2014 Draft Class – Wide Receivers and Tight Ends

Summer time is over for us up here in the Deep North. Those two 90 degree days were brutal, let me tell you. I’ve spent the summer cocooned in my office cooking up the latest and greatest that I can offer in predictive football statistics both at the college and professional levels.

If you’re new to the site during a football season, I’ll be talking wide receivers and quarterbacks here, both at the collegiate and professional level.

And to start, let’s talk NFL rookie wide receivers. I made some predictions about rookie wide receivers for the 2013 season and they were…well they were terrible. I spent most of my spring and summer ripping apart the model and figuring out what went wrong. I discovered two very important elements of predicting wide receivers that needed to be addressed.

#1) What’s your Dependent Variable?

One of the trickiest things about doing football analysis is figuring out exactly what you want to measure and what you want your wide receiver or pass catching tight end to do. Many people have tried to deal with this issue when it comes to pass receivers with varied success.

My approach in 2013 was to use an in-house metric I created that measures pass catching ability. This, it turns out, was a horrible mistake. The reason is that NFL teams typically use particular wide receivers in particular roles. One receiver goes deep, another goes across the middle, etc. This creates a problem because it confounds pass catching ability with depth of target. Deep passes are successful less often, but the large impact they create on the game can offset their lower success rate.

For the 2014 predictions, I have changed the DV I use to get around this problem. I start with NFL Yards per Target. Yards per Target is much less susceptible to the depth of target problem. It’s not perfect, but it’s less bad than what I was using last year. I also do a little hoo-doo with the numbers to make them more consistent year-over-year. The first thing I do is to subtract the league average Yards per Target for the given season. This corrects for changes in the passing game across seasons, rule changes, passing tendencies, etc. Next, I use a highly constrained (sort of) structural equation model to pull out the effect of quarterback and offensive system on yards per target. I call it a “sort of SEM” because the model is incredibly constrained due to the realities of the game I’m modeling. It’s so constrained that what I do cannot be called a true SEM. But the technical details are probably not why you’re here. The ultimate result is a metric I call Receiver Influence on Yards per Target (RIYPT; in my ears “ripped”). We’ll use this metric at the NFL level as our DV.

#2) Lower-Level Interactions

Issue #2 I didn’t appreciate when making the 2013 predictions is the importance of interactions. You see, RIYPT at the NFL level predicts productivity. In fact, it’s the only receiver-focused metric that predicts NFL level performance. I made a bad assumption that the same situation would exist at the college level. It doesn’t. At the NFL level, every receiver has great hands. If you don’t have great hands, you don’t get to be a receiver in the NFL. Once we account for depth of target, there’s no meaningful variance in ability to catch a football among NFL pass receivers.

This is not true at the NCAA level. You can be a college receiver without having exceptional hands. As long as you make up for it with lots of long gains, less-than-stellar hands aren’t the handicap that they can be in the NFL. To deal with this, you need an interaction term. Interactions find the receivers that have good enough hands to make it in the NFL while also having the ability to gain useful yardage on an efficient basis.

That’s enough details. Down to brass tacks. Who should we be looking at as far as success at the wide receiver position? Remember, our DV is yards per target, so our definition of success may be different than the actual outcomes obtained on a football field. You can have a large RIYPT, but if you don’t get a lot of targets you won’t gain a lot of yards (see Ladarius Green in 2013).

The full table can be found above in the web page header. My top five rookie wide receivers, according to Predicted NFL RIYPT are…

  1. Brandin Cooks – Oregon State – 2.56
  2. Jalen Saunders – Oklahoma – 2.33
  3. Cody Latimer – Indiana – 1.99
  4. Marqise Lee – USC – 1.97
  5. Cody Hoffman – BYU – 1.93

Here you can see I expect Brandin Cooks to be head and shoulders above the rest of the rookie receivers in the NFL. This is especially true now that he is a member of the New Orleans Saints. Jalen Saunders will be a stickier situation. He’s a lower round draft pick, so it will be more difficult for him to see the field compared to Cooks. Second, he has (at the moment) Geno Smith throwing to him. Past visitors to the site will know I’m not high on Geno Smith. Geno will likely improve next year compared to 2013, but I still expect him to be in the bottom fifth of the league in terms of completion percentage and passing yards.

My top five pass catching tight ends according to Predicted NFL RIYPT are…

  1. Eric Ebron – North Carolina – 1.37
  2. Richard Rodgers – California – 1.12
  3. Marcel Jensen – Fresno State – 1.04
  4. Blake Jackson – Oklahoma State – 1.02
  5. Jace Amaro – Texas Tech – 1.02

Once again, we have one prospect that is head and shoulders above the rest, that being the prospect everyone expected to be on top, Eric Ebron. The second name on that list probably surprises a few people. If you look up scouting profiles of Richard Rogers, they’re not that glowing of him. I guess we’ll see where we end up. Rodgers also ended up in a great place to succeed as a pass catching tight end – Green Bay – so hopefully we get an opportunity to see him succeed.

This wraps up our rookie preview.  Up next, we’ll predict 2014 yardage totals for veterans from 2013 data.

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