Redraft Projections Part 1— Methods, Exceptions, Differences from Ranking, & More
My redraft projections are “finished,” but I’m likely to release them with the divisions as this is a new process or exercise as part of the Fantasy for Real podcast. This podcast episode and post is dedicated to going over a bit of the methodology that will be used in this exercise.
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Estimating Volume x Efficiency Metrics
Here are the various statistics used to project each category (Passing/Rushing/Receiving) for the upcoming season:
Passing - Pass Attempts, TD%, INT%, and YPA (I misspoke on the show; these are the four statistics here)
Rushing - Carries, YPC, and TD%
Receiving - Targets, Catch%, YPR, and TD%
All RBs have a receiving line built around the same methodology. For QBs and WRs, rushing statistics do not use this specific methodology, but are more a general estimation based on trends and history. I only including rushing statistics for WRs who were projected to score 10 or more Fantasy Points in rushing this season.
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Averages, Trends, and Minimal Changes
The numbers mentioned above will rarely-if-ever be far outside of the player’s career norms, trends, or a slight positive bump for young players. Due to this, and because we can’t purely scout on a spreadsheet, my Redraft rankings do not align directly with my Statistical Projections. However, the goal of the statistical projections exercise is to stay within reasonable limits for some of these numbers.
To use some practical examples of how this might effect rankings—
Neither Marvin Harrison Jr. or Rome Odunze are projected to score as highly as they are ranked in Redraft. However, there is a massive difference between the two players. While Harrison’s Catch% and TD% were not great, his YPR and particularly trend with targets are direct numbers that can be applied and create a solid fantasy projection. Kyler Murray is a great QB for fantasy, but not necessarily a great passer to give confidence in dramatically improving that Catch% or TD%, and so while I will move them up marginally, it is ultimately a marginal difference. Because of this, Harrison is ranked closer to my WR20 while he’s being drafted even in Redraft as the WR10. However, Odunze unfortunately scores poorly in all of these metrics relative to his peers. Unlike Harrison Jr., Odunze has neither the target trend nor the target situation that Harrison has in Arizona. Even giving Odunze positive movement in each statistic, Odunze fails to crack my top 40 WRs for redraft projections. My personal faith in Odunze still exists, and I have acquired Odunze this off-season in at least one league. But statistically, Odunze has one of the worst full-season projections. He is expected to be ranked far above that projection even in Redraft, but this helps to highlight some of the methodology behind these projections.
While a player like Rashee Rice has never had a full seasonal output near his current projection, Rice does have a definitive sample from the end of 2023 going into the beginning of 2024 to draw from. When and how to apply trend is definitely going to be very subjective, but Rice is a good case of a player who can actually be projected far above their career highs in raw output due to trends and focusing on these Volume x Efficiency metrics.
George Pickens, due to the trade, is another player likely to get a favorable projection outside of the usual norms. This is because some of the numbers like TD% and his Target volume can at least potentially be favorably adjusted due to the new landing spot. Not quite the same, but Garrett Wilson is another case of a player whose projections are a bit further outside their career norms due to the situation. While Wilson is the only show in town, Fields’ general passing volume leaves Wilson with a projection for his lowest career target output. However, I am projecting the potential for better efficiency with Fields’ rushing ability taking some of the pressure.
Trends versus Averages is always going to be one of the most significant variables. For older players like Tyreek Hill, I am likely to be ruthless with the projection and unwilling to give much leeway for a bounce back. While there are reasons to doubt it, statistically, teammate Jaylen Waddle would be far more likely to see a statistical projection that represents regression to his career norms. Maybe 2024 was the beginning of the end for Waddle, and give his career of injuries that would be less surprising than other players with similar age-related outputs, but right now my projection for Waddle is going to be more of a return to the normal of his career.
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Key Reasons a Player will be Ranked above/below their Redraft projection in my Redraft rankings
Age
While this is redraft and not dynasty, extremely young players who are more likely to have untapped potential are the most likely group of players to be ranked above their redraft projection. Similarly, players on the verge of being old (McLaurin, Sutton, etc.) will not get knocked much for age, but a player like Mike Evans certainly will be ranked below his projection at 32 Years Old due to fall-off risk.
Same/Different Situations
George Pickens statistical projection is bullish, but being in a new situation and on a new team are reasons to doubt the stability in that projection. In contrast, a player like Terry McLaurin actually had a slightly bearish projection given the TD regression I applied, but given the fact that his only significant offense change is bringing in Deebo Samuel, McLaurin’s situational similarity likely increase the stability in his projection, and rank him above his raw statistical projection.
Volume
While we try not to double count, volume security is a reason that goes beyond statistical projection that can further increase redraft stock. Players like McLaurin mentioned in the previous section as well as Sutton, Ridley, and Jeudy are a few examples of players who may get a slightly favorable boost because the reasonable expectations for targets should be in the 130 range for these players. A player who even has a higher volume projection but may not be secure in that volume, like for examples 49ers WRs, might be ranked below their statistical projection because the volume stability does not exist nearly as much. Similarly, a player like Jordan Addison has been a top-24 WR in many formats the last two years, but sharing the #2 role for a rookie QB with T.J. Hockenson does not necessarily create a volume security that many other players have.
Injuries
While rare, a player who is consistently injured may be ranked below their redraft rankings. However, injuries are not only hard to project, but injuries hurt the year-end numbers more than game-to-game numbers on many occasions, meaning these players still have high weekly utility.
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On the pod I go a bit deeper into some of my higher/lower projections that surprised me. The next substack post should include the full projections for the 2-3 Divisions covered on the next show.
Thanks,
C.J.
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