After finding that if a player finished as a WR1 with under eight YPT that he was likely to decline in the following season, I wanted to research the opposite. How receivers performed after finishing a WR1 season with eight or more YPT. Would we see as large of a decrease in fantasy points in their following season? 

At first glance, the list is overwhelming as 151 players fit the criteria versus only 41 who were under eight YPT. Naturally, this makes sense as most WR1 seasons happen by players who have good seasons and are efficient.

The full list is posted below.

PLAYERSEASreYPTPPRreYPT.N+1PPR.N+1
Jordy Nelson201113.2284.310.2167.5
Mike Wallace201012.7249.610.6245
Torry Holt200011.8282.210.2259.3
Victor Cruz201111.7289.97.6255.2
Randy Moss200011.2313.28270.15
Santana Moss200511.12867.8180.2
Mike Evans201811286.49.8232.7
Steve Smith200811260.17.5206.6
Isaac Bruce200010.9289.210.7212.9
Julio Jones201610.9259.99.8251.9
Tyreek Hill201810.83289.8188.3
Steve Smith201110.82688.5217.1
DeSean Jackson201310.7269.412.3209.6
Calvin Johnson201110.6361.29.6348.4
Miles Austin200910.6278.88.7230.4
Mike Wallace201110.62457196.3
Reggie Wayne200410.5269.68.6218.5
Steve Smith200510.4340.68.3259.7
Doug Baldwin201510.4268.99253.75
T.Y. Hilton201410.3260.58.4211.4
Jordy Nelson201310.3264.410.1327.9
Torry Holt200110.2259.38.1247
Demaryius Thomas201310.13198.8340.9
Demaryius Thomas201210.129710.1319
Torry Holt200410.1291.28.2289.3
Randall Cobb201410.1297.46.4202.9
Greg Jennings201010.1274.49.4215.9
Emmanuel Sanders201410301.88.3228.4
Dez Bryant201210303.77.7294.4
Amani Toomer200210264.57199.2
Odell Beckham Jr.2014102979.2319.7
Brandin Cooks201610246.39.5221.2
DeSean Jackson200910251.311204.2
Julio Jones20189.9329.88.9274.1
Terrell Owens20009.9323.29.1332.3
Andre Johnson20129.8295.87.8279.7
Julio Jones20149.8299.49.2371.1
Julio Jones20179.8251.99.9329.8
Derrick Mason20039.8274.47.4254.5
Reggie Wayne20079.7315.48.7232.8
Derrick Alexander20009.7281.66.993.6
Calvin Johnson20129.6348.49.5305.2
DeAndre Hopkins20189.6337.57.8268.6
Michael Thomas20189.6321.59.3374.6
Terrell Owens20079.63077.5237.5
Reggie Wayne20069.62739.7315.4
Randy Moss20039.53848.9203.55
Antonio Brown20179.5310.37.7323.7
Calvin Johnson20139.5305.28.4226.7
Brandon Lloyd20109.52866.5196.6
Alshon Jeffery20139.5285.67.8261.6
Eric Decker20139.5281.88.4200.2
Antonio Brown20149.4385.19.5386.9
Roddy White20089.4268.87266.5
Vincent Jackson20129.4260.47.7242.4
Roddy White20129.4269.17.3152.1
Lee Evans20069.4259.27.5169.9
Laveranues Coles20029.4251.37.6242.3
Michael Thomas20169.4259.78.4258.5
Santana Moss20039.4251.210.7160.6
Torry Holt20039.3359.110.1291.2
Rod Smith20009.3324.17.8318
Marvin Harrison20019.3351.78.4384.2
Randy Moss20079.3384.28.1235.8
T.Y. Hilton20169.3273.88.9177.6
Larry Fitzgerald20089.3311.17.1284.2
Allen Robinson20159.33045.9199.3
Robert Woods20189.3265.68.1232.9
Julio Jones20159.2371.110.9259.9
Andre Johnson20089.2322.59.2314.9
Andre Johnson20099.2314.98.8256.6
Odell Beckham Jr.20159.2319.78.1298.6
Chad Johnson20059.2297.59268.3
Larry Fitzgerald20119.2269.15.1174.8
Golden Tate20149.2259.16.3211.4
Plaxico Burress20029.2254.56.9169.3
Jeremy Maclin20149.2276.88.8244.9
Greg Jennings20089.2265.29.4207.3
Randy Moss20099.2289.46.297.3
Wes Welker20119.1335.97.7291.4
Terrell Owens20019.1332.38.2321.9
Joe Horn20049.1301.96.3120.4
Anquan Boldin20139.12468.1219.6
Jerry Rice20019.1250.98.1257.1
Chad Johnson20069268.38.9289.7
Marvin Harrison20039281.58287.3
Antonio Bryant200892526.9123
Doug Baldwin20169253.758.5223.3
Chad Johnson20078.9289.75.6131
Calvin Johnson20088.92857.2202.7
Marques Colston20128.9258.48.6199.3
Demaryius Thomas20148.8340.97.4271.4
Muhsin Muhammad20048.83315.5163
Keenan Allen20178.8278.28.7262.1
Chad Johnson20038.8285.57.5280.3
Joe Horn20008.82778.1263.9
Joe Horn20028.8263.47.5237.5
Donald Driver20048.8261.28.4239.4
Brandin Cooks20158.8253.610246.3
Brandon Marshall20158.7343.26.1162.1
Antonio Brown20138.7303.459.4385.1
Roy Williams20068.7255.28177.9
Isaac Bruce20048.7254.27.4106.5
Drew Bennett20048.7277.26.8156.1
Keenan Allen20188.7262.18261.5
Dwayne Bowe20108.7278.68.2228.1
Eric Decker20128.7269.49.5281.8
Marvin Harrison20058.6267.69.2303.6
Larry Fitzgerald20058.53088.5199.6
Joey Galloway20058.5272.17.4210.6
Reggie Wayne20098.5284.47.7282.5
Peerless Price20028.5271.95.9166.1
Hines Ward20098.5247.78164.3
Tim Brown20008.52568.3265.4
Kevin Johnson20018.5247.75.9166.95
Mike Evans20148.5245.18.2213.1
Marvin Harrison20028.4384.29281.5
Marvin Harrison20008.4327.39.3351.7
Larry Fitzgerald20078.4300.99.3311.1
Braylon Edwards20078.4304.96.3164.3
Michael Thomas20178.4258.59.6321.5
Jimmy Smith20008.4260.37.8297
Troy Brown20018.42606.3207.4
Juju Smith-Schuster20188.3294.67.7115.2
Wes Welker20098.3285.46.9212.8
Hines Ward20028.3335.17.5277.4
Antonio Brown20168.3307.39.5310.3
Jordy Nelson20168.3306.75.5137.2
Larry Fitzgerald20158.3284.56.8246.9
Marques Colston20078.3284.28.6153
Steve Smith20068.3259.76.7235.2
Tim Brown20018.3265.47.3187.9
Anquan Boldin20058.2290.77.9230.1
Davante Adams20188.2329.67.9214.7
A.J. Green20128.2301.88306.6
Torry Holt20058.2289.36.6271.8
Terrell Owens20028.2321.97.5244
Calvin Johnson20108.2266.210.6361.2
T.J. Houshmandzadeh20068.2252.76.8299.7
Hakeem Nicks20108.2250.29237.2
Anquan Boldin20088.2265.58.1217.6
Davante Adams20168.2248.77.5222.5
Eric Moulds20008.1258.96.7189.7
Torry Holt20028.12479.3359.1
Joe Horn20018.1263.98.8263.4
Jerry Rice20028.1257.17161.9
Wes Welker20078.1280.97.8250.1
A.J. Green20138306.69209.3
Randy Moss20018270.157.3292.45
Torry Holt20078255.96.7161.6
Marvin Harrison20048287.38.6267.6

I sure hope you skimmed through that list as I did.

Incredibly, we see almost identical results as we did for the inefficient WR1s. The average efficient WR1 declined 39.18 points, as opposed to the 39.15 points we saw the inefficient WR1 declined to the following season.

At first glance, we see that regardless of how efficient you were, if you finished as a WR1 you were more likely than not to decline the following season. This makes intuitive sense – if you climb to the top of your position the only way to go from there is down.

  • 23 of 151 players increased on their point total the following season (15% vs. 17% for inefficient WR1s)
  • 72 of 151 players finished as a WR1 the following season (48% vs. 41% for inefficient WR1s)

We see a slight increase in WR1s the following season from this cohort, but nothing substantial or actionable.

Comparing Targets

We see a major difference in targets between efficient and inefficient WR1s, as inefficient WR1s averaged 167.78 targets in their WR1 season.

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We see the targets of these WR1s are actually much lower than the inefficient ones as if you’re efficient you won’t need as many targets to reach a WR1 season. The following season we only see a decrease in targets by 4.36 which is a much smaller margin than the inefficient WR1s, who decreased in targets by 21.85 the following year.

Let’s start diving in a little more to see if there is something hidden we can find between these differentiating WR1 seasons. What happens if we increase the efficiency threshold to nine YPT for these WR1 seasons to see if we can start to get a higher probability for following season production?

Increased Efficiency

Increasing the efficiency to nine yards per target drops our sample size down to 88 players.

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With a decline in 39.63 points the following season, we see here again that previous year YPT has literally no effect on the following season’s PPR point production.

  • 15 of 88 players increased on their fantasy point total the following season (17%)
  • 44 of 88 players finished as a WR1 the following season (50%)

Comparing Ages

With a last-ditch effort to see if we can find any use for YPT to help predict the following season, let’s try and see how their age affects this.

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Players who were younger still saw a solid decrease in fantasy points the following year, but overall slightly more fantasy points than the original group with only a 32.6 point reduction in points.

  • 21 of 105 players saw an increase in fantasy points the following season (20%)
  • 53 of 105 players finished as a WR1 the following season (51%)

Let’s see how the older players faired.

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We see a much bigger decline in the following season production as this group scores on average 59.3 fewer points the following season. This falls right in line with what we saw in the first part of the study.

  • 8 of 46 players saw an increase in production the next year (17% vs. 6% for the inefficient WR1s)
  • 19 of 46 players had a WR1 the following seasons (41% vs. 25% for the inefficient WR1s)

Main Takeaways

What these numbers tell us is that while the overall average decline is fairly large, we see that a decent amount of these players were still able to manage WR1 seasons the following year. This falls in line with Mike’s study on the decline of WRs at their age-30 season.

While it’s a risky bet to draft a WR1 who is age 30 or older, it’s a safer bet to draft the receiver who had a YPT over eight the year prior. This YPT study really helps to illustrate the age curve of WRs and why we should be avoiding WR1s who are 30 years old or older – especially the ones coming off a season under eight YPT.

It also helps to show us that efficiency really doesn’t matter for predicting the following season performance for WR1s and how hard it really is for these players to maintain WR1 status year in and year out.

Looking into 2020’s WR1s

Here is the full list of players to qualify as a WR1 according to the study.

PLAYERAGEreYPTPPR
Michael Thomas269.3374.6
Chris Godwin2311.2276.1
Julio Jones308.9274.1
Cooper Kupp268.7270.6
DeAndre Hopkins277.8268.6
Keenan Allen278261.5
Julian Edelman337.3258.75
Allen Robinson267.5254.9
Kenny Golladay2610.3250
Amari Cooper2510246.5
DeVante Parker269.4246.2

We touched on Julian Edelman, Allen Robinson, and DeAndre Hopkins in Part 1.

The remaining players are all guys we should be considering to sell high in dynasty except for Chris Godwin due to his young age. Knowing that most of these players are going to decline in fantasy points next year, this is a good time as any to capitalize on that peak value and sell. Remember, receivers generally start declining after turning 27 years old.

Thanks for reading along and I hope that you learned something new in this article. My goal was to try and find an edge in efficiency, but this just reaffirmed my beliefs in the age curve for receivers as well as understanding the true volatility of the WR1.

Thanks to RotoViz for the awesome tools they have that allowed all this research to get done.