It’s that wonderful time of year again. As we reach the climax of rookie draft research season, I will once again be revealing my annual Pre-NFL Draft WR1 prospect analytical model ratings.
For those new to the WR1 rating, this is a highly accurate proprietary forecasting formula I developed to provide a data-driven forecast of future Dynasty value for incoming rookie wide receivers. The WR1 model scores rookies on nine predictive metrics and then combines those individual metric scores into a single WR1 rating. The goal is to provide a single easy-to-use score for those who don’t want to spend all the time dissecting different metrics.
Before I go into further explanation, I want to provide a proof of concept. The WR1 rating database includes the college data for all wide receivers drafted since 2007. Each prospect is graded using the same formula. Below are the top 20 WR1 prospect scores from 2007-2021 based solely on how their college statistics compute into the WR1 formula.
Note: Film grade was not available pre-2014 so estimates were used that did not materially affect where they would otherwise rank.
Seventeen of the 20 top-scoring prospects have already had a top-24 PPR PPG NFL fantasy season.
Fourteen of the 20 have also had a top-12 PPR PPG NFL fantasy season. Nine have had multiple top 12 seasons including perennial top-5 studs like Julio Jones, Calvin Johnson, Odell Beckham Jr., and the new elite studs like Ja’Marr Chase and Justin Jefferson.
Of the three who have not achieved a top-24 season yet, two are going into their third year and still have plenty of time to cross that top-24 fantasy threshold.
- Elijah Moore was the WR30 in PPG in his rookie season. He ended up in Robert Saleh’s dog house last year after some selfish quotes putting himself ahead of the team. He was since traded to the Cleveland Browns and now he finds himself in a nice situation with a proven high-end QB in Deshaun Watson throwing him the ball.
- The jury is still out on Rashod Bateman but given his standing in this group, I would say the odds are good he will have a top-24 season in his career.
Justin Blackmon‘s only played two years in the NFL and unfortunately was derailed by a substance abuse problem. In his second year, he averaged over 100 yards receiving per game.
For further proof of concept, from the 2020 season, the model identifies Justin Jefferson as the superior prospect to CeeDee Lamb when Lamb was the consensus top wide receiver in the 2020 draft.
Here is how the model graded the top 2021 wide receivers.
Chase, Moore, Waddle, and Smith were each top-5 in rookie WR PPR PPG. Amon-Ra St. Brown was the other in the top five and he ranked 11th of 31 wide receivers graded despite the NFL drafting him 17th overall. This model led me to post this immediately after St. Brown was drafted.
Drake London was the top rookie in the model in last year’s class and he went on to post an unheard-of top-five target share as a rookie. He is well on his way to a high-end fantasy career.
The metrics each prospect is graded on include:
- Breakout year
- Weighted Dominator
- Film grade
- Relative athletic score
- Conference competition score
- Draft round
- College point per reception fantasy points per game
- Receiving yards per team pass attempt
- Early declare status
These metrics have each individually shown correlation to future fantasy success. They are defined as follows:
Weighted college dominator rating: A player’s percentage of his team’s receiving yards and touchdowns*. Weighted 80% receiving yards share vs 20% receiving touchdown share.
Breakout year: The college year when they first posted a dominator rating at or above 20%*.
Film grade: The WR1 model was a pioneer in incorporating a film grade in its model. Since its inception, many other models have also started Incorporating film grades. This allows the model to capture context the data could not. Lance Zierlein is a legend in breaking down film for incoming rookies. His numeric grades are available on NFL.com from 2014 on. Players who were drafted before 2014 were given a film grade that did not materially affect their ranking.
Relative athletic score (RAS): Developed by Kent Lee Platte, the relative athletic score evaluates a player’s athletic ability relative to their height, weight, and position based on several known measurables. Each player receives a score of 1-10. Below is the relative athletic scorecard for Julio Jones.
Conference competition score: The conference score applies points based on the level of competition. SEC players receive the maximum points within this metric. G5 schools receive negative points. Prospects also are awarded points if they play on an offense competing with other NFL-level players to compete for targets.
Draft round: Points are awarded on a sliding scale based on the round the player was selected in the NFL Draft.
College fantasy point per reception points per game: At the pro level we know that past fantasy points per game are the metric with the highest correlation to future fantasy points per game. This is also a metric that incorporates the receptions portion of fantasy production into the model whereas metrics such as Dominator only address yards and touchdowns. Receptions account for approximately 38% of NFL PPR PPG so it is an important metric to capture.
Receiving yards per team pass attempt per game (RYPTPAPG): RYPTPA is a favorite metric of the devy Twitter community to forecast future fantasy production. I took this one step further and made it a per-game metric to improve accuracy. RYPTPA measures the receiving yards a player has produced per each of their team’s pass attempts.
Early declare status: If a player enters the NFL draft early it is typically because the NFL has indicated that the player will be drafted in the earlier rounds. Therefore, if a player is an early declare he is awarded five points towards his overall rating.
*Source: Player Profiler
How it works:
For each metric, a player is awarded a score based on the tier they fall in for that metric.
For example, receiving yards per team pass attempt
0.00 – 0.99 = -5
1.00 – 2.39 = 0
2.40 – 2.99 = 3
3.00 – 3.49 = 10
3.50 – 3.99 = 12
4.00 + = 17
Marquise Brown had an RYPTPA of 3.29. Therefore, he was awarded 10 points toward his overall WR1 rating for this metric.
Each player’s metric score is then added to the combined nine-metric formula for each player. This gives them their overall WR1 score.
Thank you to Player Profiler, Lance Zierlein, Grinding the Mocks, NFL Mock Draft Database, and Spaceman prospect database for supplying data. Some of these metrics are dynamic and may change after this article is published.
I hope you enjoyed reading my article. My goal is to provide actionable advice you can utilize to improve your dynasty team. You can follow me on Twitter @force_fantasy.
