DadBodFootball Week 14 NFL Picks Against The Spread, Totals, and Implied Totals
Spreads, Totals, Implied Totals, and Updated Power Rankings to Inform Your Betting Habits
What more could you want from a Thursday night matchup - from a first half that lulled most of us to sleep, to a second half in which we saw the Lions nearly snatch defeat from the jaws of victory… This Lions team is frisky and reminds me of many teams that either make significant noise and rampage through the playoffs (Chiefs 2023, Rams 2021). Having home field advantage all but locked up is a significant advantage when you play in at Ford Field, and I have a hard time seeing another team playing at their level at this time.
Speaking of teams playing at their level, the Eagles may be the next best team in Football and I’ll continue to ride them (and the Chargers) as teams I love to bet on. Spreads, MLs, Totals… they’re very predictable and go about their business in a reliable manner.
At this point in the betting season, you have the third variable of “how much interest does Team B have in playing Team A” - some teams are already thinking about the beach in the offseason while others are beginning to scrap and claw for their playoff lives. Expect the unexpected - and I’d advise you to focus on your “horses” and not stretch bets this late in the season.
Chasing Zebras - “3/4 Season” Power Rankings
Sure - we’re not quite there, but it only feels right to publish the 3/4 Season edition of the Power Rankings. The Broncos, Buccaneers, and Dolphins represent the teams showing the most positive momentum since the halfway mark, while (to no one’s surprise) the 49ers are really starting to fall off.
DBF Score: This is what ultimately drives the ranking - it is a composite score of the teams relative efficiency on both offense and defense. The Ravens are a great example where their offense is carrying a spectacularly mediocre defense.
DBF Offense / Defense Rank: How a team compares to the entire league on both offense and defense. There’s a lot more that goes in to the weekly Spread/Total/Implied Total calculations, but this is a simple enough way to understand what offenses and defenses are over/under performing.
Points Scored Per Game: Simple - total points scored divided by number of games played
Projected Points Scored Per Game: This is where the model becomes part art and part science… it calculates a weekly total for each team relative to existing variables and historical performance (i.e. how the 14th ranked offense would perform across a season where the average - 16th ranked offense - puts up XXX points). You’ll note that the Dolphins are expected to rank much higher to end the season than they performed historically.
Points Allowed Per Game: Total points allowed divided by number of games played
Projected Points Allowed Per Game: Similar to Projected Points Scored Per Game - this is how the defense can be expected to perform for the rest of the season given historical trends and averages.
Spreads, Totals
Note: I model every matchup’s spread, total, and implied totals leveraging a data model rooted in historical (3+ seasons) worth of offensive and defensive scoring, team-specific efficiency (i.e. Red Zone TD %s), home and road performance, and variables like injuries to QBs, new head coaches, and Matt Patricia.
The only updates I generally make are to the variables - i.e. Davante Adams is unable to go this week. Lines will move throughout the week, so if the DELTA (the net difference between the data model’s predicted spread/total/implied total and the actual spread/total/implied total) is small, there’s a good chance that the guidance will go to neutral or to the other team as the week evolves.
Columns Explained
DBF Line - the model’s calculated line for the game
Real Line - the Vegas offered line for the game (usually within 0.5 points of most books)
DBF O/U - the model’s expected point total for the game
Real O/U - the Vegas offered line for the game (usually within 0.5 points of most books)
The DELTA - the net difference between the data model’s predicted spread/total/implied total and the actual spread/total/implied total provided by most betting sites. The higher the delta (in either direction) the more confident we are in the bet because, according to the data, the spread/total/implied total should be lower or higher than it is.
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.
We can use Thursday’s Lions vs. Packers matchup - where the model loved the OVER on the Lions Implied Total of 27.5 (Double Delta 6.5). This is 4.4 points below their per game scoring average (31.9) and 2.1 points below their expected points against the Packer’s defense (29.6). Add those together for… 6.5 Double Delta.
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 Ravens tend to win and score a lot of points - and identify how they generally align against their spreads/totals.
NFL Week 14 - 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.
Total Record (Since week 7)
19-7
This Week
Cincinnati Bengals -5.5 vs. Dallas Cowboys, Bengals Over 27.5
The Bengals come in to the week averaging 28 PPG on offense but putting up nearly 35 PPG against teams who rank in the bottom 16 on defense. The Cowboys net out at 30th of 32 teams and though they’ve fared better in recent weeks, they’ve not faced an offense quite like the Bengals. I also like the OVER 49.5 in the game but the question we don’t know the answer to is “Can the Cowboys keep up…”
Buffalo Bills -3.5 vs. Los Angeles Rams, UNDER 49.5, Bills Over 26.5
The Rams are a good team in a weak division, the Bills are a great team in a weak division… Home Underdogs are failing to cover (and win) at historic rates and this line feels low. Love the Bills - 3.5, like the UNDER, though I’m more tempted by the Bills OVER implied total of 26.5.
Jacksonville Jaguars vs. Tennessee Titans -3, Jaguars UNDER 18.5
The model struggles to take in to account when a team loses an underperforming starter and replaces them with a former under-performing starter now… serviceable backup? That said, It’s difficult to see how the Jaguars will score on the Titans OR stop them from scoring. The Titans are definitionally mediocre, but the Jags are so, so much worse (ranking 23 on offense and 31 on defense).
Contrarian From The Model Pick
The Browns find a way to cover +6.5 against the Steelers, my guess is the UNDER (43.5) also takes this game… It’s the AFC North afterall.
The Kansas City Chiefs beat the Chargers and cover the -4 point spread. The Chargers are most likely playing without Ladd McConkey on an offense already missing JK Dobbins. That’s too much “star power” to overcome against the consistent Chiefs.
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 10-6 with a WAR of 50.7. This isn’t a particularly impressive WAR - meaning that we missed some big swings and hit mostly little ones. I feel it’s positive by product of going 10-6 on spreads and not because we hit the biggest deltas.
On Totals, we went 7-5-2 with a WAR of 81.8. This is actually a much better performance than the spreads in that we hit the largest delta total predictions and missed the small ones.
On the season that brings us to…
Spreads - 99-76-8; WAR:1291.3 given we run this model and record for ALL matchups, the model is absolutely humming on spreads (in that it is correctly predicting what spreads are outliers relative to the data).
Totals - 91-79-9; WAR: 221.3; again, we’re seeing traction in that the model is nailing the large delta TOTALS and missing those that are close. When you count every game/pick in your record, it’s okay to be hovering around 54%. You want the higher deltas to be your wins.