I’ll be honest with you – my main sport is basketball. When I started writing for Fantasy Labs and a variety of other places and I had to expand my knowledge of other sports (I mean, I’ve grown up watching NFL and MLB heavily but I can’t say I knew what wOBA was when I was 16) rather quickly. While it was stressful and even a little embarrassing/humbling at times, I think it’s actually made me a better writer across all of the sports I now cover.
The reason is something that fellow Fantasy Lab-ber Jonathan Bales wrote about in an article recently: idea sex. I encourage you to read that article because it’s good and it explains the concept better than I could, but essentially it’s about taking two unrelated ideas and thinking about them together. I think a lot more of this can and should happen across different sports.
The reason I bring this all up is because when I first started diving into the advanced metrics of MLB, I was really drawn to the idea of BABIP, or a statistic that more-or-less helps to measure luck and subsequent regression either way as a result. I know that some statisticians have been musing on this idea for a while – Ken Pomeroy, for example, has a “Luck” metric on his site for NCAA hoops. Also, analysts can talk about luck in terms of knowing where an average of something should be (mean) and whether it’s significantly higher or lower than that. It’s not a one-number thing, but it’s a useful anecdote to talk about either in articles or broadcasts.
However, the NFL doesn’t seem to have any sort of thing. Sure, it kind of exists in a broad form in terms of team wins. Pythagorean wins exist for the main sports and it essentially just says how many wins a team “should” have based on their point/run differential. Set that as your mean and you can see which teams have been lucky or not.
Obviously, context means a ton in every statistic that tries to incorporate or find luck. An example off the top of my head is Lance Stephenson – he shot almost impossibly bad last season for the Charlotte Hornets and I waited and waited and waited for regression that never came. There were probably a multitude of reasons why it didn’t – perhaps confidence, role, injury, etc… — so it can sometimes be hard to separate true luckiness and unluckiness from other variables that skew it.
So, this all leads me to introduce an idea that is far from perfect and finished as a product/stat/whatever you want to call it. I was inspired by the luck idea and by BABIP and wanted to try to create something along those lines for the NFL, and specifically for NFL receivers. The metric I have come up with is called TASER, short for Targets Add Scores Except in Redzone.
Ok, now the explanation.
I’ve had an idea like this for a while, but it wasn’t until Demaryius Thomas’ first couple of games happened that really jolted it out of me. Let me explain – Thomas led the NFL in both total targets (191) and redzone targets (40) in 2014. However, through the first two weeks of 2015, Thomas had 25 total targets but 0 redzone targets and 0 touchdowns. Obviously, we wouldn’t expect that trend to continue for a receiver like Thomas, so I wanted to try to quantify that regression into a number. What I came up with was TASER.
It’s really simple and the calculation is exactly the acronym: add a player’s total targets to their touchdowns and then divide by their redzone targets and touchdowns. This works because it operates under the simple assumption for the majority of receivers – most receivers that score a high number of touchdowns will also get a high number of targets in the redzone. Also, most receivers that score a high number of touchdowns also are a big part of their passing offense, which can be quantified by their total targets. As such, we see the difference between those two ideas and see how “lucky” or “unlucky” a receiver has been during the season.
Now, as all stats, there are expections and you have to use common sense to interpret the data. For example, we know that Julian Edelman is going to be quite the outlier in this regard – he gets a ton of receptions all the way up to the redzone, where then Brady focuses on Gronkowski. That happens and with some slot receivers, their data will have to be interpreted through a different lens. I’ve talked with Bales about this idea and he suggested adding in a component of expectation (kind of like our Plus/Minus) and I think he’s right and I’ll have to work on that for the future.
Just as an example, I ran the data after the first two weeks and here were the top 20 scores. For reference, there’s really no theoretical top limit – anything above 3 means regression (as in they’ve been “unlucky”) with it teir-ing up accordingly. Obviously, below 3 means they’ve been “lucky.”
| Name | Team | Position | TASER |
| Thomas, Demaryius | DEN | WR | 6.000 |
| Cooper, Amari | OAK | WR | 5.400 |
| Jones, Julio | ATL | WR | 4.875 |
| Lewis, Dion | NE | RB | 4.400 |
| Crabtree, Michael | OAK | WR | 4.286 |
| Cook, Jared | STL | TE | 4.000 |
| Bennett, Martellus | CHI | TE | 4.000 |
| Sanders, Emmanuel | DEN | WR | 3.889 |
| Ginn, Ted | CAR | WR | 3.833 |
| Sproles, Darren | PHI | RB | 3.800 |
| Tate, Golden | DET | WR | 3.667 |
| Edelman, Julian | NE | WR | 3.636 |
| Johnson, Calvin | DET | WR | 3.625 |
| Vereen, Shane | NYG | RB | 3.600 |
| Harvin, Percy | BUF | WR | 3.600 |
| Allen, Keenan | SD | WR | 3.571 |
| Beckham, Odell | NYG | WR | 3.500 |
| Washington, Nate | HOU | WR | 3.429 |
| Baldwin, Doug | SEA | WR | 3.429 |
| Heyward-Bey, Darrius | PIT | WR | 3.400 |
Thomas indeed came up with the highest TASER, thus expecting regression to more touchdowns and redzone targets. While he received no RZ targets in Week 3, he did have two in Week 4. I would expect him to stay near the top of that list until either he regresses to closer to his average of 2.5 per game or we find out that the offense or Peyton has changed so much that they no longer feature Demaryius in this way. I’d bet on the former, but I don’t think the latter is impossible nor does it make TASER worthless.
Running it after Week 4, there’s definitely some interesting results. Most notably, Demaryius Thomas increases his TASER and could be up to double-digits in a couple weeks if we don’t see the regression we expect. He’s currently on pace for a career high in targets – his 50 targets through 4 games puts him right at 200 for the year – but is on track for only 4 touchdowns, despite being in double-digits the last three years. You can see why TASER would scream regression.
Here’s the top 20 through Week 4, and at the bottom of this article, I’ll add the entire table of NFL players.
| Name | Team | Position | TASER |
| Thomas, Demaryius | DEN | WR | 8.286 |
| Cooper, Amari | OAK | WR | 8.167 |
| Allen, Keenan | SD | WR | 6.111 |
| Clay, Charles | BUF | TE | 5.571 |
| Lewis, Dion | NE | RB | 5.400 |
| Britt, Kenny | STL | WR | 5.400 |
| Beckham, Odell | NYG | WR | 5.300 |
| Brown, Antonio | PIT | WR | 5.200 |
| Matthews, Rishard | MIA | WR | 5.143 |
| Cooks, Brandin | NO | WR | 5.000 |
| Benjamin, Travis | CLE | WR | 4.875 |
| Tate, Golden | DET | WR | 4.857 |
| Colston, Marques | NO | WR | 4.833 |
| Crabtree, Michael | OAK | WR | 4.800 |
| Robinson, Allen | JAC | WR | 4.800 |
| Bennett, Martellus | CHI | TE | 4.750 |
| Sanders, Emmanuel | DEN | WR | 4.636 |
| Baldwin, Doug | SEA | WR | 4.571 |
| Jones, Julio | ATL | WR | 4.533 |
| Hurns, Allen | JAC | WR | 4.444 |
Amari Cooper is an interesting case – we don’t have the data on him historically like we do with Demaryius, but his overall numbers, which are outstanding for a rookie, should put him at more than just two touchdowns through the first four games. I would lean that way just from knowing his skill set and watching him play in college, but there will be guys who are naturally higher or lower TASER guys throughout their careers, just like there are guys who always seem to have a lower or higher BABIP than we’d expect.
I’d expect TASER to have more weird stuff than BABIP just because football is naturally less predictive than baseball because of the differences in sample sizes. That’s why I think using the most frequent stat for receiving (targets) is the way to go in attempting to measure luck and regression.
I also think there might have to be some stuff added to account for completion percentage and average depth of target, as this would probably affect the data – not all receivers are the same, think Julio Jones and Julian Edelman. However, this is a start and something I think can be communal – let me know your thoughts and ideas. I’ve never really tried to invent a statistic before, so there might be some really obvious flaws that I’m missing because I’m too close to it at the moment. However, I do feel confident in the idea and that eventually we can craft this into something really useful as football catches up with the other major sports in terms of predictive analytics.
TASER data through Week 4:
| Name | Team | Position | TASER |
| Thomas, Demaryius | DEN | WR | 8.286 |
| Cooper, Amari | OAK | WR | 8.167 |
| Allen, Keenan | SD | WR | 6.111 |
| Clay, Charles | BUF | TE | 5.571 |
| Lewis, Dion | NE | RB | 5.400 |
| Britt, Kenny | STL | WR | 5.400 |
| Beckham, Odell | NYG | WR | 5.300 |
| Brown, Antonio | PIT | WR | 5.200 |
| Matthews, Rishard | MIA | WR | 5.143 |
| Cooks, Brandin | NO | WR | 5.000 |
| Benjamin, Travis | CLE | WR | 4.875 |
| Tate, Golden | DET | WR | 4.857 |
| Colston, Marques | NO | WR | 4.833 |
| Crabtree, Michael | OAK | WR | 4.800 |
| Robinson, Allen | JAC | WR | 4.800 |
| Bennett, Martellus | CHI | TE | 4.750 |
| Sanders, Emmanuel | DEN | WR | 4.636 |
| Baldwin, Doug | SEA | WR | 4.571 |
| Jones, Julio | ATL | WR | 4.533 |
| Hurns, Allen | JAC | WR | 4.444 |
| Harvin, Percy | BUF | WR | 4.375 |
| Johnson, Calvin | DET | WR | 4.231 |
| Dorsett, Phillip | IND | WR | 4.200 |
| Dunbar, Lance | DAL | RB | 4.143 |
| Washington, Nate | HOU | WR | 4.125 |
| Evans, Mike | TB | WR | 4.125 |
| Brown, John | ARI | WR | 4.111 |
| Matthews, Jordan | PHI | WR | 4.091 |
| Hilton, T.Y. | IND | WR | 4.091 |
| Garcon, Pierre | WAS | WR | 4.000 |
| Ingram, Mark | NO | RB | 4.000 |
| Sproles, Darren | PHI | RB | 4.000 |
| Vereen, Shane | NYG | RB | 4.000 |
| Forsett, Justin | BAL | RB | 4.000 |
| Watson, Benjamin | NO | TE | 4.000 |
| Murray, Latavius | OAK | RB | 4.000 |
| Johnson, David | ARI | RB | 4.000 |
| Williams, Maxx | BAL | TE | 4.000 |
| Smith, Steve | BAL | WR | 3.929 |
| Edelman, Julian | NE | WR | 3.923 |
| Wallace, Mike | MIN | WR | 3.875 |
| Cunningham, Benny | STL | RB | 3.833 |
| Gabriel, Taylor | CLE | WR | 3.833 |
| Wilson, Marquess | CHI | WR | 3.833 |
| Moncrief, Donte | IND | WR | 3.818 |
| Hartline, Brian | CLE | WR | 3.800 |
| Maclin, Jeremy | KC | WR | 3.750 |
| Reed, Jordan | WAS | TE | 3.727 |
| Woodhead, Danny | SD | RB | 3.714 |
| Heyward-Bey, Darrius | PIT | WR | 3.714 |
| Cook, Jared | STL | TE | 3.625 |
| Freeman, Devonta | ATL | RB | 3.625 |
| Watkins, Sammy | BUF | WR | 3.600 |
| Miller, Lamar | MIA | RB | 3.600 |
| Yeldon, T.J. | JAC | RB | 3.600 |
| Lockett, Tyler | SEA | WR | 3.600 |
| Shorts, Cecil | HOU | WR | 3.538 |
| Ginn, Ted | CAR | WR | 3.500 |
| Agholor, Nelson | PHI | WR | 3.500 |
| Woods, Robert | BUF | WR | 3.500 |
| Johnson, Andre | IND | WR | 3.429 |
| Coleman, Brandon | NO | WR | 3.429 |
| Cooper, Riley | PHI | WR | 3.400 |
| Brown, Marlon | BAL | WR | 3.333 |
| Powell, Bilal | NYJ | RB | 3.286 |
| Murphy, Louis | TB | WR | 3.286 |
| Witten, Jason | DAL | TE | 3.273 |
| Kelce, Travis | KC | TE | 3.273 |
| Marshall, Brandon | NYJ | WR | 3.250 |
| Aiken, Kamar | BAL | WR | 3.250 |
| Randle, Rueben | NYG | WR | 3.250 |
| Crowder, Jamison | WAS | WR | 3.250 |
| Fleener, Coby | IND | TE | 3.250 |
| Ebron, Eric | DET | TE | 3.222 |
| Riddick, Theo | DET | RB | 3.222 |
| Fitzgerald, Larry | ARI | WR | 3.200 |
| Johnson, Steve | SD | WR | 3.200 |
| Anderson, C.J. | DEN | RB | 3.200 |
| Kendricks, Lance | STL | TE | 3.200 |
| Hankerson, Leonard | ATL | WR | 3.167 |
| Wheaton, Markus | PIT | WR | 3.167 |
| White, Roddy | ATL | WR | 3.167 |
| Celek, Garrett | SF | TE | 3.167 |
| Enunwa, Quincy | NYJ | WR | 3.167 |
| Beasley, Cole | DAL | WR | 3.111 |
| Snead, Willie | NO | WR | 3.111 |
| Charles, Jamaal | KC | RB | 3.091 |
| Hopkins, DeAndre | HOU | WR | 3.087 |
| Ertz, Zach | PHI | TE | 3.000 |
| Hawkins, Andrew | CLE | WR | 3.000 |
| Owusu, Chris | NYJ | WR | 3.000 |
| Bernard, Giovani | CIN | RB | 3.000 |
| Polk, Chris | HOU | RB | 3.000 |
| Sims, Charles | TB | RB | 3.000 |
| Tamme, Jacob | ATL | TE | 3.000 |
| Jennings, Greg | MIA | WR | 3.000 |
| Robinson, Khiry | NO | RB | 3.000 |
| Mathews, Ryan | PHI | RB | 3.000 |
| Gore, Frank | IND | RB | 3.000 |
| Spiller, C.J. | NO | RB | 3.000 |
| Landry, Jarvis | MIA | WR | 2.944 |
| Green, A.J. | CIN | WR | 2.938 |
| Royal, Eddie | CHI | WR | 2.909 |
| Grant, Ryan | WAS | WR | 2.889 |
| Douglas, Harry | TEN | WR | 2.875 |
| Floyd, Michael | ARI | WR | 2.875 |
| Floyd, Malcom | SD | WR | 2.857 |
| Cameron, Jordan | MIA | TE | 2.833 |
| Austin, Miles | PHI | WR | 2.833 |
| Wright, Kendall | TEN | WR | 2.800 |
| Barnidge, Gary | CLE | TE | 2.800 |
| Jennings, Rashad | NYG | RB | 2.800 |
| Walters, Bryan | JAC | WR | 2.800 |
| Kearse, Jermaine | SEA | WR | 2.778 |
| Stills, Kenny | MIA | WR | 2.750 |
| Adams, Davante | GB | WR | 2.714 |
| Moore, Lance | DET | WR | 2.714 |
| Funchess, Devin | CAR | WR | 2.714 |
| Mumphery, Keith | HOU | WR | 2.714 |
| Lewis, Marcedes | JAC | TE | 2.714 |
| Austin, Tavon | STL | WR | 2.700 |
| Daniels, Owen | DEN | TE | 2.700 |
| Greene, Rashad | JAC | WR | 2.667 |
| Brown, Corey | CAR | WR | 2.667 |
| Peterson, Adrian | MIN | RB | 2.667 |
| Abdullah, Ameer | DET | RB | 2.625 |
| Randle, Joseph | DAL | RB | 2.600 |
| Boldin, Anquan | SF | WR | 2.583 |
| Graham, Jimmy | SEA | TE | 2.583 |
| Davis, Vernon | SF | TE | 2.571 |
| Grimes, Jonathan | HOU | RB | 2.571 |
| McCoy, LeSean | BUF | RB | 2.571 |
| Bailey, Stedman | STL | WR | 2.571 |
| Walker, Delanie | TEN | TE | 2.571 |
| Jackson, Vincent | TB | WR | 2.556 |
| Rudolph, Kyle | MIN | TE | 2.545 |
| Donnell, Larry | NYG | TE | 2.545 |
| Williams, Terrance | DAL | WR | 2.533 |
| Jones, James | GB | WR | 2.533 |
| Forte, Matt | CHI | RB | 2.500 |
| Green, Ladarius | SD | TE | 2.500 |
| Rodgers, Richard | GB | TE | 2.500 |
| Wright, Jarius | MIN | WR | 2.500 |
| Patton, Quinton | SF | WR | 2.500 |
| Jones, Marvin | CIN | WR | 2.455 |
| Cobb, Randall | GB | WR | 2.450 |
| Gillmore, Crockett | BAL | TE | 2.444 |
| Smith, Torrey | SF | WR | 2.444 |
| Lee, Marqise | JAC | WR | 2.400 |
| McCluster, Dexter | TEN | RB | 2.400 |
| Gordon, Melvin | SD | RB | 2.400 |
| Starks, James | GB | RB | 2.400 |
| Thompson, Chris | WAS | RB | 2.400 |
| Gronkowski, Rob | NE | TE | 2.375 |
| Eifert, Tyler | CIN | TE | 2.357 |
| Olsen, Greg | CAR | TE | 2.350 |
| Juszczyk, Kyle | BAL | FB | 2.333 |
| Montgomery, Ty | GB | WR | 2.333 |
| Rivera, Mychal | OAK | TE | 2.286 |
| Hogan, Chris | BUF | WR | 2.286 |
| Dobson, Aaron | NE | WR | 2.250 |
| Graham, Garrett | HOU | TE | 2.250 |
| Williams, DeAngelo | PIT | RB | 2.200 |
| Bell, Joique | DET | RB | 2.200 |
| Mason, Tre | STL | RB | 2.200 |
| Stewart, Jonathan | CAR | RB | 2.200 |
| Meredith, Cameron | CHI | WR | 2.200 |
| Miller, Zach | CHI | TE | 2.200 |
| Wilson, Albert | KC | WR | 2.200 |
| Hyde, Carlos | SF | RB | 2.167 |
| Willson, Luke | SEA | TE | 2.167 |
| Martin, Doug | TB | RB | 2.167 |
| Williams, Karlos | BUF | RB | 2.167 |
| Bellamy, Josh | CHI | WR | 2.167 |
| Decker, Eric | NYJ | WR | 2.154 |
| Johnson, Charles | MIN | WR | 2.143 |
| Fells, Darren | ARI | TE | 2.143 |
| Fells, Daniel | NYG | TE | 2.143 |
| Hill, Josh | NO | TE | 2.143 |
| Jackson, Fred | SEA | RB | 2.143 |
| Parker, Preston | NYG | WR | 2.125 |
| Lynch, Marshawn | SEA | RB | 2.125 |
| Amendola, Danny | NE | WR | 2.125 |
| Seferian-Jenkins, Austin | TB | TE | 2.111 |
| Norwood, Jordan | DEN | WR | 2.111 |
| Sanu, Mohamed | CIN | WR | 2.091 |
| Murray, DeMarco | PHI | RB | 2.000 |
| Huff, Josh | PHI | WR | 2.000 |
| Reece, Marcel | OAK | FB | 2.000 |
| Thomas, DeAnthony | KC | WR | 2.000 |
| Robinson, Josh | IND | RB | 2.000 |
| Lacy, Eddie | GB | RB | 2.000 |
| Crowell, Isaiah | CLE | RB | 2.000 |
| Dickson, Ed | CAR | TE | 2.000 |
| Johnson, Chris | ARI | RB | 2.000 |
| Pierce, Bernard | JAC | RB | 2.000 |
| Whittaker, Fozzy | CAR | RB | 2.000 |
| Brown, Jaron | ARI | WR | 1.857 |
| Roberts, Andre | WAS | WR | 1.857 |
| Gresham, Jermaine | ARI | TE | 1.857 |
| Coffman, Chase | TEN | TE | 1.833 |
| Jeffery, Alshon | CHI | WR | 1.800 |
| Griffin, Ryan | HOU | TE | 1.800 |
| Nelson, J.J. | ARI | WR | 1.800 |
| Burkhead, Rex | CIN | RB | 1.800 |
| OShaughnessy, James | KC | TE | 1.800 |
| Harbor, Clay | JAC | TE | 1.800 |
| Smith, Lee | OAK | TE | 1.800 |
| Fasano, Anthony | TEN | TE | 1.778 |
| Miller, Heath | PIT | TE | 1.750 |
| Roberts, Seth | OAK | WR | 1.750 |
| Hunter, Justin | TEN | WR | 1.714 |
| Taliaferro, Lorenzo | BAL | RB | 1.714 |
| Holmes, Andre | OAK | WR | 1.714 |
| Williams, Damien | MIA | RB | 1.667 |
| Walford, Clive | OAK | TE | 1.667 |
| Matthews, Chris | SEA | WR | 1.667 |
| Morris, Alfred | WAS | RB | 1.667 |
| Allen, Dwayne | IND | TE | 1.625 |
| Cotchery, Jerricho | CAR | WR | 1.625 |
| Tolbert, Mike | CAR | FB | 1.625 |
| Blue, Alfred | HOU | RB | 1.600 |
| Bolden, Brandon | NE | RB | 1.600 |
| Cunningham, Jerome | NYG | TE | 1.600 |
| Dray, Jim | CLE | TE | 1.600 |
| Ellison, Rhett | MIN | TE | 1.600 |
| Humphries, Adam | TB | WR | 1.600 |
| Johnson, Malcolm | CLE | FB | 1.600 |
| Jones, Matt | WAS | RB | 1.600 |
| McFadden, Darren | DAL | RB | 1.600 |
| Olawale, Jamize | OAK | RB | 1.600 |
| McKinnon, Jerick | MIN | RB | 1.600 |
| Street, Devin | DAL | WR | 1.600 |
| Asiata, Matt | MIN | RB | 1.600 |
| DiMarco, Patrick | ATL | FB | 1.600 |
| Hillman, Ronnie | DEN | RB | 1.600 |
| Rodgers, Jacquizz | CHI | RB | 1.600 |
| Stevens, Craig | TEN | TE | 1.600 |
| Ivory, Chris | NYJ | RB | 1.571 |
| Campanaro, Michael | BAL | WR | 1.571 |
| Fiedorowicz, C.J. | HOU | TE | 1.571 |
| Sankey, Bishop | TEN | RB | 1.556 |
| Bryant, Dez | DAL | WR | 1.500 |
| Davis, Mike | SF | RB | 1.500 |
| Bell, Blake | SF | TE | 1.500 |
| Caldwell, Andre | DEN | WR | 1.500 |
| McDonald, Vance | SF | TE | 1.500 |
| Toilolo, Levine | ATL | TE | 1.500 |
| Waller, Darren | BAL | WR | 1.500 |
| Williams, Nick | ATL | WR | 1.500 |
| Parker, DeVante | MIA | WR | 1.444 |
| Carrier, Derek | WAS | TE | 1.429 |
| Davis, Knile | KC | RB | 1.400 |
| Ellington, Bruce | SF | WR | 1.400 |
| Jackson, DeSean | WAS | WR | 1.400 |
| Jones, Taiwan | OAK | RB | 1.400 |
| Robinson, Denard | JAC | RB | 1.400 |
| White, DeAndrew | SF | WR | 1.400 |
| Bowe, Dwayne | CLE | WR | 1.400 |
| Oliver, Branden | SD | RB | 1.400 |
| Patterson, Cordarrelle | MIN | WR | 1.400 |
| Shepard, Russell | TB | WR | 1.400 |
| Sherman, Anthony | KC | FB | 1.400 |
| Varga, Tyler | IND | FB | 1.400 |
| Ward, Terron | ATL | RB | 1.400 |
| Green, Virgil | DEN | TE | 1.375 |
| Escobar, Gavin | DAL | TE | 1.333 |
| Coleman, Tevin | ATL | RB | 1.333 |
| Ellington, Andre | ARI | RB | 1.333 |
| Stoneburner, Jake | MIA | TE | 1.333 |
| Grant, Corey | JAC | RB | 1.333 |
| Housler, Rob | CLE | TE | 1.333 |
| Johnson, Austin | NO | FB | 1.286 |
| Bush, Reggie | SF | RB | 1.286 |
| Celek, Brent | PHI | TE | 1.286 |
| Chandler, Scott | NE | TE | 1.273 |
| Alualu, Tyson | JAC | DT | 1.200 |
| Cadet, Travaris | NE | RB | 1.200 |
| Coleman, Derrick | SEA | FB | 1.200 |
| Davis, Geremy | NYG | WR | 1.200 |
| Davis, Kellen | NYJ | TE | 1.200 |
| Felton, Jerome | BUF | RB | 1.200 |
| Fisher, Jake | CIN | OT | 1.200 |
| Fowler, Jalston | TEN | FB | 1.200 |
| Hayne, Jarryd | SF | RB | 1.200 |
| Hill, Jeremy | CIN | RB | 1.200 |
| Jacobs, Nic | JAC | TE | 1.200 |
| Mulligan, Matthew | BUF | TE | 1.200 |
| Nix, Roosevelt | PIT | RB | 1.200 |
| Pettigrew, Brandon | DET | TE | 1.200 |
| Sims, Dion | MIA | TE | 1.200 |
| Swaim, Geoff | DAL | TE | 1.200 |
| Young, Darrel | WAS | FB | 1.200 |
| Green-Beckham, Dorial | TEN | WR | 1.182 |
| Allen, Javorius | BAL | RB | 1.167 |
| Rainey, Bobby | TB | RB | 1.167 |
| Butler, Brice | DAL | WR | 1.143 |
| Draughn, Shaun | CLE | RB | 1.143 |
| Hewitt, Ryan | CIN | TE | 1.000 |
| Miller, Bruce | SF | FB | 1.000 |
| Reitz, Joe | IND | G | 1.000 |
| Streater, Rod | OAK | WR | 1.000 |
