We're 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 can be found at the bottom of this story.
Defensive player props
Roquan Smith (BAL) under 9.5 tackles + assists (-140)
Smith has put up some huge tackle numbers against the run, as 28% of run plays resulted in a tackle for Smith, second highest among inside linebackers. So why are we fading him? Well, not every play is a run. The Ravens are 6.5-point favorites over the Bengals, which works in our favor.
If the Bengals fall behind as the line expects, they'll have to rely more on Joe Burrow's arm. In fact, that's what they want to do: no team passes more relative to expectations than Cincinnati, per NFL Next Gen Stats. All that works in our favor and my tackle model forecasts a mean of 7.4 tackles + assists for Smith.
Kyle Van Noy (BAL) under 0.5 sacks (-125)
Just a few years ago in 2021, Burrow had a high 8.6% sack rate, which represented a weakness in his game. But in both 2023 and 2024 -- despite league-wide sack rates going up in that span -- Burrow's sack rate has been just 6.0%, lower than league average. That helps our case with the under here.
In addition, Van Noy's pass rush win rate at edge this season is 18%, which is 16th best out of 52 pass rushers but means he's probably running a little hot with sacks (7.0) in comparison. I'm a little concerned Van Noy gets to mostly play opposite rookie tackle Amarius Mims in this one, but I'll trust my model when it says the fair price should be -188.
See also:
Nick Bosa (SF) over 0.5 sacks (+100)
Kevin Byard III (CHI) under 6.5 tackles + assists (-120)
Taylor Rapp (BUF) under 6.5 tackles + assists (-110) (added 9/8)
Dexter Lawrence II (NYG) under 0.5 sacks (-110) (added 9/8)
Alternate receiving yards
Cooper Kupp (LAR) 90+ receiving yards (+200)
The key thing to see here is that Kupp -- after playing fewer than 60% of the Rams' offensive snaps in his first game back from injury in Week 8 -- played almost every snap in Week 9. So it seems safe to expect a full workload against Miami.
Since he has played only four games, the model is considering both this year and last for Kupp. In that span he has a 29% target rate, 10th highest among wide receivers, and is averaging a median receiving yards line of 70.1, both factors the model likes to see. It makes the fair price +140.
Anytime touchdown
Puka Nacua (LAR) 1-plus touchdowns (+140)
As I mentioned with Kupp above, Nacua played fewer than 60% of the Rams offensive snaps in Week 8 after returning from injury. The difference here is that he was ejected from the game in Week 9 so we don't know what his playing time was going to be. We're going to work under the assumption he was on a similar plan to Kupp and was going to increase his reps last week. And if we do that, Nacua looks like a real value: I make him -127 to score.
That's in part because of the playing time I mentioned above and in part because of Nacua's generally strong receiving numbers (again, dating to last season) that includes the sixth-highest yards per route run (2.7) in that span. It also likes the type of receiver Nacua is: the touchdown model dislikes players who run a ton of deep fades and go routes (which could signal they are mostly a clear-out decoy receiver) and Nacua is decidedly not that.
Running back receiving props
Kareem Hunt under 1.5 receptions (+100)
We haven't had success with these so far this season, but we did last season and I'm sticking with the same theory. The idea here is that running backs catch passes at a much lower rate of dropbacks vs. man coverage (8%) compared to zone coverage (15%), and the hope (and what I found previously in backtesting) is that wasn't fully baked into reception unders.
The Broncos run man coverage 57% of the time, more than anywhere else, so that points us to Hunt's under.
QB interceptions
Drake Maye (NE) under 0.5 interceptions (+135)
The thesis here is pretty simple: The chance of an average starting quarterback throwing an interception is close to 50%. This season, starting quarterbacks have thrown at least one pick 51% of the time, and if we extend the time frame to include last season, the number is 49%. What I've found from modeling these props is that the distribution tends to tightly hug 50%, too.
There are factors here that lead to Maye being more likely than the average QB to throw a pick: he's a rookie, he has a high 2.5% interception rate thus far, he's playing a good pass defense in Chicago, and the Patriots are underdogs. But that's all why the model gives Maye a 53.8% chance (-116) to throw an interception, making +135 on the under a value.
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.