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Not this again: Will Eric Ebron turn out like Brandon Pettigrew?


A New Hope

The Lions took TE Brandon Pettigrew with the 20th overall pick in the 2009 NFL draft, and we Lions’ fans were pretty psyched. He had a strong pre-draft billing as a “solid complement to Calvin Johnson in the passing game” with “good strong hands.” And since we had also snagged the rocket-armed Matthew Stafford with the first overall pick, we Lions’ fans had hope that our offense was finally getting ready to turn around, especially after the disastrous 0-16 season we had the year before.

The Lions tried to use Pettigrew as an offensive weapon. Since he was drafted, only six other tight ends have seen more than Pettigrew’s 456 targets, approximately 91.2 targets per season.1 With Calvin Johnson often drawing double teams, Stafford turned to Pettigrew as his check-down safety blanket. Pettigrew certainly got a fair chance to show off his skills.

Maybe he didn’t understand what “showing off” meant

Here’s a figure of Pettigrew’s yards per catch and yards per target2 plotted along with the drop rates of similarly used TEs, 3 with some notable names highlighted:


It does not look like Pettigrew has learned how to be productive with his opportunities. So what has he been doing with his time in the NFL, if not learning how to be a productive receiving TE? It appears he’s been developing an exceptional ability to drop catchable passes. Here’s his drops per target4 plotted along with drop rates from that same group of TEs in the first figure:


Seven drops for every 100 targets may not seem like a big deal, but a TE drafted 20th overall, who was touted to have good hands, surely ought not be dropping passes more frequently than his lower-drafted peers. While it isn’t fair to call Pettigrew a bust – he is an excellent blocker – he certainly is not the offensive weapon the Lions expected him to be. You probably didn’t notice many Lions’ fans jumping for joy when he was re-signed this offseason, but you might have heard some groans.

Danny DeVitos and Arnold Schwarzeneggers

Enter Eric Ebron. Like Pettigrew, he was an early first-round draft pick, going 10th overall. And like Pettigrew, he was widely considered to be the best TE available in the draft. Scouting reports called him an “advanced route runner” with “outstanding athletic ability and receiving skills” and “ample ability to be a playmaker at the next level.” Ebron himself thinks he’s going to be used like Jimmy Graham.

For the last two decades, whenever the Lions drafted two players from the same position in the first round, those picks have often turned out like bipolar twins: for every Matthew Stafford, there was a Joey Harrington; for every Calvin Johnson, a Charles Rogers; for every Jeff Backus, an Aaron Gibson.

At this point, it looks like Pettigrew is playing the role of the evil twin of first-round TEs. But should we have any hope that Ebron will turn out to be the good twin, the foil to Pettigrew’s lumbering stonehandedness?5

To the data we go!

If it walks like a duck and quacks like a duck…

Here’s how Pettigrew and Ebron stack up physically, according to Combine measureables from

Combine Measure Pettigrew Ebron
Age (when drafted) 24 21
Height (inches) 77 76
Weight (lbs) 263 250
Arm span (inches) 34.88 33.25
Hand span (inches) 10.75 10
40 yard dash (sec) 4.83 4.6
Bench press (reps @ 225lbs) 22 24
Vertical jump (inches) 33 32
Broad jump (inches) 118 120

Other than Pettigrew being a few years older (which RotoVizers will tell you is probably an important thing to keep in mind), these guys look to have pretty similar builds and athletic skill sets. I’m not really sure how meaningful the .23 second difference in 40 yard dash times is – it translates to about a step at a full sprint, which could be quite significant on a go route, but for the intermediate routes over the middle or comebacks along the sideline, an extra forward step is probably a lot less important than good timing and a good grip.

Combine metrics don’t seem to support the notion that Ebron will be a savior for the Lions’ 2014 season. But we can’t stop there: we have a tremendous amount of data from both Pettigrew’s and Ebron’s collegiate careers. If we look at game-by-game performance, we may be able to uncover some reliable differences in receiving abilities between the two TEs.

Quick! To the gamelogs!

I used the play-by-play data from ESPN to extract individual statistics for every game in which Pettigrew and Ebron had at least one target. Unfortunately, I couldn’t find data on drops for either player, so I couldn’t calculate a drop rate. Instead, I calculated catch rate (number of catches per target) as a proxy – it isn’t exactly the same thing, since a player could fail to catch a pass for many reasons other than a drop, but it isn’t a terrible stand-in.

Since Ebron only played for three seasons, and because Pettigrew was hurt for much of his senior year, I’m only going to compare these guys across their first three collegiate seasons as well.

If a picture is worth a thousand words, what about a thousand pictures?

Let’s take a look at some figures.6 First, let’s look at total targets per game, along with the market share of each player’s team’s total targets per game:ebron.pettigrew.chart

So, both players start off with relatively minor roles in their respective offenses, which increased over time. By their third seasons, both players had major roles in their teams’ passing games, though it appears that Ebron’s was slightly bigger than Pettigrew’s (2.5 more targets per game for Ebron, and about 4.75% more of his team’s total targets).
What did they do with those targets? The next two figures look at catch rate and yards per catch:

From these charts, it looks like Ebron was doing a bit more with his opportunities (catching them and turning into yardage) than Pettigrew, but only in their second seasons; by their third seasons, it looks like everything is pretty similar again (when error bars overlap, that’s generally a good sign that there aren’t reliable differences). That second season difference could be due to the huge uptick in targets for Ebron from year 1 to year 2, but it’s hard to say without adding some statistical control. Speaking of…

Everyday I’m modeling

Sometimes pictures can really help clarify similarities and differences across individuals, but that doesn’t seem to be the case here. So, we need to break out the big guns, in this case, the ANCOVA (analysis of covariance). ANCOVA is a technique that tests for differences in continuous dependent measures (like all of the measures in the figures above) across different levels of a categorical variable, while controlling for other continuous variables that might have an influence on the relationship you’re trying to test.

WARNING! Technical details of models are discussed in the next paragraph (as if that last paragraph didn’t deserve a warning of its own).

I ran several separate ANCOVAs: my dependent variables were receptions, catch rate, and yards per catch; my predictor was player (Pettigrew vs. Ebron); and my covariates were as follows: player age, number of games played, targets, proportion of team’s targets, quarterback completion percentage, total offensive plays, proportions of pass vs. run plays, total team offensive yards, proportions of pass vs. run yards, point differential, home vs. away, and whether the team’s opponent is from a BCS conference.

Still here? Whew. Here’s the summary of important bits. In the table, you’ll see the effect of player – if the p-value is less than .05, that means there’s a reliable difference between Pettigrew and Ebron on a measure, even after holding all of those other variables constant – and statistically significant covariates.

Effect Estimate p-value
Player -1.204 0.595
Targets 0.783 0.005
QB Completion% 4.653 0.0105
Receiving Yards
Effect Estimate p-value
Player -33.678 0.494
Yards per Catch
Effect Estimate p-value
Player -24.889 0.168
Games played 0.336 0.016
QB Completion% -34.795 0.017
Catch Rate
Effect Estimate p-value
Player -0.296 0.619
QB Completion% 0.97 0.04

See how for every Player row, the p-value is bigger than .05, and in most cases, that it’s pretty close to .5? This suggests that the Player variable doesn’t have a reliable effect on any of the dependent measures, which supports my suspicion – after controlling for all of those important covariates, there doesn’t appear to be a significant difference between Brandon Pettigrew and Eric Ebron.7 Both seemed to be equally adept at catching and advancing the ball in college, so long as they had a QB capable of getting it to them.

So is all hope lost for Detroit?

Based on all of these analyses, I don’t think that Eric Ebron is going to be the next Jimmy Graham, or even a real offensive savior for the Detroit Lions. I do think he’ll get a chance to showcase his talents, since the Mayhew regime doesn’t like to give up on early round picks too quickly. I think the Lions already have enough weapons, from Megatron and Golden Tate to Reggie Bush and Joique Bell, to be able to compete in the NFC North. Ebron could be icing on the cake, but the data just don’t seem to be that up.

Since we focus on actionable fantasy content here, you might be looking for a projection for Ebron. In this case, I don’t think that’s a responsible thing to offer, considering the coaching changes in Detroit. Caldwell and his staff liked Ebron enough to pass over some terrific defensive talent at pick 10, so presumably they’ll try and give him as many opportunities as they can, but whether he gets treated like Jimmy Graham, or like Dennis Pitta, or even like Brandon Pettigrew, remains to be seen. I will say this, however: Eric Ebron will not be on any of my fantasy teams in redraft leagues, or anything but the deepest of dynasty leagues, like the kind where you get legitimately excited about practice squad players. But as a long-suffering fan of the Lions, I really hope that I’m wrong.

  1. according to data extracted from  (back)
  2. from  (back)
  3. These are the top 20 TEs in terms of most targets per season since 2009  (back)
  4. again according to  (back)
  5. According to Google, this is the 119th use of “stonehandedness” on the web. Nice.  (back)
  6. Error bars represent standard errors  (back)
  7. I ran these same analyses with all 4 years of Pettigrew data, and found same results, just slightly different parameter estimates  (back)

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