Week 3 Recap
Week 3 was a good one for the model. It correctly identified the big breakout by Mike Evans, who ended up in the Milly Maker winning lineup on DraftKings. That’s always good to see. Curtis Samuel was also decent, beating his projection by five points. Marquez Valdes-Scantling scored a touchdown on a free play to start the Packers game against the Broncos, making him an early hit on Sunday as well.
Will Fuller was a bit of a disappointment. Despite beating his projection, he shared the deep looks with Kenny Stills, making his future slightly less shimmering. Still, as you’ll see, he’s back on the list again this week so perhaps there’s hope.
Here are the full results for Week 3:
|Name||Projection||Week 3 PPR||MilliMaker Own|
But enough of the review. We’re on to week 4.
For those who are new, 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 0.58 (last week was 0.57, and higher is better).
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.
* 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. Currently it’s based on just three weeks of data.
* Actual = A player’s average PPR points per game through the first 3 games.
* Difference = The difference between projection and previous week result in full-PPR fantasy points.
- Allen Robinson tops the list after a Monday night game that saw Taylor Gabriel score all the touchdowns. Robinson is an easy play, dominating the opportunity in Chicago and doubling the weighted opportunity rating of Gabriel over the first three weeks. Let the rubes chase the day-old, already-blown fireworks. Robinson is the WR1 in Chicago.
- Stefon Diggs makes the list for what I believe is the first time ever. A dynamic playmaker, Diggs seldom underperforms his opportunity, but here we are. The low pass volume of the Vikings offense is reflected in his correspondingly low point per game projection, but he’s still underperforming that substantially. When you see big name receivers like this struggling early in the season it’s often the case that they get fed. The reasons why are unclear, and you can fit any number of narratives to answer the question, but if the Vikings decide to feature Diggs it’s likely he’ll do something with his opportunities.
- DeVante Parker dropped a red zone target from Josh Rosen on Sunday that might have paid off all 7 of the people who were brave enough to roster him in Week 3. While Rosen didn’t look great, he threw 6 passes Parker’s way. Parker caught 3. Preston Williams saw 12 targets and caught 4, as a point of comparison. If that trend continues Parker won’t be long for the buy low list. I’m not ready to give up yet since Parker is still the clear number one in Miami over three weeks of play, but you’ll need stones of steel to throw him in more than a handful of lineups this week.