You’re going to want to sit down for this one: Antonio Brown and Julio Jones were the two best receivers in the NFL last year.
Houston star DeAndre Hopkins was responsible for 37.8% of all Texans receiving yards last season, the highest rate in the league in 2017 (Hopkins also did this as a rookie in 2014). But Brown and Jones weren’t too far behind him: Brown had 34.8% of all Steelers receiving yards despite missing nearly three full games. And Jones had 33.8% of all Falcons receiving yards, the third highest ratio in the NFL. But Hopkins played on a mediocre Texans passing attack that ranked 20th in ANY/A (more precisely, he spent 40% of his time on a great passing attack led by Deshaun Watson, and 60% of his time on a terrible pass offense with Tom Savage and T.J. Yates under center). Jones and Brown played on passing offenses that averaged 7.0 ANY/A, ranking 7th and 8th in the NFL in 2017.
One of my favorite things to do at Football Perspective is to look at receiving production in the context of two stats: percentage of team yards and team passing efficiency (highlighted here when looking at Gary Clark’s production on the ’91 Skins). Why do I like looking at this? In some ways, these are counter forces. Put a great wide receiver on a good passing attack and he might not have a huge share of the offense, but the passing attack should be outstanding. Put him on a bad passing attack, and the pass efficiency may not be great, but he should have a huge share of the pie. It is hardly perfect, but it’s fun to look at.
So how do we quantify this? Let’s use Keenan Allen as an example for the table below. He had 30.6% of all Chargers receiving yards last season and Los Angeles averaged an impressive 7.48 ANY/A. He ranked 6th in percentage of Team Receiving Yards, and the Chargers ranked 3rd in ANY/A. Allen was 1.03 standard deviations above average in percentage of team receiving yards – the % of TRY Z-Score — and the Chargers were 1.47 standard deviations above average in ANY/A (the ANY/A Z-Score). If you add those two numbers together, Allen was 2.50 standard deviations above average, the metric by which the table below is sorted.
| Player | Team | % of TRY | ANY/A | % of TRY Rk | ANY/A Rk | % of TRY Z | ANY/A Z | Total |
|---|---|---|---|---|---|---|---|---|
| Julio Jones | ATL | 34.8% | 6.99 | 2 | 7 | 1.87 | 1.01 | 2.87 |
| Antonio Brown | PIT | 33.8% | 6.98 | 3 | 8 | 1.67 | 1.00 | 2.66 |
| Keenan Allen | LAC | 30.6% | 7.48 | 6 | 3 | 1.03 | 1.47 | 2.50 |
| Adam Thielen | MIN | 32.5% | 7.03 | 4 | 6 | 1.40 | 1.04 | 2.45 |
| Michael Thomas | NOR | 28.7% | 7.71 | 9 | 1 | 0.66 | 1.69 | 2.35 |
| DeAndre Hopkins | HOU | 37.8% | 5.31 | 1 | 20 | 2.46 | -0.56 | 1.89 |
| Tyreek Hill | KAN | 27.3% | 7.35 | 10 | 5 | 0.39 | 1.35 | 1.73 |
| Rob Gronkowski | NWE | 23.5% | 7.55 | 20 | 2 | -0.38 | 1.54 | 1.15 |
| A.J. Green | CIN | 31.8% | 5.60 | 5 | 17 | 1.27 | -0.29 | 0.99 |
| Marvin Jones | DET | 24.6% | 6.92 | 18 | 9 | -0.15 | 0.94 | 0.79 |
| Cooper Kupp | LAR | 21.6% | 7.47 | 24 | 4 | -0.75 | 1.45 | 0.70 |
| Doug Baldwin | SEA | 24.9% | 6.35 | 17 | 13 | -0.10 | 0.41 | 0.31 |
| T.Y. Hilton | IND | 29.9% | 5.06 | 7 | 25 | 0.90 | -0.80 | 0.10 |
| Zach Ertz | PHI | 20.8% | 6.82 | 25 | 10 | -0.92 | 0.85 | -0.06 |
| Mike Evans | TAM | 21.7% | 6.60 | 23 | 11 | -0.73 | 0.64 | -0.08 |
| Larry Fitzgerald | ARI | 29.1% | 5.00 | 8 | 26 | 0.72 | -0.85 | -0.13 |
| Robby Anderson | NYJ | 26.9% | 5.43 | 11 | 19 | 0.29 | -0.45 | -0.16 |
| Dez Bryant | DAL | 25.2% | 5.71 | 15 | 16 | -0.04 | -0.19 | -0.23 |
| Devin Funchess | CAR | 25.3% | 5.22 | 14 | 21 | -0.02 | -0.65 | -0.67 |
| Keelan Cole | JAX | 20.1% | 6.22 | 26 | 14 | -1.04 | 0.29 | -0.75 |
| Jamison Crowder | WAS | 19.3% | 6.38 | 30 | 12 | -1.21 | 0.44 | -0.77 |
| Jarvis Landry | MIA | 26.0% | 4.83 | 12 | 28 | 0.13 | -1.01 | -0.88 |
| Marquise Goodwin | SFO | 22.7% | 5.46 | 22 | 18 | -0.53 | -0.42 | -0.95 |
| Delanie Walker | TEN | 23.8% | 5.10 | 19 | 23 | -0.32 | -0.76 | -1.08 |
| Davante Adams | GNB | 25.1% | 4.66 | 16 | 30 | -0.07 | -1.17 | -1.24 |
| Demaryius Thomas | DEN | 25.9% | 4.41 | 13 | 31 | 0.09 | -1.41 | -1.31 |
| Jared Cook | OAK | 18.3% | 5.95 | 31 | 15 | -1.41 | 0.03 | -1.37 |
| Mike Wallace | BAL | 23.1% | 4.79 | 21 | 29 | -0.45 | -1.05 | -1.50 |
| Sterling Shepard | NYG | 19.9% | 5.06 | 28 | 24 | -1.09 | -0.80 | -1.89 |
| Kendall Wright | CHI | 19.9% | 4.94 | 27 | 27 | -1.09 | -0.91 | -1.99 |
| Charles Clay | BUF | 18.1% | 5.15 | 32 | 22 | -1.45 | -0.71 | -2.16 |
| Duke Johnson | CLE | 19.6% | 3.63 | 29 | 32 | -1.15 | -2.13 | -3.28 |
So does this analysis work? Look at Duke Johnson, who ranked just 29th in percentage of team receiving yards while playing on the 32nd-ranked passing offense. He grades as a terrible leading receiver in this analysis, which is… correct, since he’s a running back! The next-worst leading receiver is a tight end, while the worst wide receiver was Kendall Wright, who is done in Chicago after just one year. In other words, this analysis seems to do well at a broad level: a good receiver should either have a ton of his team’s pie or else be on a really good passing attack. T.Y. Hilton grades out as about average for a number one receiver here, because he overcame his team’s bad passing offense by getting a ton of targets.
What do you think?