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Is year 4 the magic season for Steelers receivers?

Looking at the top receivers in Steelers history, how did they perform in their fourth season?

Baltimore Ravens v Pittsburgh Steelers Photo by Justin K. Aller/Getty Images

In the most recent episode of the Steelers Stat Geek podcast, I was tasked with trying to verify the idea that wide receivers have their best season in year four with the Pittsburgh Steelers. With Deonte Johnson entering his fourth season in 2022, the idea behind the question was if it would be more cost effective to sign Johnson to a deal prior to year four, if the Steelers are interested in signing Johnson to a deal at all, as the price could go up after another season.

To look at the history, I decided to break down the first four seasons of each of the wide receivers on top of the Steelers all-time receiving yards list. In doing so, I looked at receptions, yards, and touchdowns. Of course, some years were lower for players simply because of the number of games in which they appeared. While this is important, I ultimately went with overall totals rather than per game averages.

Here is the information for each of the 10 wide receivers on the Steelers top 10 receiving list since the NFL merger in 1970. Note this list of only wide receivers and do not include tight ends or running backs. The year in which they have the most in a given category will be in bold. It should also be noted that the reason these players are the ones to which compared Diontae Johnson is because he currently sits 13th on the list with 2,764 yards.

*Pro Bowl selection

Hines Ward

Year 1 (1998): 16 games; 15 receptions; 246 yards; 0 touchdowns
Year 2 (1999): 16 games; 61 receptions; 638 yards; 7 touchdowns
Year 3 (2000): 16 games; 48 receptions; 672 yards; 4 touchdowns
Year 4 (2001*): 16 games; 94 receptions; 1,003 yards; 4 touchdowns

Antonio Brown

Year 1 (2010): 9 games; 16 receptions; 167 yards; 0 touchdowns
Year 2 (2011*): 16 games; 69 receptions; 1,108 yards; 2 touchdowns
Year 3 (2012): 13 games; 66 receptions; 787 yards; 5 touchdowns
Year 4 (2013*): 16 games; 110 receptions; 1,499 yards; 8 touchdowns

John Stallworth

Year 1 (1974): 13 games; 16 receptions; 269 yards; 1 touchdowns
Year 2 (1975): 11 games; 20 receptions; 423 yards; 4 touchdowns
Year 3 (1976): 8 games; 9 receptions; 111 yards; 2 touchdowns
Year 4 (1977): 14 games; 44 receptions; 784 yards; 7 touchdowns

Louis Lipps

Year 1 (1984*): 14 games; 45 receptions; 860 yards; 9 touchdowns
Year 2 (1985*): 16 games; 59 receptions; 1,134 yards; 12 touchdowns
Year 3 (1986): 13 games; 38 receptions; 590 yards; 3 touchdowns
Year 4 (1887): 4 games; 11 receptions; 164 yards; 0 touchdowns

Lynn Swann

Year 1 (1974): 12 games; 11 receptions; 208 yards; 2 touchdowns
Year 2 (1975*): 14 games; 49 receptions; 781 yards; 11 touchdowns
Year 3 (1976): 12 games; 28 receptions; 516 yards; 3 touchdowns
Year 4 (1977*): 14 games; 50 receptions; 789 yards; 7 touchdowns

Plaxico Burress

Year 1 (2000): 12 games; 22 receptions; 273 yards; 0 touchdowns
Year 2 (2001): 16 games; 66 receptions; 1,008 yards; 6 touchdowns
Year 3 (2002): 16 games; 78 receptions; 1,325 yards; 7 touchdowns
Year 4 (2003): 16 games; 60 receptions; 860 yards; 4 touchdowns

Mike Wallace

Year 1 (2009): 16 games; 39 receptions; 756 yards; 6 touchdowns
Year 2 (2010): 16 games; 60 receptions; 1,257 yards; 10 touchdowns
Year 3 (2011*): 16 games; 72 receptions; 1,193 yards; 8 touchdowns
Year 4 (2012): 15 games; 64 receptions; 836 yards; 8 touchdowns

JuJu Smith-Schuster

Year 1 (2017): 14 games; 58 receptions; 917 yards; 7 touchdowns
Year 2 (2018): 16 games; 111 receptions; 1,426 yards; 7 touchdowns
Year 3 (2019): 12 games; 42 receptions; 552 yards; 3 touchdowns
Year 4 (2020): 16 games; 97 receptions; 831 yards; 9 touchdowns

Santonio Holmes

Year 1 (2006): 16 games; 49 receptions; 824 yards; 2 touchdowns
Year 2 (2007): 13 games; 52 receptions; 942 yards; 8 touchdowns
Year 3 (2008): 15 games; 55 receptions; 821 yards; 5 touchdowns
Year 4 (2009): 16 games; 79 receptions; 1,248 yards; 5 touchdowns

Yancy Thigpen+

Year 1 (1992): 12 games; 1 reception; 2 yards; 0 touchdowns
Year 2 (1993): 12 games; 9 receptions; 154 yards; 3 touchdowns
Year 3 (1994): 15 games; 36 receptions; 546 yards; 4 touchdowns
Year 4 (1995*): 16 games; 85 receptions; 1,307 yards; 5 touchdowns

+Appeared in four games in 1991 with the San Diego Chargers but was not even targeted

I debated how analyze Yancy Thigpen since he was the only member on his list who did not start his career with the Pittsburgh Steelers. But once I saw he was not even targeted in his one year in San Diego, I simply stuck to the list being with “a players first four years with the Steelers.”

In looking at this list, there are some interesting conclusions which can be drawn from the data. Seven out of the 10 players on the list saw their highest output of their first four seasons in at least one of these three categories. One player, JuJu Smith-Schuster, saw his highest total in year four in one category while three players had highs in two categories and three others reaching the peak of their first four seasons in all three categories.

To use these numbers as a projection, it would mean Diontae Johnson has a 70% chance of bettering one of these three categories in 2022. With career highs and all three categories (107 receptions, 1161 yards, 8 touchdowns) last season, it would be fantastic for the Pittsburgh Steelers to see Johnson put up bigger numbers in even one of the stats. Based on these numbers, Johnson would also have a 60% chance of bettering two of these three categories.

Of course, looking at these numbers as a prediction is quite difficult. There are a number of variables which could influence Johnson’s statistical output for 2022 such as health, quarterback play, offensive philosophy, and other supporting cast. But when simply looking to see if Steelers receivers have a tendency to have their best year in their fourth season with the team, for the very best of the franchise has had over the last 50 years, the answer would be “most of the time.”

The complete episode of the Steelers Stat Geek podcast where this topic was discussed can be found here: