DadBodFootball Week 8 NFL Picks Against the Spread, Totals, and Implied Totals
DadBodFootball Week 8 NFL Picks Against the Spread, Totals, and Implied Totals
Idiot Sandwich - Ingredients: Two Slices of Bread, Butter, Me...
What are you… An Idiot Sandwich! That’s me this week after recommending everyone bet the Vikings -3 on the road against the Rams. Though the model had been adjusted for the return of Cooper Kupp and Puka Nacua - the model clearly hadn’t been adjusted enough.
The model saw this as a delta of -8.3 - which meant that the Rams should have been closer to 10 point underdogs than the 3 points offered by Vegas. Clearly a 30 to 20 win was never something that I or the model saw coming, but on a short week, flying across the country after an emotional loss to the Lions was too much for the Vikings to overcome.
Speaking of the Lions - teams are 0-5 the week after playing the Lions… I’m still not sure how to include this in the model because the moment we do, it’ll reverse the curse. That said, I absolutely love these little micro-trends. My favorite from last year was that if you bet the Monday Night Football Underdog Money Line from Weeks 3 to 11, and rolled your winnings from your initial $50 bet in to the next week… you’d have something like $1.7M. Numbers are probably off (I think you’d end up with considerably more than $1.7M, but I went to public school and math was never my strong suit….)
Where do we go from here? Well, I’ll be honest, I did make adjustments both to the Rams for next week and to the Dolphins for this week. It may not be enough for the Dolphins, but it does show why relying on a current season’s data is problematic on either side. The Dolphins started much slower this year than they did last year, and with injuries to Tua (among other players), they are averaging nearly half of their point total from 2023… They’re now healthy - so… how can we adjust this to reflect accurate models on efficiency and performance data that isn’t accurate?
To be honest, I don’t have a great message for you other than caveat emptor… Buyer Beware. The aim of the model is NOT to make every bet or nail every prediction, so consider these types of bets where I, personally, disagree or want to add a note to the buyer (you all) that the model is flawed. I’m adding a new section to the 3-pack… the What The Model Got Wrong This Week section where I cover topics like the Dolphins this week (and the Commanders this week as well).
Chasing Zebras - Hometown Zeroes
In this week’s DBF Chasing Zebra segment, I’m going to run through every matchup where the home favorite failed to cover and identify if there are any common profiles that lend themselves to higher or lower than the 44% cover rate. This exercise will hopefully help me (and all of us) better identify matchups that are most favorable for home-team favorites.
In 2024,there are 65 total matchups where the home team is favored - with the home team failing to cover in 37 of those matchups - good for a 44% cover rate.
I broke these matchups out by Week (1-7), Spread, Over/Under, Type of Matchup (Divisional Game, Conference Game, Inter-Conference Game), and for shits and giggles, if the home team won or lost despite not covering.
First Thought. Are certain teams not able to cover spreads..
The teams least likely to cover despite being favored are…
Dolphins - 3 (0 Wins)
Falcons - 3 (1 Wins)
There are 9 teams that failed to cover 2 spreads in which they were favored at home.
Second Thought. Is there a common pattern around the amount of the spread
The average spread in 2024 is a hair over 4 points (4.125) - meaning the average team is favored by 4 points. I grouped the values here, but in general roughly half of spreads are below 4.5 points and roughly half are above 4.5.
My takeaway here is that games where the home team is favored by 5.5 or more points represent over 50% of the “Fails to Cover.”
Third Thought Do home team favorites fail to cover in low or high scoring games
We actually dug in to this in Week 3 where we tested the theory that it is hard for favorites to cover large spreads (> 6 points) with a low total (< 43.5 points - below NFL scoring averages). We know that in those matchups, the home team is covering less than 1/3 of the time while the road underdog is covering over 2/3s (71%).
Fourth Thought Are there particular types of games that fit the profile
One of my favorite deep dives from last season was the March Madness theorem - where we tested out if a lack of familiarity with play style and opponent led to divergent outcomes. Why “March Madness”? Because you have a tournament where teams play opponents they have little to no familiarity with coming out of a heavy conference slate of games.
As a reminder, teams play 6 divisional games, 6 conference games, and 5 inter-conference games in their 17 game season. Here is a breakdown of types of matchups where the home favorite failed to cover
Despite making up only 29% of total NFL games, Inter-Conference games represented nearly 43% of matchups where the home favorite failed to cover. More importantly, they failed to cover at nearly double the rate of Divisional matchups.
TL;DR - What’s the move
Bet the underdog to cover if the spread is > 5.5 points
Bet the underdog to cover if the total is below 43.5 points AND the spread is > 5.
Bet the underdog to cover if the home team is favored AND it’s an inter-conference (AFC vs. NFC) matchup.
Spreads, Totals
The UNDER carried 9 of 15 matchups last week - this week, Vegas reduced points, but most of this is due to Jayden Daniels and Andy Dalton not playing as both of those game totals dropped by 3 points Monday to Friday.
Implied Totals
For those new to implied totals (or wondering what the heck I’m talking about) - an Implied Total is the expected points for ONE team in a matchup (with a TOTAL being both teams).
DBF Data points - Interpreting Implied Totals: In the DBF Tracker below, I include the Implied Total and delta to two other important data points
Average Points Scored: Informs how many points a team scores on average against a neutral opponent
DBF Points Expected: The Model’s output for expected points including adjustments for opponent defense, weather, home/road performance, injuries
This allows us to calculate the DOUBLE DELTA - how far off both average points and DBF Expected Points an implied total is. The more negative or positive, the more… theoretically… likely it is to be OVER or UNDER.
Winning Quadrants - Do Teams Win And How?
This is a mainstay of the weekly post - visit Week 10 of the 2023 season for a longer description Winning Quadrants graphic from Week 10. I’ll be adjusting to 2024 data right around Week 6.
Y-AXIS Net Points: The “higher” a team is on the Y Axis - the more team “Wins” by, and the “lower” - the more a team loses by.
X-AXIS Average Total Points (net 2023 NFL Scoring average of ~43.8 PPG) -The left-most teams participate in games with the lowest TOTAL points - the right-most teams participate in the highest scoring games. I netted (subtracted) season scoring average to show if they are above or below the average game.
How can you use this? Well - it’s an interesting way of aligning our “feel” about certain teams - the Dolphins tend to win and score a lot of points - and identify how they generally align against their spreads/totals.
Giants and Steelers both participate in games with totals more than 5 points below the 43.5 point NFL Scoring Average. Although the total is 36.5, I would stay away from the OVER (potentially avoid bets entirely) as neither of these teams is primed for an offensive breakout.
NFL Week 8 - 3 Pack
This new section is where I go a bit deeper on how the data and analytics in this post can be applied to a given week’s matchups. I wouldn’t say that these are picks - more how I’m feeling about a week’s set of lines, totals, and implied totals.
*** NOTE *** - I generally write these on Thursday/Friday before game day, so the lines may NOT be exactly as they are below, but the notes won’t change substantially.
Last Week Recap
HIT: Miami Dolphins Implied Total 20.25 - UNDER
MISS: Tampa Bay (+160) vs. Baltimore Ravens
HIT: Tampa Bay vs. Baltimore Ravens 49.5 TOTAL points - OVER
HIT: Cincinnati Bengals (-5.5) vs. Cleveland Browns
HIT: LA Chargers vs. Arizona Cardinals UNDER 44 points
New Orleans Saints vs. LA Chargers -7, UNDER 41 Points
The chargers are winning in games that average nearly 15 points less than the season long NFL scoring average of 44 points (29 PPG TOTAL). The Saints are averaging less than 17 PPG since Carr was injured - they have a banged up offensive line - and are missing at least 3 starters in offensive skill positions. Love the Chargers to win and for it to be a low scoring affair.
V NOTE: This is the ideal opportunity to bet the road underdog in a inter-conference matchup where the home team is favored by more than 5 points with a low total… and yet, I can’t bring myself to do it.
Green Bay Packers -4 vs. Jacksonville Jaguars;
The model expects this to be a shootout with the final score Green Bay 31 - Jacksonville 20. Jacksonville’s defense hasn’t shown up (despite their output against the Patriots anemic offense in London), and the model doesn’t feel like their offense can keep up against the Packers.
Tennessee Titans vs. Detroit Lions -11.5
The Titans are starting Mason Rudolph without D. Hopkins (traded) and potentially Calvin Ridley (injured). Their offense is going to have to try to get the run game going against a much improved Lions defense. The model doesn’t call it out, but I also like the Titans UNDER 16.5 points as the model isn’t heavily adjusted for Mason Rudolph (can he be worse than Levis? TBD) or the departure of Hopkins.
What the model (probably) got wrong this week!
Stay away from the Miami Dolphins vs. Arizona Cardinals game as I’m not confident in my ability to factor Tua’s return back in… even with Tua to start the season, they were nowhere near as efficient as 2023.
Personally, I don’t love the San Francisco 49ers vs. Dallas Cowboys matchup either. Cowboys are coming off a bye and the 49ers are a frisky team that is somehow last in their division. It just feels like there are too many other items at play for historical data to be relied upon here.
Model Performance
Reminder - the model GUIDANCE and not PICKS. I run every game through the model to identify opportunities where the underlying scoring and efficiency data does not align with the Vegas Spread and Total. I’ll continue to include WAR score here and a link to the post explaining why / how we can use it to determine if we’re hitting our most confident bets.
On Spreads, we went 8-6 with a WAR of 48.5. This means that not only did the model accurately predict a majority of spreads, but it correctly predicted the highest confidence/largest delta spreads too.
On Totals, we went 6-7-2 with a WAR of 21.2. This is a good reminder that while record is important, being able to accurately predict the most likely outcomes (and largest deviance outcomes) is best as we’re not betting every spread and total. A losing record is okay if we have a high WAR.