How to Project Receiving Yards In 2014

A method to come up with a starting point for your wide receiver projections in 2014

Last preseason, I evaluated the best way to come up with the starting point for your wide receiver projections.  While many start their projections by using last year's rankings, that's not the preferred approach.  That data is part noise, part signal; a receiver ability may be pretty constant from year-to-year, but other factors are much less reliable. If we can isolate the most relevant data, we'll be in a better position to predict what will happen in 2014.

The analysis looks at three variables:

  • The number of pass attempts by his team;
  • The percentage of his team's passes that go to him; and
  • The receiver's average gain on passes that go to him.


If you think about receiving yards in that context, a the number of yards a receiver will gain is equal to the following formula:

    Receiving yards = (Receiving Yards/Target) x (Targets/Team_Pass_Att)  x  Team_Pass_Att.

Last year, Josh Gordon's Browns led the NFL in pass attempts with 681 (although Gordon himself missed two games); Pierre Garcon led the league in targets at 182, but it was Vincent Jackson who was number one in percentage of team targets at 31.1%. Depending on your cut-offs, either Kenny Stills (on 50 targets) or DeSean Jackson (on 126 targets) finished first in yards per target. In theory, picking among Gordon and the two Jacksons in many ways involves deciding which variable is most likely to repeat itself in 2013. Of course, all three players have significant changes going into 2014: Gordon faces a possible year-long suspension, DeSean Jackson is now in Washington, and Vincent Jackson's Buccaneers spent the first two picks in the draft on wide receiver Mike Evans and tight end Austin Seferian-Jenkins.

Alternatively, regression to the mean principles could have you high on a receiver who had an unusually low number in one of these three metrics. The 49ers were last in pass attempts last year; an increase could be good news for Anquan Boldin or Michael Crabtree or Vernon Davis. The Rams' Chris Givens saw the fewest targets of any number one wide receiver to play in at least 14 games last year; that means there's opportunity for growth in St. Louis, either for Givens or perhaps Tavon Austin. And Cecil Shorts finished last among receivers in yards per target (minimum 700 receiving yards). Knowing which of those three statistics - pass attempts, percentage of the pie, and yards per target - is most likely to regress to the mean is very helpful when it comes to making fantasy projections.

Team Pass Attempts

How sticky are team pass attempts from year to year? Last year, I further broke "Pass Attempts" down into two variables: Offensive Plays and Pass Attempts per Offensive Play (excluding sacks from the numerator but including them in the denominator). We can use those two variables to predict future pass attempts. The best fit formula to predict team pass attempts based on historical data is:

Future Pass Attempts = 36 + (450 x Pass_Attempts/Play) + (0.255 x Offensive Plays)

What does that mean for 2013? I took last year's stats and applied that formula, which gives us a best-guess projection for 2014 in terms of number of pass attempts. Here's how to read the table: In 2013, the Browns ranked 1st in pass attempts, and threw a pass on 63.2% of all offensive plays. Cleveland ran 1,078 plays and threw 681 passes, but in 2014, the Browns are projected for "only" 595 passes, a decline of 86 attempts.

RkTeam2013 PA/P2013 Off Plays2013 Passes2014 Proj PassDifference
1 CLE 63.2 1078 681 595 -86
2 DEN 58.4 1156 675 594 -81
3 ATL 64.4 1024 659 587 -72
4 NOR 60.3 1079 651 583 -68
5 DET 57.5 1102 634 576 -58
6 HOU 58.1 1089 633 575 -58
7 NWE 55.2 1138 628 575 -53
8 BAL 56.8 1090 619 570 -49
9 WAS 55.2 1107 611 567 -44
10 MIA 59.3 1001 594 558 -36
11 JAX 58 1020 592 557 -35
12 CIN 53.5 1097 587 557 -30
13 DAL 61.2 957 586 556 -30
14 PIT 57.3 1023 586 555 -31
15 IND 56.9 1023 582 553 -29
16 CHI 57.2 1013 579 552 -27
17 ARI 55.4 1037 574 550 -24
18 GNB 53.1 1074 570 549 -21
19 NYG 57.4 988 567 546 -21
20 SDG 51.3 1060 544 537 -7
21 KAN 53.1 1029 546 537 -9
22 MIN 53.9 1013 546 537 -9
23 TEN 51.6 1032 533 532 -1
24 BUF 46.8 1116 522 531 9
25 OAK 51.9 1000 519 525 6
26 TAM 52.4 981 514 522 8
27 PHI 48.2 1054 508 522 14
28 STL 52.3 968 506 518 12
29 NYJ 47.1 1020 480 508 28
30 CAR 47.3 999 473 504 31
31 SEA 43.2 973 420 478 58
32 SFO 43.4 961 417 476 59

This formula doesn't change the order of things, but it shrinks the distribution. Teams like San Francisco and Seattle were very run-heavy in 2013; while that could happen again next year, some reversion to the mean should be expected. Similarly, Denver and Cleveland will probably come back to the pack, at least to some extent. While you might In 2012, the Lions threw 740 pass attempts; this formula projected Detroit to throw 619 passes in 2013, not too far off the 634 actually attempted by the team.

TARGETS PER TEAM PASS ATTEMPT

How "sticky" is the percent of targets each receiver sees from year to year? The best-fit formula for WRs who play in at least 14 games and see 100+ targets is:

    Future Percentage of Targets = 6.2% + 71.3% x Past Percentage of Targets

What does that mean? There is some regression to the mean, but not too much: for the most part, the piece of the pie that a receiver sees is pretty consistent from year to year. There were 28 wide receivers who played in at least 14 games and saw 100+ targets in 2013, and are back with the same team in 2014. The table below shows the percentage of team targets this formula would tell us to project for those players for 2013:

RankReceiverTeam2013 Targets2013 Team Pass Att2013 Tar/TPA2014 ProjectionDiff
1 Vincent Jackson TAM 160 514 31.1 28.4 -2.7
2 Anquan Boldin SFO 129 417 30.9 28.2 -2.7
3 A.J. Green CIN 178 587 30.3 27.8 -2.5
4 Pierre Garcon WAS 182 611 29.8 27.4 -2.4
5 Andre Johnson HOU 181 633 28.6 26.6 -2
6 Antonio Brown PIT 166 586 28.3 26.4 -1.9
7 Brandon Marshall CHI 164 579 28.3 26.4 -1.9
8 Dez Bryant DAL 159 586 27.1 25.5 -1.6
9 Kendall Wright TEN 139 533 26.1 24.8 -1.3
10 Alshon Jeffery CHI 149 579 25.7 24.5 -1.2
11 Calvin Johnson DET 156 634 24.6 23.7 -0.9
12 Julian Edelman NWE 151 628 24 23.3 -0.7
13 T.Y. Hilton IND 139 582 23.9 23.2 -0.7
14 Mike Wallace MIA 141 594 23.7 23.1 -0.6
15 Larry Fitzgerald ARI 135 574 23.5 23 -0.5
16 Josh Gordon CLE 159 681 23.3 22.8 -0.5
17 Brian Hartline MIA 134 594 22.6 22.3 -0.3
18 Jordy Nelson GNB 127 570 22.3 22.1 -0.2
19 Torrey Smith BAL 137 619 22.1 22 -0.1
20 Victor Cruz NYG 122 567 21.5 21.5 0
21 Demaryius Thomas DEN 142 675 21 21.2 0.2
22 Harry Douglas ATL 132 659 20 20.5 0.5
23 Nate Washington TEN 105 533 19.7 20.2 0.5
24 Michael Floyd ARI 113 574 19.7 20.2 0.5
25 Greg Jennings MIN 106 546 19.4 20 0.6
26 Keenan Allen SDG 104 544 19.1 19.8 0.7
27 Dwayne Bowe KAN 103 546 18.9 19.7 0.8
28 Marques Colston NOR 111 651 17.1 18.4 1.3

As you can see, we shouldn't project too much variation from last year's target ratios absent other information. Of course, for Jackson, there is quite a bit of new information, and Evans and Seferian-Jenkins should eat into his targets in 2014 (of course, this might be offset by any efficiency Jackson gains on a per-target basis). I'll also note that while Keenan Allen is at the bottom of this list, I might make an exception for him. Sure, as a rookie, he wasn't commanding a lot of targets. But based on his per-target efficiency last season, it's fair to predict that he'll be seeing more footballs in 2014; of course, this might be offset decrease in efficiency Allen has on a per-target basis. That brings us to our next category.

Yards per TARGET

Compared to percentage of team targets, yards per target isn't a very "sticky" metric. This makes sense. Targets are a good thing and are indicators of talent and ability. Punishing a player for a "failed" target doesn't make a lot of sense, and it doesn't help you predict the future. By putting targets in the denominator, you're implying that a target that yields no yards is a bad thing, but in fact, the opposite is often the case. On a given incomplete pass, the targeted receiver may have done the best job of the players on the field, and that makes him more likely to see targets in the future.

The best-fit formula to project future Yards/Target from past Yards/Target:

    Future Yards/Target = 5.5 + 0.29 x Past Yards/Targets

This formula tells us that receivers retain only 29% of their Yards/Target value, whether positive or negative. For each receiver, we're better off taking a league baseline number -- here, 5.5 -- and then adding 29% of the actual Yards/Target from the receiver last year. Here's what this means for our 28 receivers in 2014:

RankReceiverTeam2013 Yards2013 Targets2013 Yards/Target2014 ProjectionDiff
1 Josh Gordon CLE 1646 159 10.4 8.5 -1.9
2 Jordy Nelson GNB 1314 127 10.3 8.5 -1.8
3 Demaryius Thomas DEN 1430 142 10.1 8.4 -1.7
4 Keenan Allen SDG 1046 104 10.1 8.4 -1.7
5 Calvin Johnson DET 1492 156 9.6 8.3 -1.3
6 Alshon Jeffery CHI 1421 149 9.5 8.3 -1.2
7 Michael Floyd ARI 1041 113 9.2 8.2 -1
8 Anquan Boldin SFO 1179 129 9.1 8.1 -1
9 Antonio Brown PIT 1499 166 9 8.1 -0.9
10 Nate Washington TEN 919 105 8.8 8.1 -0.7
11 Marques Colston NOR 943 111 8.5 8 -0.5
12 Torrey Smith BAL 1128 137 8.2 7.9 -0.3
13 Victor Cruz NYG 998 122 8.2 7.9 -0.3
14 Harry Douglas ATL 1067 132 8.1 7.8 -0.3
15 A.J. Green CIN 1426 178 8 7.8 -0.2
16 Brandon Marshall CHI 1295 164 7.9 7.8 -0.1
17 Andre Johnson HOU 1407 181 7.8 7.8 0
18 Dez Bryant DAL 1233 159 7.8 7.8 0
19 Kendall Wright TEN 1079 139 7.8 7.8 0
20 T.Y. Hilton IND 1083 139 7.8 7.8 0
21 Vincent Jackson TAM 1224 160 7.7 7.7 0
22 Brian Hartline MIA 1016 134 7.6 7.7 0.1
23 Greg Jennings MIN 804 106 7.6 7.7 0.1
24 Pierre Garcon WAS 1346 182 7.4 7.6 0.2
25 Larry Fitzgerald ARI 954 135 7.1 7.6 0.5
26 Julian Edelman NWE 1056 151 7 7.5 0.5
27 Mike Wallace MIA 930 141 6.6 7.4 0.8
28 Dwayne Bowe KAN 673 103 6.5 7.4 0.9

Again, the significant amount of regression to the mean is clear with this metric. That would normally mean bad things for say, Demaryius Thomas, but I'll note that he actually ranked #1 in this statistic in 2012 at 10.2. Of course, having Peyton Manning helps out quite a bit. More interesting might be to look at one of the players at the bottom of the list: Mike Wallace was a disappointment in year 1, but that was more due to his efficiency than his percentage of team targets. With an improved offensive line, perhaps he and Ryan Tannehill will be able to connect on a few more bombs in 2014.

CONCLUSION

Now, what if we put it all together? Remember, we can define Receiving Yards as Team Pass Attempts multiplied by (Targets/Team Pass Attempt) multiplied by (Receiving Yards/Target). Since we now have projections for each of these 28 receivers in each of these three categories, we can come up with a baseline projection of 2013 receiving yards.

RankReceiverTeam2013 Yards2014 Team Pass2014 Targ/TPA2014 Yards/Target2014 Rec YdsDiff
1 A.J. Green CIN 1426 557 27.8 7.8 1208 -218
2 Andre Johnson HOU 1407 575 26.6 7.8 1193 -214
3 Antonio Brown PIT 1499 555 26.4 8.1 1187 -312
4 Pierre Garcon WAS 1346 567 27.4 7.6 1181 -165
5 Josh Gordon CLE 1646 595 22.8 8.5 1153 -493
6 Vincent Jackson TAM 1224 522 28.4 7.7 1142 -82
7 Brandon Marshall CHI 1295 552 26.4 7.8 1137 -158
8 Calvin Johnson DET 1492 576 23.7 8.3 1133 -359
9 Alshon Jeffery CHI 1421 552 24.5 8.3 1122 -299
10 Dez Bryant DAL 1233 556 25.5 7.8 1106 -127
11 Anquan Boldin SFO 1179 476 28.2 8.1 1087 -92
12 Demaryius Thomas DEN 1430 594 21.2 8.4 1058 -372
13 Jordy Nelson GNB 1314 549 22.1 8.5 1031 -283
14 Kendall Wright TEN 1079 532 24.8 7.8 1029 -50
15 Julian Edelman NWE 1056 575 23.3 7.5 1005 -51
16 T.Y. Hilton IND 1083 553 23.2 7.8 1001 -82
17 Torrey Smith BAL 1128 570 22 7.9 991 -137
18 Larry Fitzgerald ARI 954 550 23 7.6 961 7
19 Brian Hartline MIA 1016 558 22.3 7.7 958 -58
20 Mike Wallace MIA 930 558 23.1 7.4 954 24
21 Harry Douglas ATL 1067 587 20.5 7.8 939 -128
22 Victor Cruz NYG 998 546 21.5 7.9 927 -71
23 Michael Floyd ARI 1041 550 20.2 8.2 911 -130
24 Keenan Allen SDG 1046 537 19.8 8.4 893 -153
25 Nate Washington TEN 919 532 20.2 8.1 870 -49
26 Marques Colston NOR 943 583 18.4 8 858 -85
27 Greg Jennings MIN 804 537 20 7.7 827 23
28 Dwayne Bowe KAN 673 537 19.7 7.4 783 110

So what can we learn from this list?

  • Antonio Brown finished with a few more receiving yards than A.J. Green or Andre Johnson, but this analysis is less bullish on Brown for 2014. Why's that? Because Brown's great 2013 season was fueled by an excellent 9.0 yards per target ratio. Both Green and Johnson have strong 2014 projections because both players finished 2013 in the top five in percentage of team targets.
  • Josh Gordon drops like a rock in this analysis, largely because of the expected decline in pass attempts for Cleveland last year. On the other hand, this regression doesn't know that Gordon missed two games in 2013; on the, uh, third hand, the regression doesn't know that Gordon could play in 0 games in 2014.
  • Pierre Garcon led the NFL in targets last year; as a result, he's projected to finish 4th in receiving yards. Obviously the DeSean Jackson acquisition will impact Garcon's fantasy value, probably in a negative way. But while Garcon will catch fewer passes in 2014, he should probably catch more than five touchdowns this season.
  • Most of the top receivers suffer from some regression to the mean, but Demaryius Thomas and Calvin Johnson get hit harder than most. That's because they played on very pass-happy teams last season and had great yards per target numbers. To the extent you think they can both do that again -- and that's a pretty reasonable assumption -- then I wouldn't be too worried about their relatively low projections here. But it is worth remembering that neither player finished in the top 10 in percentage of team targets, and that's the most sticky of the three stats we're looking at here.
  • Keenan Allen does not fare well in this analysis, as predicted. The big question for Allen is whether he can see his target percentage jump from 20% to the high twenties. A 10.1 Y/T average is simply not sustainable, so he needs to get more looks from Philip Rivers in 2014. The guess here is that he does just that.
  • Jordy Nelson is on the buyer beware list. While he topped 1300 receiving yards in 2013, he only saw about 22% of all Packers targets last year. And that's with Randall Cobb missing most of the year with an injury. The departure of James Jones will help (although Green Bay drafted Fresno State's Davante Adams in the second round), but Nelson's monster season was the result of an absurd 10.3 yards per target average last season.

More articles from Chase Stuart

See all

More articles on: Stats

See all

More articles on: Strategy

See all

More articles on: WR

See all