Analytics show Cleveland Browns passing game needs an overhaul

More on Impact Play Percentage (IPP)

Because Impact Play Percentage (IPP) is a totally new stat, stat geeks everywhere will want to develop a feel for what it implies about star players. The table below lists the top 20 receivers ranked in terms of receptions in 2021, according to Pro Football Reference.

Snaps is the total number of offensive players the player was on the field for, not including special teams or defense. IPP is equal to first downs plus touchdowns divided by total targets, expressed as a percentage.

In other words, if the quarterback throws the ball at the receiver, what is the average probability something meaningful is going to happen? Targets Per Snap (TPS) tells how frequently an attempted pass came the player’s way, also expressed as a percentage. Targets, Receptions, Catch Percentage, and Yards are imported directly from PFR. The symbol “*” denotes the player went to the 2021 Pro Bowl, and “+” means he was selected All-Pro.

The working hypothesis is that players with high IPP also tend to get high TPS. For the most part, this is true (except for your screwed-up Browns).

Among the top 20 NFL receivers, there were nine receivers who were targeted more frequently than Jarvis Landry when they were on the field. There were three receivers who scored lower than Landry in terms of IPP. None were lower in IPP and higher in TPS.

Low scores for IPP were turned in by Marquise Brown (32.2%), but he was not the primary target for Baltimore. Mark Andrews was, and his IPP was an impressive 54.9%. Anyway, GM Eric DeCosta of the Ravens was so impressed by Brown that he traded him this offseason. Perhaps Brown should not be cited as a counter-example of an excellent receiver with a low IPP.

Likewise, Cole Beasley turned in a 31.1% IPP, but he was on the same team as Stefon Diggs (46.3%), and Dawson Knox (56.3%), as shown in the second table below.

Jacobi Meyers had an IPP of 31.3%, but the second lowest TPS among the group at 13.5%. Moreover, he was on the same team as Kendrick Bourne (58.2%, 12.2%) and Hunter Henry (57.3%, 10.0% ). Meyers had only 66 more yards than Bourne on the year.

Rec Player               Team       Pos  Snaps      IPP      TPS    Tgt   Rec      Catch Yards
Rnk                                                                                                               pct

1    Cooper Kupp*+           LAR   WR  1024  55.0% 18.7%   191  145  75.9%  1947
2    Davante Adams*+     GNB  WR    886  56.2%  19.1%  169   123  72.8%  1553
3    Tyreek Hill*                 KAN   WR    867  52.8%  18.3%  159   111  69.8%  1239
4    Justin Jefferson*        MIN   WR 1014  50.9%  16.5%  167   108  64.7%  1616
5    Mark Andrews*+       BAL    TE     936   54.9% 16.3%  153  107  69.9%  1361
6    Diontae Johnson*      PIT     WR   988   39.6%  17.1%  169  107  63.3%  1161
7    Keenan Allen*            LAC     WR   972   45.9%  16.2%  157  106  67.5% 1138
8    Jaylen Waddle            MIA    WR   903   46.4%  15.5%  140  104 74.3%  1015
9    Stefon Diggs*             BUF    WR  977   46.3%  16.8%  164  103  62.8%  1225
10 Hunter Renfrow*       LVR     WR 758   46.9%  16.9%   128  103  80.5% 1038
11 Chris Godwin              TAM    WR  833   47.2%  15.2%  127    98  77.2%  1103
12 D.J. Moore                    CAR    WR  992   39.3%  16.4%  163    93  57.1%  1157
13 Travis Kelce*               KAN    TE    926   53.7%  14.5%  134    92  68.7%  1125
14 Marquise Brown        BAL    WR  924   32.2%   15.8% 146    91  62.3%  1008
15 Brandin Cooks            HOU   WR  831   38.1%  16.1%  134    90  67.2%  1037
16 Amon-Ra St. Brown DET    WR   816   44.5%  14.6%  119    90  75.6%    912
17 Michael Pittman Jr.   IND    WR   979   46.5%  13.2%  129    88  68.2%  1082
18 Jakobi Meyers             NWE WR   931   34.9%  13.5%  126    83  65.9%    866
19 Cole Beasley                BUF  WR   691   31.3%  16.2%  112    82  73.2%    693
20 Ja’Marr Chase*            CIN   WR   939   53.9%  13.6%  128    81   63.3% 1455

Diontae Johnson (Pittsburgh) D.J. Moore (Carolina), Brandin Cooks (Houston) all turned in IPP higher than Landry’s but under 40. Not surprising, all three teams had sputtering pass offenses with mediocre quarterback play.

Browns division rival Diontae Johnson deserves special comment. With Big Ben Roethlisberger in his last season and not very mobile behind a weak offensive line, the Steelers ran a lot of plays from the spread formation with Ben chucking very short passes under three seconds.

Hence we can understand why that offense produced a high completion percentage but not enough passes that moved the chains. Hence if Johnson’s IPP is a bit lower than expected, there is an explanation.

Similarly, D.J. Moore played for Carolina. Quarterback Sam Darnold can sling it when he is healthy, but he injured his shoulder and had to be shut down. For 15 minutes, it seemed that the Panthers could bring in Cam Newton with zero familiarity with the personnel and zero familiarity with the playbook and have him become a superstar again, but that turned out not to be the case. No one should be surprised by that.

Brandin Cooks played for Houston, with Tyrod Taylor and Davis Mills sharing quarterback duties. Once again, I am prepared to forgive Cooks for a slightly depressed IPP, but still higher than Landry’s. Cooks was a 1,000-yard receiver despite the team’s problems.

To build some context around Jarvis Landry, who had the 68th most catches in the NFL last season, the second table below was constructed with six receivers just ahead of Landry and five below him. Running backs were not included because they are just not targeted with the same frequency as wide receivers or tight ends. Most of the players in the second table are not the number one receiver on their team, and many are the number three receiver.

The numbers show that Landry had the highest TPS among this group. Seven of the 11 other receivers had higher IPP. The numbers are consistent with the view that Landry was targeted as if he were a star number one receiver, but his production was more like a number three.

We can discuss why the Browns didn’t want to use the younger receivers who were getting better numbers. Blame the younger receivers for not getting open, the coaches for not wanting to disrupt the clubhouse, or just not realizing that the kids were better than the older receivers.

Rec Player               Team       Pos  Snaps  IPP      TPS      Tgt   Rec      Catch Yards
Rnk                                                                                                                     pct

60 Rob Gronkowski        TAM  TE     634   44.9%  14.0%    89    55   61.8%   802
61 Darren Waller             LVR   TE     608   35.5%  15.3%    93    55   59.1%   665
62 A.J. Green                     ARI    WR   888   43.5%  10.4%    92    54   58.7%   848
64 Rondale Moore          ARI    WR   432   29.7%  14.8%    64    54   84.4%   435
65 Robby Anderson       CAR   WR   978   29.1%  11.2%  110    53   48.2%   519
66 Tim Patrick                 DEN   WR   849   51.8%  10.0%    85    53   62.4%   734
68 Jarvis Landry              CLE    WR   533   36.8%  16.3%    87    52   59.8%   570
70 Jamison Crowder      NYJ    WR   538   36.6%  13.2%    71    51   71.8%   447
71 Hunter Henry            NWE  TE    750    57.3%  10.0%    75    50   66.7%   603
72 Van Jefferson            LAR    WR   875   42.7%  10.2%    89    50   56.2%   802
73 K.J. Osborn                 MIN   WR   774   40.2%  10.6%    82    50   61.0%   655
75 Dawson Knox            BUF   TE     917   56.3%    7.7%    71    49    69.0%   587

Or maybe the author’s numbers are wrong or misleading. Maybe the rest of the NFL is also wrong and Landry, Hooper and Higgins all deserve top ten contracts despite last season’s debacle.

Will this be their redemption year, and will the Browns look foolish for letting them go? If you wish to share your opinion, comment below!