It's Week 18 and we're still betting to win.
And if I'm the one doing the betting, there are two keys I need to have the confidence to place the wager:
A model-backed approach, or at the very least a quantitative-based angle. But almost all the bets in this column will be based on the outputs of models built by me, or occasionally by my colleagues at ESPN Analytics.
A less-efficient market. NFL sides and totals are voluminous markets, and betting against those mainstream numbers is like wagering on All-Madden mode. It's why I often look to props (especially on defense) and alternate lines. Less attention means less-efficient markets and therefore more opportunities to find value.
Those two criteria make up the crux of this weekly column, though occasionally I'll recommend bets that satisfy one criterion or another. Each week, I'll post bets from our models in mostly lower-visibility categories with the simple goal of coming out ahead. We'll be looking at odds all across the spectrum, from -1000 to 100-1 -- as far as I'm concerned, value is value no matter the price.
Results for this season are at the bottom of this story.
Defensive sacks
Nick Herbig (PIT) over 0.5 sacks (+375)
I consider myself a major Herbig stan, so it warms my heart to see the model identify his over as a value without my (possible) bias. Herbig isn't always on the field, but when he is he disrupts the quarterback. He has a well above average 23% pass rush win rate and 3.0% sack rate in his career, including 4.5 sacks this year.
He's not playing as much now as he was when Alex Highsmith was injured, but he'll still get his chances to sack Joe Burrow. My model prices Herbig's over at +237.
Andrew Van Ginkel (MIN) under 0.5 sacks (-170)
Van Ginkel has had a heck of a season (he was selected to the Pro Bowl Thursday, in fact) that includes 11.5 sacks. His advanced metrics are not quite so rosy, though: his pass rush win rate of 16% is just average for an edge rusher and his 8% pressure rate is 68th highest among all players.
On Sunday night, he'll have a particularly tough challenge: taking down Jared Goff. One of the Lions' QB's strengths is sack avoidance, as his 5.3% sack rate this year is lower than the 6.5% league average. That Detroit are slight favorites here hurts Van Ginkel's sack chances, too. I make the fair price here -250.
See also:
Cameron Heyward (PIT) under 0.5 sacks (-230)
Alex Highsmith (PIT) under 0.5 sacks (-110)
Nnamdi Madubuike (BAL) under 0.5 sacks (-175)
Joseph Ossai (CIN) under 0.5 sacks (-135) (added 1/3)
Brian Burns (NYG) over 0.5 sacks (+125) (added 1/3)
Kayvon Thibodeaux (NYG) over 0.5 sacks (+165) (added 1/3)
Montez Sweat (CHI) over 0.5 sacks (+375) (added 1/3)
Defensive tackles
DeShon Elliott (PIT) under 7.5 tackles + assists (-145)
Elliott is a safety but in reality he lines up all over. Elliott's tackle rates -- whether you are comparing him to a safety or a slot corner -- are extremely high. But they also have a significant run-pass split in favor of the run, making his tackle numbers susceptible to game script the way a linebackers typically are.
Elliott's opponent on Saturday? The Cincinnati Bengals, who have the second-highest pass rate over expectation in the NFL. That works in our favor betting the under. My model forecasts 6.3 combined tackles for Elliott.
See also:
Jordan Whitehead (TB) over 5.5 tackles + assists (-130) (added 1/3)
Brandon Jones (DEN) over 5.5 tackles + assists (-105) (added 1/3)
Defensive interceptions
Terrion Arnold (DET) under 0.5 interceptions (-700)
From my interception model's perspective, this is a pretty standard outside corner situation. Arnold's target rate and yards per coverage snap are close to average, Sam Darnold's interception rate is middle of the road, the Lions play roughly an average amount of two-high coverage and are only slight favorites.
The model believes the average starting outside corner has just about a 10% shot to nab a pick in a game, but Arnold hasn't recorded an interception all year, so it thinks the probability here is a shade lower than that and prices this at -975.
Alternate receiving yards
Amon-Ra St. Brown (DET) 100-plus receiving yards (+210)
Often when we've reached for upper echelon alts like this, we're looking at vertical threat receivers and playing the variance game. That's not really the case here, as St. Brown has a low average air yards per target. Instead, the model is simply buying stock in an elite wide receiver who has a median receiving yards line of 79.5 in a game with a 56.5 total.
From its perspective, that's a recipe for St. Brown to reach 100 yards more than a third of the time which is all that's required for this bet to breakeven.
Anytime touchdowns
Rome Odunze (CHI) to score 1-plus touchdowns (+425)
The payout is simply too high here for my touchdown model -- which prices Odunze to score at +258 -- to pass up. It's been a somewhat disappointing rookie campaign for Odunze, but he's playing a ton and that gives him an opportunity to score. He also has 1,275 air yards (yards through the air on targets, not necessarily receptions) on the year, which is 16th highest among wideouts.
The problem is he's converted just 36% of those into actual completed air yards, an incredibly poor rate. I'd be willing to bet on some positive regression there, in Week 18 and in 2025, which could result in a score.
QB interceptions
Jordan Love (GB) under 0.5 interceptions (-115)
Yes, Love has thrown interceptions on 2.5% of dropbacks, higher than the league average rate. However, I'm surprised that we're getting this favorable a price on his under for the same reason the model is, because the Packers are 10-point favorites. In addition to the ability of the quarterback and defense, interceptions are a product of circumstance (well, that and randomness).
Green Bay, which tilts run-heavy anyway, ought to lean even more on its ground game if it gets up big against Chicago as expected. Even when Love does pass, he should have to take fewer risks. I'm at -146 for Love's under.
Past results
Past results for this season are below. I wrote about the rules I set for myself regarding line movement and adding props in Week 1's column.