So far, I’ve looked at the basics of offensive identity in 2018 (plays from scrimmage; how many fantasy points (FP) those plays generated; how many of those plays were “wasted” from a fantasy perspective; and the relationships between wins and plays and FP) and the running game (including the correlations between running plays and winning, RB carries and FP, and RB1 “share” and fantasy performance). Last week, I began looking into the passing games of the 2018 offenses with their overall amount of passing and efficiency at doing it, and their use of WRs. I’ll wrap up this with how 2018 offenses used their RBs and TEs in the passing game.
A key point of last week’s article was how important target volume is to WR fantasy output. As we’ll see, for TE and RB fantasy production, targets explain even more. Here are the raw TE target numbers:
Sometimes low TE targets are due to another position group taking targets away: SD and DET are good examples, with RBs who were 4th and 5th in the league in targets and TEs who were 28th and 31st in the same category. It’s more usually WRs and TEs who interchange targets, since 2002, WR and TE targets have had a -0.27 correlation league-wide. The negative sign means as one stat goes up, the other goes down. While it is only a moderate correlation, it persisted over a long time and was -0.32 in 2017. But 2018 was different: the correlation between those stats was just 0.02, essentially meaning they were unconnected. Meanwhile, RB and TE targets had a modest -0.20 correlation in 2018; since 2002 the correlation has been 0.00. Before 2018, knowing how many targets a team’s RBs got told us NOTHING about the number of targets its TEs would see, but a team’s WR targets had told us something about its TE targets (and vice versa). I believe 2018 was an anomaly in this regard but it bears watching to see if this is a trend that makes predicting WR targets harder.
Looking at the chart above, PHI’s total obviously stands out: it’s extremely unusual to see any team-level stat more than three standard deviations from the league average. The 212 targets sent to Eagles TEs last year was the 2nd highest total of any team since 2002. Only the 2011 Aaron Hernandez-Rob Gronkowski Pats had more (an astounding 237). While Zach Ertz’ had 156 targets, don’t overlook the 44 thrown to Dallas Goedert. Only O.J. Howard had more as a team’s TE2, and he was really the #1 TE in Tampa, only sliding to TE2 status by virtue of missing 6 games.
Last year I wrote:
The Eagles and Chiefs remained at the top of the list. The Bears did increase their TE usage, from 78 to 92 targets, but remained below average in that regard. Burton himself saw 76 targets, 11th in the league (he finished as TE15) and basically what the Bears TEs as a whole saw in 2017. The Bears did not use their secondary TEs much, with just 16 targets to the other players at that position, which was less than all but SF, NE, and MIN (tied with ARI).
Note that NE was below average in TE use even with Rob Gronkowski; don’t necessarily think his replacement will get all of his 72 targets in 2019.
DET was 2nd last in TE targets and went out and drafted one at 8th overall. BUF (4th fewest) also got a TE relatively high, in the 3rd round, and both teams also used a 7th on the position. SEA (3rd fewest) did almost nothing, adding Jacob Hollister in trade (16 total targets in 2 years with NE) so we can assume the Seahawks will either make another move or will continue ignoring their TEs. MIA (fewest) added two FA TEs, including forever TE tease Dwayne Allen and Clive Walford (13 targets in his last 14 games), so there is not a clear signal that the Dolphins will involve their TEs more.
Note that WAS gave its TEs an above average share of targets, ranking 5th in this category (and 6th in total TE targets, but not as far above average in that category). More passing in WAS this year could translate to more total TE targets if you’re still a Jordan Reed-truther.
Note too that NE was in the red as far as TE share goes. I think Austin Seferian-Jenkins is almost certain to be over-drafted.
Note that (historical) positional target shares are much more highly correlated than total targets are:
- WR-TE share: -0.76 correlation (vs. -0.27 for total targets)
- WR-RB share: -0.45 (-0.03)
- RB-TE share: -0.17 (0.00)
Again, the correlations are almost all negative. Of course “share” is a zero-sum statistic: more share for one position necessarily means less for another. But total positional targets can go up in two ways: targets taken from another position (a bigger slice of the pie) OR more total passes (a bigger pie).
And of course, more total passes necessarily means more targets across the positional groups. But there is essentially no correlation between more total passes and target share: how the pie gets divided is a function of the offense’s identity (favors RBs over TEs for example) and the talent (the Dick Vermeil/Mike Martz offense in STL almost never used its TEs; when Martz went to DET that held true but Vermeil in KC with Tony Gonzalez was much more TE-friendly).
As mentioned at the beginning: targets matter for TEs too. TE FP production is highly correlated with total targets. In fact, 90% of TE FP in 2018 were due to target totals (r-squared = 0.8993).
Four teams in total TE targets were in the green. IND was very efficient (FP-wise) in targeting its TEs, SF and KC were close to average, and PHI was fairly inefficient. The Eagles TEs were efficient in this metric the previous year. Did their efficiency drop from over-use? Or from using a rookie (Goedert) to replace a veteran Burton? Goedert was actually very close to Burton in efficiency, and more efficient than Zach Ertz. Goedert had a higher catch rate, yards per catch, and TD rate. Of course, Ertz garnered more attention from defenses, so Goedert might not better Ertz’ numbers if given more targets. But it’s possible that some of Ertz’ targets could shift to Goedert this year. (Ertz also averaged about half a target for per game with Nick Foles vs. Carson Wentz the last two years, and the TE had 1.5 more targets/game in 2018 when Alshon Jeffery was out – and 1.5 fewer when Golden Tate was in, so a lot of variables could affect Ertz’ totals this year.)
Generally, the teams that didn’t use their TEs much weren’t very good at it, so it made sense to throw to other positions. SEA is the exception – although TE1 Nick Vannett wasn’t very productive. Will Dissly and Ed Dickson combined out-scored Vannett 80.8 FP to 73.9 on about two-thirds of Vannett’s targets (27 vs. 43). SEA seems unlikely to involve its TEs more, but Dissly could be something of a sleeper in deep or TE-heavy formats.
That leaves RB targets:
The top four teams in RB targets also had the four oldest everyday QBs. PIT and GB broke the trend, and NE and NO have had RB-heavy passing games for a few years. Injuries to other players factored into the Giants’ and Chargers’ use of RBs, and I’m not sure why DET moved from around league average to above average, although the departure of Eric Ebron may have had something to do with it.
HOU and TEN remained near the bottom in RB targets in 2018, as did ATL. I’d think a new OC in ATL might increase the usage of RBs in the passing game, but Dirk Koetter was near the bottom in RB targets in TB as well. SEA dipped into the red but had been below average in 2017 as well – and since the team didn’t throw much overall, it’s not a surprise the RBs didn’t see many targets.
Notice that SEA was near average in RB target share: their low RB target totals really were a function of low pass totals, while ATL, HOU, and TB the issue for RBs in the passing game was predominantly target share. TEN was more like SEA.
On the downside, PIT and MIN both saw significant decreases in RB share, probably a combination of OC changes and the absence of good pass-catchers (Le’veon Bell and Jerick McKinnon) they’d had in 2017.
A big change from 2016 to 2017 was how much share shifted to the RBs: from 19% to 22% league-wide. It dipped to 21% in 2018, but that’s still on the high side compared to the period from 2010-2016, when RBs’ share was between 18% and 20%. I’d expect things to remain in the 21-22% range in 2019, with the obvious effect on RB FP totals.
While the Saints again were efficient in targeting RBs, they were nowhere near as efficient as in 2017. The other two teams at the top of the RB target table, the Patriots and Giants, were only around average in generating FP from those targets. CHI, CAR, and the Chargers were heavy RB users who were good at getting FP out of their RB targets, but DET, OAK, DEN, and IND were not as productive.
The Chiefs were off the charts in efficiency with their RB targets but that may have partly been due to the threat of Tyreek Hill taking safeties deep. It will be interesting to see if KC can remain this efficient with its RBs if Hill misses time.
Overall, about two-thirds of RB Receiving FP can be explained by target totals (R^2 = 0.6751). This is about the same as for WRs overall.
Now we come to the last category I analyze: RB1 passing game identity. And this is important, because an RB with around 250 carries, could be the #1 back in FP/G or the #29 or #33 guy based on their usage in the passing game. Todd Gurley had 81 targets (256 carries), Adrian Peterson had 26 (251), and Jordan Howard had 27 (250). Even if Gurley had Peterson’s 4.2 YPA and 7 rushing TDs instead of his actual 4.9 and 17, he would have still finished as a Top 10 back.
Gurley ranked 5th among RB1s despite missing two games. The green bars represent, from left to right: Christian McCaffrey, 2nd in FP/G; Ezekiel Elliott (6th), Gurley (1st); Alvin Kamara (4th), and Saquon Barkley (3rd). (Note that unlike most of my charts, the lines don’t define one standard deviation, because of the extreme variation in RB1 target totals, from McCaffrey’s 124 targets to Gus Edwards’ 2.)
It’s not a surprise to see Edwards barely register in total targets. But Sony Michel is the (semi-) shocker. Not because a rookie RB might be less involved in the passing game, but because the Patriots led the league by far in total RB targets. Note that Michel’s 64% catch rate and 7.1 yards per reception were both well below average (76% and 8.0). Missing three games hurt Michel’s target totals – but he was still the #1 back on the team in carries, so that’s not the total explanation. It’s not unusual for NE to use a back almost exclusively as a ball-carrier: LeGarrette Blount played 49 games in NE with 13.8 carries/game (Michael averaged 16/game last year) and just 24 TOTAL targets. Michel needs either more targets or more TDs (6 last year) to register as more than an RB3. He’s worth taking as an RB3 with upside (Blount had 18 TDs in 2016), but don’t count on it (the return of Brandon Bolden is strange in that he seems to be another ball-carrier-type RB).
DET, MIA, PHI, and TEN also seldom used their RB1s in the passing game. The Eagles backfield was just a mess. The other three teams all used pass-catching backs: Theo Riddick, Kenyan Drake and Dion Lewis had between 67 and 74 targets. Drake is the intriguing name, as the RB1 in MIA last year, Frank Gore is gone, and no clear replacement has been added (unless you count former 4th-round pick Mark Walton, whose NFL carries-to-arrest ratio of less than 5 isn’t promising).
Basically, the teams in the red in RB1 target share are those that were low in RB1 targets, with the exception of TEN. In the green, ARI was close to that level in RB1 target total but just missed. PIT is a similar story; otherwise, the green totals and share bars line up.
David Johnson really suffered last year from poor QB and offensive line play. Usually, an RB1 3rd in rushing share and 6th in target share is going to rank higher than RB11 in FP/G. But his team’s low overall play total and yards/carry and yards/catch well below his career averages really killed his fantasy numbers. There is no telling what a rookie QB and rookie HC/OC will do (and I’d like to have seen more resources go into upgrading the line), but if Johnson again gets 250+ carries and 70+ target,s you have to think he’ll improve his fantasy rank.
Last chart:
Two players to highlight on this chart. First, look at the CAR diamond (McCaffrey). Clearly, the Panthers were doing the right thing throwing to him. Contrast that with the NYG/Barkley marker. The Giants didn’t have many options, especially when Odell Beckham got hurt. And Eli may not have the arm any more to do more than check down/dump-off. But it was not a good use of targets to go to Barkley that often, so it’s worth asking yourself if the offense will continue to be structured that way.
Second, KC/Kareem Hunt. He was about the most efficient RB1 in making FP out of targets. For the 2nd straight year. With Alex Smith and then Patrick Mahomes. I know the team had Tyreek Hill and Travis Kelce, but I just think Hunt merited more targets. Damien Williams did a decent job out of the backfield once Hunt was cut, but newly added Carlos Hyde was featured in this space last year as one of the most INefficient RBs in the passing game – and he was worse in 2018.
Basically, while I talk a lot about efficiency on these FP vs. target charts, for RB1s, it’s almost all about volume as you can see by how close the diamonds are clustered to the regression (dotted) line. Overall, 94% of RB1 Receiving FP is determined by opportunity or targets (r-squared = 0.9444).
Overall, the first thing to focus on in all these charts are teams that are on the extremes one way or the other and then make a change: add key players in FA or the draft, get a return to health from an important guy, hire new coaches, etc. This opens up opportunity for big improvement or steep decline – or creates the possibility of regression to the mean. The second thing is to look at teams who have a historic identity and are likely to offer stability (for good or bad) at a position. As the site discusses the individual coaches in subsequent articles, focusing on that will be a key thing.
FIN
