Interceptions by Targeted Receiver

One thing I've learned to appreciate is how much interceptions can be the fault of the intended receiver. Whether it's a bad route, a misplayed tip, or a failure to fight the defender for the ball, receivers can often be as much if not more at fault than the passer.

We're always happy to list interceptions by quarterback or by defender, but rarely do we see interception stats by receiver. So I put one together. These are not interceptions I have qualitatively determined to be the receivers fault, but simply all interceptions when the receiver was listed as the intended target.

82-K.Winslow TB7
89-S.Smith CAR6
83-V.Jackson SD6
17-D.Moore OAK6
13-St.Johnson BUF5
84-R.White ATL5
83-F.Davis WAS5
87-R.Wayne IND5
87-B.Celek PHI4
86-D.Nelson BUF4
12-A.Roberts ARI4
82-M.Manningham NYG4
87-A.Caldwell CIN4
80-M.Thomas JAX4
87-E.Decker DEN4
10-D.Jackson PHI4
17-A.Benn TB4
88-T.Gonzalez ATL4
88-E.Sanders PIT3
80-J.Graham NO3
85-A.Gates SD3
82-D.Bowe KC3
11-L.Fitzgerald ARI3
17-A.Collie IND3
11-S.Smith PHI3
10-J.Gaffney WAS3
19-D.Jones BUF3
17-L.Naanee CAR3
12-J.Ford OAK3
18-A.Green CIN3
87-R.Gronkowski NE3
84-B.Lloyd DEN3
88-D.Bryant DAL3
84-E.Dickson BAL3
19-B.Marshall MIA3
81-C.Johnson DET3
82-B.Hartline MIA3

Obviously, the QB, the lines, and the secondary all play roles. Interceptions could be considered the culmination of the efforts and errors of all 22 players on the field. Situations and luck play their part as well. And this list does not necessarily mean the guys at the top aren't doing their job. It could mean just the opposite. Maybe they're drawing more than their share of double coverage, or they are their QB's security blanket--the guy his QB instinctively looks for when in a panic. Still, it's a different way to look at one of the most important plays in the game.

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13 Responses to “Interceptions by Targeted Receiver”

  1. DSMok1 says:


    Could you incorporate those into the wide receiver stats page somehow? Should this be reflected in the player's WPA and EPA?

    Related to this--is there a way to disentangle the interception "accountability" somehow? For instance (this is something I did with your PBP data from 05, I think it was): create a regressing predicting likelihood of interception modeled as a*QB + b*WR + c*Defense = odds of interception, where the set is limited to teams with multiple QBs playing significant time, constrain (a + b + c)=1.0, and then solve for a, b, and c.

    Actually, I don't think I ran that for interception%, but for some other results... What do you think, Brian?

  2. Boston Chris says:

    conversion to a rate stat?

  3. Adam Davis says:

    I second the notion of wanting to see it converted to a rate. This was the first thing that screamed out at me when I read the chart. Is Winslow at the top (or is it bottom?) merely because he has twice as many targets as every other player? Or does he get half as many targets, and he just stinks that badly?

  4. James says:

    Rate would be good, but with some necessary caveats. Probably should limit it to only receivers with 2 or more interceptions or X number of targets.

  5. DSMok1 says:

    Player Team Ints Targets INT%
    17-A.Collie IND 3 26 11.5%
    17-D.Moore OAK 6 54 11.1%
    82-K.Winslow TB 7 70 10.0%
    12-J.Ford OAK 3 30 10.0%
    84-B.Lloyd DEN 3 33 9.1%
    12-A.Roberts ARI 4 45 8.9%
    83-V.Jackson SD 6 71 8.5%
    82-B.Hartline MIA 3 36 8.3%
    83-F.Davis WAS 5 64 7.8%
    87-A.Caldwell CIN 4 53 7.5%
    89-S.Smith CAR 6 81 7.4%
    87-B.Celek PHI 4 55 7.3%
    86-D.Nelson BUF 4 55 7.3%
    13-St.Johnson BUF 5 71 7.0%
    10-D.Jackson PHI 4 58 6.9%
    80-M.Thomas JAX 4 59 6.8%
    85-A.Gates SD 3 45 6.7%
    19-D.Jones BUF 3 45 6.7%
    82-M.Manningham NYG 4 62 6.5%
    87-R.Wayne IND 5 83 6.0%
    88-T.Gonzalez ATL 4 68 5.9%
    84-R.White ATL 5 85 5.9%
    87-E.Decker DEN 4 69 5.8%
    88-D.Bryant DAL 3 53 5.7%
    10-J.Gaffney WAS 3 59 5.1%
    18-A.Green CIN 3 67 4.5%
    84-E.Dickson BAL 3 68 4.4%
    87-R.Gronkowski NE 3 73 4.1%
    82-D.Bowe KC 3 80 3.8%
    11-L.Fitzgerald ARI 3 83 3.6%
    19-B.Marshall MIA 3 87 3.4%
    81-C.Johnson DET 3 93 3.2%
    80-J.Graham NO 3 94 3.2%

  6. Anonymous says:

    And then make it a rate relative to QB's overall INT rate. Then make a generic adjustment for position (RB,TE,WR). Aggregate over several season, and you *may* have something that is slightly predictive, though I have my doubts.

  7. Will says:

    The regression suggested above could take care of all of that. Run it on the rate stat. A quick monte-carlo could provide reliability estimates.

    Don't waste your time watching the film. Assigning "fault" is nearly impossible. Is a pass off the fingertips the receiver's fault or the QB's? The regression would pull out what can be pulled out. I'm guessing R^2 will be low.

  8. Anonymous says:

    Naanee is incorrectly listed as a Charger.

  9. Bill says:

    This seems like a figure that'd need a huge sample to be worth while. Like 4-5 seasons, minimum, because INTs are infrequent and are probably more often a QB/defense responsibility. And, as anon suggested, adjusted for QB and position.

  10. Brian Burke says:

    Naanee fixed. Thanks.

    Yes. Very random!

    Thanks, DSMok1.

  11. Richard says:

    I've said for years that some INTs should be viewed like errors in baseball. You know, earned interceptions vs. unearned. Someone makes the call, and the unearneds don't count against the QB's stats. And potentially they could count against the receiver (fielder) as an error.

  12. Mavyrk says:

    Will Heller? Stafford's been picked off IIRC at least two times, and with him being a third string TE that's probably a ridiculous int/target ratio. Any chance you've got those numbers?

  13. lemmy caution says:

    This Sunday the 49ers double teamed Larry Fitzgerald all day leading to some ridiculous interceptions in Larry Fitzgerald's general direction.

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