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 are at the bottom of this story.
Defensive sacks
Tershawn Wharton (KC) under 0.5 sacks (-200)
My sack model prices Wharton's under at -307, but I think if it had the whole story, it would feel even stronger about this bet. When it comes to playing time, the starting point for the model is to simply look at a player's season averages. But in some cases, that's not adequate. In this case, Wharton's playing time has dipped in recent weeks: He played 69% of snaps through Week 12, but over the past three weeks -- with Charles Omenihu rejoining the rotation after recovering from a torn ACL -- Wharton has played only 49% of snaps.
So even at -307, I think there's a chance the model is overrating Wharton's sack probability.
Poona Ford (LAC) under 0.5 sacks (-450)
I'm enjoying the Ford breakout as much as anyone. In addition to his three sacks, Ford has an 11% pass rush win rate at defensive tackle, ninth best at the position. Even with his improved performance, however, Ford is still awfully unlikely to get a sack in any given game. The seventh-year player has never accrued more than three sacks in a season, and while it doesn't mean he can't exceed that, his historical sack production has been low thus far. Additionally, Ford plays on slightly more than half of the Chargers' defensive snaps and spends some time at nose tackle, from where a sack is particularly unlikely.
Plus, in this game he's going against Bo Nix, who has a tiny 3.8% sack rate. I price Ford's under at (gulp) -827.
See also:
Milton Williams (PHI) under 0.5 sacks (-250) (added 12/20)
Baron Browning (ARI) over 0.5 sacks (+325) (added 12/20)
Harold Landry III (TEN) over 0.5 sacks (+300) (added 12/20)
Arden Key (TEN) over 0.5 sacks (+235) (added 12/20)
Chase Young (NO) over 0.5 sacks (+375) (added 12/20)
Defensive tackles
Patrick Queen (PIT) under 8.5 tackles + assists (+100)
Our default position for an inside linebacker with an 8.5 combined tackle line is to lean under. 55% of off-ball linebackers who have played at least 90% of snaps have recorded eight or fewer tackles in a game this season. For our purposes, that estimate is a little high because it's not fully accounting for players who get hurt before they play 90% of snaps. It doesn't mean we automatically bet under 8.5 tackles + assists for linebackers, but it's our starting place and we need to be moved off it.
I don't see enough to move off that mark here. Though the Steelers are underdogs, Queen's tackling rates are a little below average for the position and Baltimore is middle of the pack in terms of NFL Next Gen Stats' pass rate over expectation. My model forecasts only seven combined tackles for Queen.
P.J. Locke (DEN) under 5.5 tackles + assists (-120)
Locke has low tackle rates for a safety as he generates a tackle on 7% of run plays and 8% of pass plays. Since those are relatively equal, he shouldn't be overly influenced by opponent passing rates or game script. He lines up 13 vertical yards from the line of scrimmage on average, per NFL Next Gen Stats, which isn't crazy deep but is on the high end for players who primarily play safety.
Against the Chargers on Thursday, my model forecasts 4.7 combined tackles for Locke.
See also:
Justin Strnad (DEN) over 5.5 tackles + assists (+110)
Minkah Fitzpatrick (PIT) under 6.5 tackles + assists (+100) (added 12/20)
C.J. Gardner Johnson (PHI) over 4.5 tackles + assists (-140) (added 12/20)
Ernest Jones IV (SEA) under 9.5 tackles + assists (-115) (added 12/20)
Defensive interceptions
Chidobe Awuzie (TEN) over 0.5 interceptions (+800) (added 12/20)
We're unlocking a new category! I've been working on a defensive interception model for the past few weeks, and it's time we take it out for a spin. The first major factor pushing us toward the over is obvious: Anthony Richardson's interception rate. The Colts' quarterback has thrown a pick on 3.9% of his dropbacks this year, highest among all QBR-qualified quarterbacks.
It's not the only reason why the model likes Awuzie, assince the start of last season Awuzie has a target rate of 14%, solidly below the 17% average for an outside corner. It may seem counterintuitive but a lower target rate is actually a positive sign for future picks because it's an indicator of a corner's skill. The edge we show here is small but it's there: the model prices this prop at +687.
See also:
Derek Stingley Jr. (HOU) under 0.5 interceptions (-700) (added 12/20)
Alternate receiving yards
DeVonta Smith (PHI) 50-plus receiving yards (-145)
Though Smith's 662 receiving yards this year don't look particularly impressive on the surface, that's in part because of missed time. On a per route basis, Smith has actually been slightly more efficient than he was last year, recording 2.2 yards per route run, which ranks 22nd among wide receivers with at least 225 routes. That he runs a below-average rate of vertical routes helps him hit the lower floor on this prop, too.
While Marshon Lattimore is a huge addition to the Commanders' secondary, Smith aligns as the wide left receiver -- opposite Lattimore -- only 25% of the time, so the other 75% of the time he could benefit from all of the targets Lattimore deters. My model strongly disagrees with the market here, pricing this prop at -303.
Anytime touchdowns
Nico Collins (HOU) 1-plus touchdowns (+145)
Early in the season when Collins' touchdown props were in this odds range, the model was all about him. We bet on him four times in the first five weeks, but then the model stayed away for a while when his odds grew shorter (and Collins got injured).
But we're back! Collins' numbers are still ridiculous, even as the Texans' offense has largely disappointed this year. He's being targeted on 30% of his routes (fifth most among wide receivers with at least 225 routes run) and has recorded 3.3 yards per route run (third).
Collins manages to run a very high rate of vertical routes (48%) without running a high amount of gos and deep fades -- meaning he's running a relatively high rate of deep overs, corners and posts -- which the model likes to see. I price him at -105 to score against the Chiefs.
See also:
Puka Nacua (LAR) 1-plus touchdowns (-105)
Alternate total
Detroit Lions-Chicago Bears under 45.5 (+120)
One factor that FPI+ -- our translation of ESPN's Football Power Index to the betting market -- finds drives lower totals is a severe mismatch in quarterback ability, because the team with the better quarterback is likely to get out to a lead and slow down its offensive play. Certainly, this game features such a mismatch between Jared Goff and the incredible Lions offense and Caleb Williams and the scuffling Bears offense. Plus, the Lions and Bears rank fourth and 13th in EPA allowed per play on defense.
That might be overrating Detroit's defense given all its injuries, but I also don't want to overreact to the Lions giving up 48 points to the Bills. Playing the Bears is like a different sport. FPI+ makes the under here +102.
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.