress, I constantly try to keep up with the most meaningful trends and metrics as the game evolves. This has led to using a rolling window of no longer than ten years of prospects. In the past seven years, draft capital itself has a historical R-squared of 0.230 to three-year PPG, compared to an R-squared of 0.378 for the Z-Score.

Remember, these are three-year projections for PPG starting from year 2, not solely rookie year success. Playing the long game is crucial with respect to wide receivers and dynasty. Their value remains much longer than the short-lived running back career arcs, for example. For year one, rookie rankings, defer to my redraft rankings and projections when released with Dynasty Nerds and FantasyPros.

Without any further ado, let’s dive into the 2022 rookie class.

I hope this breakdown was helpful for you to find the stats that matter most when researching your rookie wide receivers for the upcoming season. Remember that projections are only a portion of what to consider when evaluating a prospect. Landing spot, coaching tendencies, and supporting cast also play significant roles.

Thanks for reading, and stay golden! If you like what you learned, follow meΒ @DavidZach16Β for more interesting stats and tidbits throughout the year.

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