Analytics show Cleveland Browns passing game needs an overhaul

Cleveland Browns tight end Harrison Bryant (88) catches a pass in the fourth quarter during a Week 9 NFL football game against the Cincinnati Bengals, Sunday, Nov. 7, 2021, at Paul Brown Stadium in Cincinnati. The Cleveland Browns won, 41-16.Cleveland Browns At Cincinnati Bengals Nov 7
Cleveland Browns tight end Harrison Bryant (88) catches a pass in the fourth quarter during a Week 9 NFL football game against the Cincinnati Bengals, Sunday, Nov. 7, 2021, at Paul Brown Stadium in Cincinnati. The Cleveland Browns won, 41-16.Cleveland Browns At Cincinnati Bengals Nov 7 /
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Dec 12, 2021; Cleveland, Ohio, USA; Cleveland Browns wide receiver Donovan Peoples-Jones (11) makes a reception under coverage by Baltimore Ravens cornerback Chris Westry (30) during the second quarter at FirstEnergy Stadium. Mandatory Credit: Scott Galvin-USA TODAY Sports /

The Cleveland Browns passing game needs to be overhauled after having fallen into major dysfunction last season. 

The Cleveland Browns had a dysfunctional passing attack last season and the numbers help quantify the frustration. By “dysfunctional,” it’s meant that other priorities displaced the goals of winning football games and the derived goals of scoring touchdowns, and moving the yardsticks by the best possible means.

Instead (at least in this author’s opinion), personalities took over, and 2021 was too much about trying to please egos. When those secondary goals took over, the result was extra losses and it made everyone less happy, not happier.

The overall assessment that the air attack was dysfunctional is just one person’s subjective opinion, which you can take or leave. However, the numbers show without a doubt that footballs were being thrown too often to wide receivers who were not the most productive targets.

Obviously, anyone can look at a stat sheet and see which receivers are making the most catches and getting the most yards. To delve deeper, however, what about a receiver who is not accumulating huge yardage totals, but is making “impact plays” that win games, namely touchdowns and first downs?

That’s a stat that can be measured, and in fact, all the necessary data is available from Pro Football Reference. A new stat can be created, called “Impact Play Percentage” (IPP) given by (first downs + TDs)/(total targets). That tells us how often an impact play resulted when a receiver was targeted.

Players who are scoring low in this category are either not making the catch or are just getting three yards and a cloud of dust; i.e., empty yards. Of course, the defensive matchup influences this stat also.

If they are double-teaming your best player, your adjusted game plan might very well favor targeting the second or third receiver. Nevertheless, while game-to-game results are going to vary widely, over the long haul, a pattern will emerge and the best receivers should be getting the most targets and should put up the best numbers.

The hypothesis is that a well-run team would seek to maximize targets to players who make first downs and touchdowns when they are on the field. Conversely, there’s not much reason to keep feeding players who are not delivering success. Measuring the stat on a per-snap basis, accounts for injuries or situational players. If they are on the field, they should be targeted if they are able to move the chains or score.

That is, if the coach, offensive coordinator, and quarterback are on the same page, their strategy ought to be to put the ball in the hands of the players who are most likely to kick butt and make impact plays, right?

Your three yards and a cloud of dust guy should not be getting too many targets per snap. This is not Pop Warner ball, where each player gets an equal chance to make plays regardless of skill level.

Accordingly, the graph and table below show each Browns receiver ranked in order of IPP. The hypothesis is that a highly productive receiver should motivate the smart play caller, play designer, and quarterback to succeed by targeting the most successful players. Hence the second column shows the total targets divided by total snaps for each player, expressed as a percentage, Targets Per Snap or TSP.

Also included are the Browns stats for Odell Beckham, Jr., as well as the stats from newcomers Amari Cooper and Jakeem Grant even though they were accumulated from different teams.

The arrow (up or down) reflects the author’s editorial comment that the receiver should have had more (or fewer) TPS based on their IPP. The next page discusses the Browns wide receivers

The hypothesis is that an NFL team should try to feed its top performers and target them more often than the underperforming players, at least when they are able to make it on the field. Maybe due to injuries or depending on the situation, not every player is on the field for every down, but the NFL team should reward success.

In Pop Warner ball, every receiver gets a shot, and maybe the best friend of the quarterback gets special treatment. Friendships sometimes matter over ability.

Now, which model did the Browns more closely resemble? You may make your own judgment by studying the table below, but some observations are shared on wide receivers on the next page and tight ends on the third page of this article. The discussion is not particularly flattering to the Browns coaching staff or quarterback.

Player                             IPP                      TPS              Comment

Harrison Bryant           60.7%                 7.0%            Least used of 3 tight ends.⇑

Demetric Felton           57.1%              16.2%            Rarely used slot receiver & RB

Jakeem Grant                52.9%              11.5%            Miami + Bears

Amari Cooper                51.0%              12.5%            Dallas Cowboys

Ja’Marcus Bradley       50.0%                 5.1%            Does coach know his name?⇑

D. Peoples-Jones         50.0%                 8.3%             Mayfield wouldn’t use him first 4 games.⇑

Odell Beckham, LA      43.8%               12.8%            Impact plays justify high targeting

David Njoku                  39.6%                 7.9%             Best athlete among TE

Jarvis Landry                36.8%               16.3%             Way over-targeted, injury-plagued year.⇓

Rashard Higgins         36.2%                  9.2%             Down year, poor production, but Baker still used him.⇓

Austin Hooper             34.4%                  8.5%             Led Browns in snaps despite poor production⇓

Odell Beckham CLE   32.4%               11.7%              Underperformed; Baker targeted him heavily at first.⇓

Anthony Schwartz     30.4%                  7.8%             Rookie played like a rookie at times. ⇓