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2020 Rookie Wide Receiver Breakout Chances

How likely is it that each rookie wide receiver breaks out? Steve Gill’s model attempts to shed some light.

 Brandon Aiyuk
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How likely is it that each rookie wide receiver breaks out? Steve Gill's model attempts to shed some light.

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2020 Rookie Wide Receiver Breakout Chances
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Andrew Sama
1 year ago

This is fantastic stuff. Great model and great explanation of how you are interpreting it. This is why I subscribe. I am about to begin a dynasty startup and just bumped Reagor up in my rankings a bit!

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Matthew Stafford
1 year ago

really interesting stuff. Any chance to get Isaiah Coulter added to this. He’s an interesting late round name I’d be curious to see where he fits with this analysis.

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Stephen Gill
Author
Reply to  Matthew Stafford
1 year ago

I’ve left out past non-FBS receivers, as their college data is much more inconsistent/hard to come by, but treating him as an FBS receiver for Rhode Island and plugging him into model he gets about a 10% chance, the same area as Duvernay and Q. Davis. My only piece of hesitance to this is that this is extrapolating to an FCS player when the sample is FBS players, but given there are some pretty small schools in FBS, I think it’s a fairly reliable ballpark estimate. Hope this helps!

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Matthew Stafford
Reply to  Stephen Gill
1 year ago

Awesome that’s really all I was hoping for. thanks!

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matthew digiovanni
1 year ago

I guess we’ll see how this pans out, but I don’t see Reagor or Aiyuk ever being anything special. Really surprised at these results.

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Stephen Gill
Author
Reply to  matthew digiovanni
1 year ago

I loved Reagor’s tape heading into the draft process, but I was surprised by Aiyuk’s high score as well. Perhaps something to keep in mind there is that this model predicts whether a player has a breakout season — i.e. a top-24 season sometime in their career. So even if they’re not anything truly special as you say, there’s still a reasonable chance they meet that standard as good (but not great) talents

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Alex King
1 year ago

Not sure how much to take from this, it already failed the first year with Slayton and McLaurin

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Stephen Gill
Author
Reply to  Alex King
1 year ago

It’s always important to note or remember that for a given model (or this one at least), no player is given a 0% or 100% chance for success, so one has to approach the results of the model with that in mind. And indeed, Slayton and McLaurin were two pretty exceptional prospects, who still haven’t broken out by the model’s standards. So even then, it wouldn’t be accurate to say the model has failed with either of them, at least to this point 🙂

Still, given we only observe 1 success or failure for each player, it can be hard to take something away from the distinction between, say, a 40% chance and a 50% chance. One interpretation of the model’s effectiveness thus far is this: About 85% of the time, the model will predict a higher breakout probability for a player who ends up breaking out than it does for a player who never ends up breaking out. Hopefully that helps.

Thanks for reading!

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dcragel
Reply to  Alex King
1 year ago

I agree, this model also projected JJ Arcega higher than AJB!!

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jeffwalch
1 year ago

Thanks for your work on this! Can you clarify the returning OC variable? If this model projects likelihood of breakout for duration of the WR career – then are you saying that a WR who joins a team the year they change OC’s has significantly lower breakout chance for entire career moving forward? What if the new OC stays on for several years and works with the WR? I originally thought the model was looking at breakout probability for ONLY the WR rookie year. This would make the OC variable make more sense – but if this is predicting for whole WR career then I am struggling a bit to understand that. Thanks for explaining!

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Stephen Gill
Author
Reply to  jeffwalch
1 year ago

“Are you saying that a WR who joins a team the year they change OC’s has significantly lower breakout chance for entire career moving forward?” — Yes, which is surprising, I’ll get into that in a second

“What if the new OC stays on for several years and works with the WR?” — The model, as it stands, only factors in that rookie off-season. In fuller words:

The variable being *predicted* is whether the receiver *ever* has a breakout season. And the OC variable is whether the team’s offensive coordinator is returning from the year *before* the player was drafted to the season *after* — that’s all. So the OC variable just measures whether the team makes a change at OC during the specific offseason when the player is drafted.

My theory is that the power in this variable comes from the OC’s familiarity in the offense: OCs who have called plays for the offense for some time before have a better feel — for the team’s current personnel and what the offense needs — than someone who’s just getting in (so the theory goes). For that reason, we can rely on the former more to get the most out of an expensive receiver, because that OC *knows* they need him in the offense, and will make sure to utilize him. Meanwhile, a new offensive play-caller may come in and start throwing darts at the board (the Broncos are a convenient example this off-season with Jeudy, Hamler, and Albert O).

It’s not very intuitive and I’d be the first to say that the actual effect on receivers’ chances is surprising, but it’s what the data has bore out thus far. It’s definitely the most interesting thing to keep an eye on in future years.

Hopefully that makes more sense. Feel free to let me know if it’s still unclear or there’s anything else you may be wondering! (And sorry for the wall of text, haha)

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