Koko WR Fantasy Projections

Here is the next installment of the Koko The Monkey's fantasy football projections. Wide receivers are ranked based on a regression from last year's stats.

These projections are intended to be establish the baseline minimum accuracy of projections as the most reasonably naive predictions. The general explanation of the system can be found in the post ranking quarterbacks.

WR fantasy performance is far simpler than QB fantasy performance. Receiving yards and touchdowns are the only driving factors. Rushing or kick returning yards are ignored in these WR projections. Receiving yards and TDs appear to regress at similar rates from year to year, so these projected rankings will likely be a straight regurgitation of last year's end-of-year rankings.

I included WRs with at least 20 receptions in a season in the analysis. Depending on how high the cutoff, or which stat you use (yards, games, receptions), the regression rate is different. In the end however, the overall rankings aren't significantly affected, and the projected points are only slightly different.

Wide Receivers don't appear to have any consistency in terms of fumbles or injuries. They average 0.05 fumbles per game, with guys who get a lot of receptions obviously having more opportunities. WRs play in an average of 14.3 games in a season regardless of how many they played the year before.

I've removed Burress and Harrison, but I didn't spend much time looking through the list to find guys who may have retired or who may already be on the IR.

RankNameTDsYdsFumPts/GProj Pts
1Anquan Boldin 0.5471.10.076.695.0
2Larry Fitzgerald 0.4772.80.056.491.3
3Calvin Johnson 0.4769.
4Andre Johnson 0.3878.
5Steve Smith CAR0.3579.
6Greg Jennings 0.4067.80.055.781.7
7Roddy White 0.3671.10.055.680.0
8Randy Moss 0.4557.40.065.578.1
9Brandon Marshall 0.3469.80.065.477.5
10Terrell Owens 0.4359.00.055.477.4
11Antonio Bryant 0.3666.20.055.376.5
12Lance Moore 0.4354.
13Marques Colston 0.3661.
14Vincent Jackson 0.3660.
15Reggie Wayne 0.3362.
16Hines Ward 0.3658.
17Dwayne Bowe 0.3657.90.054.970.7
18Kevin Walter 0.3853.40.054.969.5
19Bernard Berrian 0.3655.80.054.869.2
20Santana Moss 0.3358.70.054.869.2
21Justin Gage 0.3852.30.054.868.7
22Eddie Royal 0.3258.70.054.767.8
23Deion Branch 0.3850.70.054.767.5
24Derrick Mason 0.3158.50.054.766.8
25Donald Driver 0.3157.60.054.666.4
26Wes Welker 0.2663.10.054.666.2
27Laveranues Coles 0.3651.60.054.666.1
28Isaac Bruce 0.3651.10.054.665.8
29Muhsin Muhammad 0.3154.30.054.563.9
30T.J. Houshmandzadeh 0.2955.80.054.563.7
31Santonio Holmes 0.3252.60.054.463.3
32Lee Evans 0.2657.80.054.462.3
33Steve Breaston 0.2657.30.054.462.2
34Jerricho Cotchery 0.3151.90.054.362.1
35Matt Jones 0.2557.60.054.361.6
36Greg Camarillo 0.2653.
37Braylon Edwards 0.2652.
38DeSean Jackson 0.2453.
39Chad Ochocinco 0.3144.
40Torry Holt 0.2649.
41Devery Henderson 0.2649.
42Michael Jenkins 0.2649.00.053.956.2
43Anthony Gonzalez 0.2944.80.053.955.3
44Chris Chambers 0.3339.90.053.955.2
45Kevin Curtis 0.2845.90.053.955.2
46Donnie Avery 0.2746.80.053.955.1
47Malcom Floyd 0.3141.50.053.854.8
48Devin Hester 0.2746.50.053.854.7
49Ted Ginn Jr. 0.2449.50.063.854.2
50Mark Clayton 0.2646.00.053.854.1
51Antwaan Randle El 0.2942.30.053.753.5
52Amani Toomer 0.2941.80.053.753.0
53Nate Washington 0.2643.60.053.752.4
54Patrick Crayton 0.2940.70.053.752.2
55Josh Reed 0.2247.40.053.651.6
56Mark Bradley 0.2939.10.053.651.2
57Brandon Stokley 0.2741.20.053.651.1
58Dennis Northcutt 0.2543.30.053.550.6
59Bobby Wade 0.2444.10.053.550.5
60Bryant Johnson 0.2640.50.053.550.2
61Jerheme Urban 0.2937.00.053.549.7
62Brandon Lloyd 0.2639.90.053.549.6
63Domenik Hixon 0.2442.40.053.549.5
64Koren Robinson 0.2540.10.053.449.2
65Josh Morgan 0.2936.10.053.449.1
66Ike Hilliard 0.2936.10.053.448.9
67Hank Baskett 0.2737.70.053.448.5
68Roy Williams 0.2737.40.053.448.3
69Johnnie Lee Higgins 0.2934.00.053.347.5
70Steve Smith NYG0.2241.30.053.347.0
71Davone Bess 0.2240.
72Chansi Stuckey 0.2734.
73Jabar Gaffney 0.2437.
74Rashied Davis 0.2436.
75Reggie Williams 0.2633.
76Bobby Engram 0.1942.
77Michael Clayton 0.2239.
78Jason Avant 0.2435.
79Arnaz Battle 0.1941.
80James Jones 0.2336.
81Shaun McDonald 0.2236.
82Brandon Jones 0.2237.
83Jordy Nelson 0.2434.
84Dane Looker 0.2532.
85Jason Hill 0.2432.20.052.942.1
86Justin McCareins 0.1937.80.062.941.9
87Harry Douglas 0.2232.30.052.840.3
88Roscoe Parrish 0.2231.00.052.839.8
89Antonio Chatman 0.1931.90.052.637.8
90Brian Finneran 0.2226.80.052.536.2

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7 Responses to “Koko WR Fantasy Projections”

  1. Nate says:

    Thanks for doing this analysis -- this is an interesting idea.

    Many fantasy leagues also award points for each reception a player records. Any chance of adding that stat to the table?

  2. ben says:

    I play in a PPR league. Do you have any idea what the average yards per reception is in the NFL? dividing yards per game by average yards per reception is probably an accurate enough estimate of receptions per game.

  3. ben says:

    I would think that player age (or years in the league should give the same info) would be a valuable predictor of next years results. I would imagine that for a WR the numbers get for the first couple of years of the players career and then plataeu as they hit their full ability and then start dropping off about 30 as their body ages.

    And of course each skill position will have a different age profile. I saw a post somewhere the demonstrated that RB's start declining (at least in terms of yards per carry) as soon as they enter the league.

  4. Nate says:


    Yards per reception can vary pretty significantly from player to player. For example, in 2007 Chad Johnson averaged 15.4 YPR while TJ Houshmandzadeh averaged only 10.2.

  5. Shake says:

    Compare Wes Welker to Vincent Jackson for a massive YPC split.

  6. ben says:

    I decided to do something for the ppr players out there. I took the data from pro-football-reference.com and regressed the 2008 wr receptions myself.

    I followed the same methodology as Brian (min 20 receptions, from 2001-2008, looking at per game stats) and I ran the regression for wr yards first to confirm that I was doing it right. I got the regression equation: 0.60x + 20.0 which is pretty close to his 0.58x + 20.6. Any differences may be caused by the fact that we are using different databases.

    Then I ran the regression for wr receptions. The equation is: 0.63x + 1.38 with an r-squared of 0.42

    You can plug that equation into your own spreadsheet or you can look at the one that I made on google docs:


  7. Anonymous says:

    How did you guys set up the raw data and get a regression line for all of the variables the way I have it set up, it has 7 different series if anyone can help I would appreciate it.

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