Forecasting 2024 NFL Rookie WR Success: 3-Year Model
![Forecasting 2024 NFL Rookie WR Success: 3-Year Model Forecasting 2024 NFL Rookie WR Success: 3-Year Model](https://www.4for4.com/sites/default/files/styles/833-respbreakpoints_theme_for4_theme_tablet-max_1x/public/articles/USATSI_23238787.jpg?itok=-87jbJZa×tamp=1716217699)
The 2024 NFL Draft is now in the books, giving us dozens of new offensive players to consider for our fantasy teams. In this article, I will discuss some of the value picks available at wide receiver in rookie drafts.
Our friends at Dynasty League Football (DLF) have already compiled some post-draft rookie ADP, and Marvin Harrison Jr. is the unanimous top receiver off the board. I wouldn't argue with that assessment. While the analytical methods I use below rank him lower than the next two receivers taken, Malik Nabers and Rome Odunze, it seems clear that, like past Ohio State receivers, Harrison is "good at football" in a way that the doesn't always show up in the statistics. He also has a better landing spot than the other two. Overall, I'm happy taking Harrison as the first rookie receiver.
More NFL Rookie Forecasting: RB | LB
Forecasting Wide Receiver Success
I estimate the odds of each player putting up a top-36 season within the first three years of their career using a combination of three models. The first is a simple statistical model (built using logistic regression) and the other two are more sophisticated machine learning models.
Despite its simplicity, I put much more weight on the simple statistical model, which uses only college production and draft capital. Of course, we cannot reasonably expect to correctly predict the success odds of all receivers using just two variables, but that is not the goal of the model: the goal is to identify undervalued players. Using the model in this way will continue to work as long as fantasy drafters continue to put insufficient weight on college production and draft capital, as I expect they will do.
As we discussed in previous seasons, this approach has an excellent track record of finding undervalued players. Last year was no exception. Of the four players we identified as undervalued, two of them, Zay Flowers and Jayden Reed, have already delivered a top-36 season in their first year. Tank Dell was arguably our best pick last year. Available in the third round of rookie drafts, Dell was easily on track for a top-36 season before missing the final five games due to injury. Despite missing so many games, he still finished 38th for the full season, just below our success line. Our fourth pick, Josh Downs, was no slouch either: he finished as 43rd ranked receiver for the full season. In general, the odds of second and third-round rookie picks delivering a top-36 season in their first three rounds is around 1 in 3, so these results are excellent.
The obvious blemish on last season's record is that the best rookie receiver, Puca Nacua, was not identified by the model. This is unsurprising given that Nacua was a fifth-round pick by the Rams. Overall, the odds of fifth-round draft picks being successful receivers in the NFL are very slim, so models like ours based on historical data will never give them a high score. That said, there are lessons that we as fantasy managers can learn, apart from the models. In the past, I have routinely given Steelers receivers a small bump due to the track record of their scouts identifying good receivers. Given the success of both Nacua and Kyren Williams, another fifth-round pick, I will probably increase my personal estimate of late-round picks by the Rams going forward.
That is enough about last season. Here are the players that stand out to me as most undervalued this year (the full table of rankings appears at the bottom of the page):
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