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Thoughts on Completion Percentage By Position

According to Football Outsiders, over the last three years, 60% of all passes have gone to wide receivers, 21% to tight ends, and 19% to running backs. There are some players who are position hybrids, of course, but as a general rule, wide receiers catch about 56.3% of passes, tight ends have a 63.1% catch rate, and running backs record a reception on 72.4% of their targets. In theory, those numbers should help us figure out which teams (and passers) have completion percentages that are artificially high (or low) because of a high number of passes to running backs (or receivers).

Let’s use the 2013 Chiefs as an example. Last year, 57% of Kansas City passes went to wide receivers, 28% to running backs, and 15% to tight ends. If we use the league-average numbers on passes to players at each position, we would “expect” Kansas City to complete about 61.9% of their passes if the Chiefs were an average passing team. That’s a number that’s slightly higher than league-average rates because the Chiefs threw very often to running backs and not so often to wide receivers.

But as it turns out, projecting a 61.9% completion percentage isn’t the best projection for the Chiefs. I performed a regression analysis to best-fit completion percentage based on the percentage of team pass attempts to running backs and percentage of team pass attempts to tight ends.1 Here’s that formula:

Completion Percentage = 0.525 + 0.135 * RB_%_of_Targets + 0.263 * TE_%_of_Targets

Since the Chiefs threw 28% of their passes to running backs and 15% to tight ends, Kansas City would be projected to complete 60.2% of passes. Now let’s say those numbers were reversed: if 28% of KC attempts were to tight ends and 15% to running backs, the projection would be 61.9%. That’s not an insignificant difference, but the interesting part is that the variables are moving in the opposite of the direction we would expect.

After all, running backs have significantly higher catch rates than tight ends, but this analysis tells us that the more teams throw to tight ends (at the expense of pass attempts to running backs), the higher the expected completion percentage. The formula places a weight on the tight end number that is nearly double the weight placed on the running back variable, when we would normally think the reverse would be true. So what’s up with that?

That’s a good question. Does it mean that throwing passes to tight ends is somehow correlated with quarterback ability, or that throwing passes to running backs is correlated with the lack thereof? It’s easy to think of Drew Brees and Tom Brady throwing lots of passes to the tight end, but Matt Schaub, Sam Bradford, and a rookie Cam Newton also show up on the list of teams with the highest percentage of passes to the tight end. Meanwhile, no single team threw more often to running backs over the past three years than the 2013 Saints. I looked at teams that threw the most passes to tight ends at the expense of their running backs. The ten teams with the strongest preference in that direction had a completion percentage of 60.3%, while the ten teams that were most RB-heavy (at the expense of tight ends) were at 60.1%. That’s pretty weird considering teams *should* have a much higher completion percentage when throwing to backs.

Here’s something else pretty weird. The teams that threw the most to tight ends (instead of running backs) completed 69% of passes to RBs, 57% to WRs, and 63% to TEs. The teams that threw the most to running backs instead of tight ends completed 73% of passes to RBs, 54% to WRs, and 65% to TEs. Again, I’m not sure what the answer is here, so I’ll open it up to the group.

It seems reasonable to suggest that great tight ends open things up for the offense. As a result, passes to tight ends could be a proxy for talent at the position, and that could lead to better numbers for the wide receivers and running backs. So I’ll look to you folks: what do you think is driving these results?

  1. Because the percentage of passes to RBs, WRs, and TEs would sum to 100% for every team, you wouldn’t run the regression on all three variables. []

{ 12 comments… add one }

  • Sunrise089 August 5, 2014, 12:35 am

    I’m guessing sample size and/or QB quality issues. Notice the chance in WR completion percentage between the RB-heavy and TE-heavy groups.

    Could it be checkdowns to the RB happening more often in situations where the QB doesn’t have downfield accuracy?

    • Chase Stuart August 5, 2014, 8:53 am

      Sample size could be an issue; no reason not to extend it to ten years or so at some point.

      That’s a reasonable conclusion. The question, though, would be if those QBs don’t have downfield accuracy, wouldn’t they throw more checkdowns, and wind up with a high completion percentage?

      Also, the top five teams since 2011 in passes to the RBs were the Chargers (2011/2012) or Saints (all years) so I wouldn’t say that idea holds up.

      Here’s another thought. Perhaps teams that don’t throw much to the RBs just throw lots of short passes to WRs and TEs. That would be an unsexy conclusion, but could be consistent with the data.

  • Ben August 5, 2014, 3:30 am

    You throw to who’s good so the teams that throw to position x more have a higher completion percentage to position x.

    • Chase Stuart August 5, 2014, 8:45 am

      That’s not really the case. This is easily seen when it comes to individual receivers (i.e., the team’s top-targeted WR could have a lower catch rate than the team’s WR3), but you see it with position groups, too. For example, in the example above, the teams that threw the most to the TE had a lower completion percentage when throwing to the TE than the teams that threw to that position the least. For example, the 2011 Bills threw just 10% of passes to the TE, but completely 85% of those passes. The Steelers and Bucs last year were at just 17% of targets to TEs, but both completed 72% of passes to the TE.

  • jt August 5, 2014, 9:18 am

    fascinating work. random thoughts.
    1. positional blurring. is a RB lined up in the slot a RB or WR? Is a TE split wide a TE or WE? plays like these may skew results?

    2. receiving ability of RB. if RB good, passes go his way. if not, targets go to TE instead.

    3. quality of OL. If OL bad, RB or TE kept in to block. does that affect target distribution?

    4. Coordinator effects. do certain coordinators force their scheme on ill suited players, resulting in suboptimal target distribution?

  • Ben W August 5, 2014, 9:51 am

    Maybe teams with bad pass catching RBs turn to their TEs more in the short passing game and teams with poor receiver play turn to their running backs more often as their WRs are covered. Or maybe teams that throw the most to RBs have a more vertical passing game. Shots in the dark here.

  • James August 5, 2014, 10:41 am

    I think it’s because a higher completion percentage isn’t necessarily good without proper context. I bet most passes to TEs are short and of the checkdown variety which boosts TE completion percentages, but they aren’t very valuable passes so they don’t happen often. But those few teams with excellent TEs give them lots of targets, but because they run deeper, more valuable routes their completion percentage suffers.

    To make up some numbers: 26 teams have bad TEs who catch 65% of their passes but get only 10% of their team’s targets. 6 teams have good TEs who catch 60% of their passes but get 25% of their team’s targets. If every team throws the same number of passes and completes 60.8% of its other passes, then our leaguewide completion percentage is 61.1, leaguewide TE comp% is 63.2%, teams with good TEs complete 60.6% of their passes, and teams with bad TEs complete 61.2% of their passes. I think that matches the actual results you posted, right? TE comp% is higher than league average, but teams that throw more passes to TEs have a lower comp%.

    In other words, bad TEs act like RBs and get a few number of targets, good TEs act like WRs and get a lot of targets, but because most teams have bad TEs they skew the league-wide averages.

    Of course, it isn’t necessarily good and bad TEs. It could be QB talent or offensive systems that make TEs act like WRs. For that matter, there’s probably tons of cause and effect going on here with all three factors playing a role. I would like to compare the TE comp% with average depth of target or YPA, as that would probably explain a lot (and tell me if my theory is right).

  • mrh August 5, 2014, 4:48 pm

    I don’t know if its a big enough number of targets to matter, but rz usage skews completion%. From pfr play index, 2004-2013:

    RB 73/69/62
    TE 65/56/54
    WR 58/52/44

    That’s completion% for non-red zone/opp 6-20 yd-line/opp 5 yd-line to goalline. Comp% decreases as the field shrinks. So the mix of passes to the different positions at different locations on the field could make a difference. Having said that, only 2.7% of all attempts are inside the 5 and only 10% between the opp 6-20 yd-line. So the lower comp% in the rz could be overwhelmed by the 87% of all passes taking place outside it.

  • Ajit August 6, 2014, 8:34 pm

    My theoretical explanation also dovetails with the overall passing explosion. The big gains are coming from the middle of the field, meaning tight ends and slot receivers. This is because they are exposing the team’s weaker coverage players – hence why the tight end numbers have exploded. I suspect over time, defenses will adjust to take this away.

  • Nick Bradley August 8, 2014, 9:45 am

    Not sure TE data is good.

    We discussed this last week, and some teams with either an elite quarterback or tight end run those killer deep routes to tight ends, while some just do a lot of TE screens.

    Alex Smith is captain checkdown, for example, while drew brees hits Graham way down field. San Francisco does a ton of deep routes with Davis.

  • Nick Bradley August 8, 2014, 9:47 am

    Fascinating idea: EPA/P by position, or EPA share by position.

    That should take into account route distance and accuracy.

    • Nick Bradley August 8, 2014, 9:51 am

      Example, 1/3 of gronks routes in 2013 were deep, but he had an EPA/p of .43, really high. Gonzalez ran very few deep rout but had a much higher catch rate and had an EPA/p of .40.

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