Week 13 Recap
First, Sammy Watkins is hot floating garbage. I think we can all agree on this. Moving on, it was a pretty rotten week for the model outside two solid WR hits. Both Anthony Miller and Courtland Sutton were top ten WRs on the week. For his part, Darren Waller was a top 5 TE. But the happiness really ends there. Sterling Shepard and Decaf Metcalf both came in over their projections, but were still fairly underwhelming. The rest were horrible busts.
I’ve berated the model, and I can report that it is inconsolable. It promised — through heaving sobs — to be better.
Here are the full results for Week 13:
Name | TM | Projection | Week 13 Actual |
Odell Beckham | CLE | 13.9 | 5.9 |
D.K. Metcalf | SEA | 11.6 | 13.5 |
Courtland Sutton | DEN | 10.9 | 23.4 |
Anthony Miller | CHI | 10.1 | 23 |
Eric Ebron | IND | 9.5 | IR |
Nelson Agholor | PHI | 9.4 | 7.1 |
Darren Waller | OAK | 9.3 | 17 |
Kelvin Harmon | WAS | 9.2 | 8.1 |
Cameron Brate | TB | 9.1 | 1.5 |
Noah Fant | DEN | 8.9 | 1.5 |
Danny Amendola | DET | 8.8 | 6.2 |
Diontae Johnson | PIT | 8.5 | 4.1 |
Sterling Shepard | NYG | 8.4 | 13 |
Sammy Watkins | KC | 8.1 | 0 |
Week 14
The Buy-Low model uses target share and air yards to estimate a player’s expected production in the passing game, then highlights the players that underperformed relative to expectation. The key insight behind the model is that opportunity is sticky and production (in the form of catches and touchdowns) is not. You want to buy the signal and fade the noise, and the model helps us do just that.
The out of sample r-squared for the model for this week is 0.55 (down 6 points from 0.61 in Week 13).
Editor’s Note: Before using the model, we strongly suggest everyone read Josh’s article introducing the concept here. We also recommend you listen to his interview with Adam Levitan in Episode 4 of the ETR podcast.
In general, pay most attention to the projection column as it reflects the value of the opportunity each player received. The next piece of information you should weigh is the size of the difference between what the model says a normal game from this player should be given his opportunity, and his actual performance in the recent past. The larger this difference, the greater the chance that the public will be fading the player, making him low-owned. And while we might be tempted to infer that larger differences might lead to a stronger “rubber band” regression effect, it’s typically the case that what dominates is the opportunity.
KEY
* Projection = The full-PPR projection the model gives for a player for the rest of the season based upon his opportunity in the previous three games.
* Actual = A player’s average PPR points per game over the past three games.
* Difference = The difference between projection and previous week result in full-PPR fantasy points.
Teams on BYE this Week are: NONE
Name | TM | Projection | Actual | Difference | DK Salary |
Leonard Fournette | JAX | 13.5 | 13.3 | -0.2 | 7800 |
Odell Beckham | CLE | 12.4 | 12.1 | -0.3 | 6300 |
Mike Evans | TB | 11.2 | 9.7 | -1.5 | 7200 |
Darius Slayton | NYG | 11.2 | 10.6 | -0.6 | NA |
D.K. Metcalf | SEA | 10.5 | 10 | -0.5 | NA |
Christian Kirk | ARI | 9.7 | 7.7 | -2 | 5200 |
Amari Cooper | DAL | 9.5 | 7.8 | -1.8 | NA |
Taylor Gabriel | CHI | 9.3 | 7.8 | -1.5 | Concussed? |
Kelvin Harmon | WAS | 9.2 | 8.6 | -0.7 | 3700 |
Terry McLaurin | WAS | 9.2 | 8.3 | -0.9 | 5100 |
Hunter Henry | LAC | 8.7 | 8 | -0.8 | 5100 |
Zach Pascal | IND | 8.7 | 7.2 | -1.5 | 5500 |
Auden Tate | CIN | 8.7 | 7.4 | -1.3 | 4000 |
Jamison Crowder | NYJ | 8.6 | 8.4 | -0.2 | 5300 |
Nelson Agholor | PHI | 8.3 | 7.5 | -0.7 | NA |
KEY TAKEAWAYS
- I have no idea what Leonard Fournette is doing on the list.
- Mike Evans is back. What a glorious time to be alive.
- Christian Kirk is back. I can’t feel my face.
- Terry “F1” McLaurin makes the list, as Ford V Ferrari gathers Oscar hype. Coincidence? I think not.
- Zach Pascal seems overpriced and I imagine he could end up high owned, but he appears to be the man in the Indy given all the injuries.