There are many factors at play when trying to determine which rookies will succeed from a fantasy perspective. What if you could eliminate a level of uncertainty by using the power of probability? This article aims to do just that by forecasting the future fantasy relevance of WRs taken in this year’s draft through a predictive algorithm.

This model, referred to as a “z-score rating,” measures a variety of factors that have historically proven to materialize into fantasy success. Doing so can provide us some comfort of assurance when selecting our dynasty candidates in our upcoming drafts. Since there are a few shared repeating themes and if you haven’t already done so, you may also be interested in checking out the RB z-score ratings found here: Predicting Post-NFL Draft Rookie RB Success (2019 Fantasy Football).

Here is the overall plot of a WR z-score in correlation to their average fantasy production per game in a PPR league for their first three years in the NFL. This list includes the majority of WRs drafted in Rounds 1-4 since 2015, along with the top fantasy scorers from last year (2018), regardless of the year they were drafted.

This lovely model has a well-fitting positive correlation along with a nice sample size. In addition, what makes it particularly attractive is the absence of any drastic outliers in the upper left and lower right sections. This means we can likely use the following visual thresholds of a 50% z-score or less for fewer than 11 points per game and a 75% z-score or more for above 11 points per game with a high level of probability. You can find a comprehensive list of each player’s z-score at the end of this article.

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Method

To avoid the dangers of tunnel vision, a z-score takes into account a wide breadth of factors that each carry their own appropriate weight. By having this balance, it tempers projections for those who score very high in a particular area (e.g. elite catching radius), but low in another (e.g. poor college production), along with rewarding or punishing those who do well or poor in multiple categories. Understanding when to use a pure linear correlation versus threshold indicators for each factor is equally as important. These factors consist of the following:

Draft position Collegiate career dominator rating per game played Market share of receiving yards in their final collegiate season Hand size thresholds Arm length thresholds Altered Height Adjusted Speed Score (HaSS) Offensive production and quarterback stability of NFL team they are drafted by from prior year Breakout Age Disqualifying Thresholds

Breaking down how each factor develops into success provides the logic behind a z-score. Draft position relates to both opportunity and talent. Better players typically go higher. and the higher a draft pick, the more investment from the NFL club selecting them, leading to more opportunities.

Collegiate career dominator rating shows a player’s success in terms of yardage and touchdowns relative to teammates and the offensive scheme. These numbers were obtained from Peter Howard’s database and were then divided by games played. If you excelled in this dominator rating, it is likely to continue in the pros. Now dissecting this further, having a heavy market share of your team’s receiving yards in your final season also has an independent direct effect on your future NFL success.

The next three factors all deal with physical attributes. Hand size, arm length, and an altered HaSS can indicate what a WR is capable of physically. Monstrous hands, long reach, and a respectable height-weight-speed combo are all traits that are shared with some of the greatest physical receivers that have graced the game with their talent.

Being drafted to a high-scoring offense or a team with an entrenched QB such as Drew Brees, Aaron Rodgers, or Andrew Luck opens up the opportunity for production. Breakout age is when a player starts performing his best, with younger being better. One you give each factor its appropriate weight and blend them together, then you have your final z-score.

2019 Dynasty WR Predictions

Looking at the rookie WR class of 2019, we have the honor of having a bona fide fantasy star along with some pretty clear tier separation. Below you can find where each WR ranks in regards to their z-score and respective fantasy projections. As with the RB projections, we’ll use the projected PPG combined with expected games played by position due to injury, which is 14.0 games per season for WRs. Naturally, a completely healthy player scores more than an oft-injured player and vice versa.

Keep in mind these projections are based on a historical record of their average fantasy production over a three-year period, not solely their rookie season. Please reference the overall chart above, or the detailed list at the end, to find players from the past that have scored similarly.

1. N’Keal Harry (NE): 111% z-score, 229 FP/year

This man is simply incredible from a statistical standpoint. With the highest z-score of any WR in the last five years, Harry is projected to be an elite fantasy contender with a very high floor. Nearby z-score rankings consist of Mike Evans, Julio Jones, Amari Cooper, and the great Larry Fitzgerald! He scores well in every z-score category, has first-round pedigree, and goes to an offense that just won the Super Bowl with Tom Brady at the helm, not to mention one of their few large body targets retired this year in Rob Gronkowski.

He is in a tier of his own and you may want to consider trading up for him (given the price is right) with anyone who has the lack of due diligence to undervalue him. If this point hasn’t been driven home yet, look at the overall chart above and follow a 1.11 z-score to corresponding PPG to convince yourself. He should be the undisputed top overall selection in all PPR rookie dynasty leagues.

2. J.J. Arcega-Whiteside (PHI): 70% z-score, 158 FP/year

Arcega-Whiteside is a nice pick for those who like to play it safe, as he achieves multiple thresholds that have translated to between 8-12 PPG. This explains his higher ranking here, albeit his situation is a bit cloudy in a crowded receiving core. He needs to carve out his role either by showcasing his talent early or for the Eagles to have personnel changes that clear up volume for him. Carson Wentz staying healthy for a full season would also benefit him.

3. Hakeem Butler (ARI): 69% z-score, 156 FP/year

Butler has some outstanding measurables with 10.75-inch hands and a 35.25-inch arm length, both of which set the mark for largest and longest, respectively, in the entire WR sample pool taken. Combine this with his 6’5″ height and the results are eye-popping. Being drafted in the fourth-round hurts his stock and his success is greatly tied to that of the number one overall selection, Kyler Murray. His few warning flags combined with his more outstanding traits make him a high-risk, high-reward candidate.

4. D.K. Metcalf (SEA): 60% z-score, 140 FP/year

As a combine spectacle going into an undetermined depth chart waiting with open arms, there’s a lot to like about Metcalf. His stiffest competition being Tyler Lockett and David Moore? Yes, please. His lack of market share compared to college teammate A.J. Brown is a concern, however, as is Seattle’s tendency to run the ball and drain the game clock relentlessly. A stronger passing philosophy and an ability to become an established presence on the outside will help him realize his fuller potential.

5. A.J. Brown (TEN): 57% z-score, 134 FP/year

Ranking right next to college teammate Metcalf seems to be a fitting place for these two. Looking onward to his new teammate Corey Davis for reference, he has a 90% z-score and a slightly underperforming 12.5 PPG with Marcus Mariota and the Titans’ offense. If Davis couldn’t make the most of the situation in Tennessee, it’s unlikely Brown will do much better given his lower z-score rating, although 57% is respectable.

6. Andy Isabella (ARI): 54% z-score, 129 FP/year

One of the most intriguing things about Isabella is his gorgeous market share of 48% his final season, which means he got the ball in a high amount of situations with opposing teams knowing he was going to get the ball, and still produced anyway in spite of this. Another player dependent on the success of Kyler Murray, he could find nice opportunity if he’s able to continue his knack for production.

7. Deebo Samuel (SF): 53% z-score, 128 FP/year

Samuel doesn’t have much standing in his way to earn a starting spot as the 49ers’ receiving group consists of some lower-scoring personnel in Dante Pettis and Marquise Goodwin. He scores decent in most categories, but great in none. If Jimmy Garoppolo returns healthy and they start passing to receivers more, his outlook could turn rosier.

8. Marquise Brown (BAL): 41% z-score, 107 FP/year

This is a rather disappointing score for a first-round selection, to say the least. Red flags run rampant with Brown as he’s short, lightweight, has smaller hands and arms, and goes to one of the most adamant run-heavy teams in the league. He has the positives of speed and pedigree going for him, but not much else, giving him the lowest z-score rating for a first-round pick in recent years.

9. Parris Campbell (IND): 36% z-score, 98 FP/year

Campbell is in a battle between low metrics and great opportunity. His sub-par dominator and market share ratings cast a bleak, dark future, but the sun over the horizon is the fact he landed with the Colts, quarterback Andrew Luck, and a generally open depth chart behind T.Y. Hilton. If you have a ‘faith to move mountains’ type of belief in opportunity over talent, Campbell fits the bill.

10. Mecole Hardman (KC): 30% z-score, 87 FP/year

In an extremely similar situation to the aforementioned Campbell, Hardman has even poorer metrics, but even better opportunity if Tyreek Hill misses prolonged time as he’ll have the reigning NFL MVP Patrick Mahomes slinging passes his way. The Chiefs traded up for him in the second round, making him a priority in their eyes. If I were to pick a man to outperform his z-score in year one based solely on opportunity and club investment (granted Hill misses time), it’s Hardman.

11. Miles Boykin (BAL): 27% z-score, 81 FP/year

Boykin has some impressive traits to get a jump ball at its high point with 6’4″ height, 33.5″ arms, 220-pound frame, and a massive 43.5″ vertical. As fun as this is to picture, his opportunities to showcase it will be very low due to first-round selection Marquise Brown, a questionably accurate Lamar Jackson, and the Ravens’ run-first tendency all standing in the way.

The following candidates have low expectations and a large depth chart hurdle, as many project to range as the WR3 to WR5 in their respective offense’s pecking order.

12. Jalen Hurd (SF): 25% z-score, 78 FP/year

13. Diontae Johnson (PIT): 24% z-score, 77 FP/year

14. Ashton Dulin (IND): 21% z-score, 72 FP/year

15. Terry McLaurin (WAS): 1% z-score, 35 FP/year

The remaining prospects not listed were taken in the fourth round or later and/or scored under a 20% z-score. They are being left off this list for the apparent lack of fantasy relevance.

Previous Years’ Z-Scores

Here are the z-score ratings for the combined years of 2015-2018 for the majority of the WR class taken in Rounds 1-4, along with some of the top fantasy scorers from 2018, regardless of their draft year and their fantasy pts/game average during their first three years in the NFL:

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David Zach is a featured writer at FantasyPros. For more from David, check out his archive and follow him @DavidZach16.