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Sports Info Solutions Analyzes Team Over/Unders

Eric on Li : 6/10/2024 9:45 am
SIS has a lot of good proprietary data which they've used to run simulations of the season. their methodology looks pretty similar to vegas' to me, though they obviously have no need to balance a book. this model's record last year looks pretty good, though if these were real vegas lines I dont think I could bet the vegas (10.4), NO (10.7), and chicago (10.7) unders fast enough.

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We’ve reached prediction season for the NFL. A big part of dissecting the upcoming season is analyzing the schedule and predicting which teams will overperform or underperform their expectations.

Expectations these days come from the sportsbooks, especially through win totals. These markets have been posted and bettors have begun forming their stance on each individual team. The lines will move all offseason long, as more information and opinions will move the lines in one direction or another.

At SIS, we have created a pre-game prediction model to predict the spreads, totals, team totals, and moneylines of each game using a multitude of data points that we collect. We also constructed the model to be able to run for the entire season, allowing us to run simulations on the season and create win total prices of our own. The model went 18-13-1 in over-under predictions on team’s preseason win totals last season.


Giants perform slightly better than vegas in their model at 7.1 but more interesting is their most underperforming team relative to vegas is Philly at 6.8 wins and almost 4 wins lower than the vegas o/u.

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Team DraftKings Win Total Model Projected Win Totals Difference (sorted from most overperforming teams to least)

Raiders 6.5 10.4 Over 3.9
Saints 7.5 10.7 3.2
Bears 8.5 10.7 2.2
Lions 10.5 12.3 1.8
Buccaneers 8.5 10.3 1.8
Browns 8.5 9.8 1.3
Packers 9.5 10.7 1.2
Seahawks 7.5 8.7 1.2
Jets 9.5 10.6 1.1
Patriots 4.5 5.5 1
Ravens 11.5 12.1 0.6
Bills 10.5 11.1 0.6
Giants 6.5 7.1 0.6
Cowboys 10.5 11.1 0.6
Rams 8.5 9 0.5
Cardinals 6.5 6.9 0.4
Bengals 10.5 10.9 0.4
Texans 9.5 9.4 Under -0.1
Panthers 5.5 5.2 -0.3
Dolphins 9.5 9 -0.5
Chiefs 11.5 10.9 -0.6
Broncos 5.5 4.7 -0.8
Steelers 8.5 7.4 -1.1
Jaguars 8.5 7.4 -1.1
Falcons 9.5 8.1 -1.4
Chargers 8.5 6.9 -1.6
49ers 11.5 9.8 -1.7
Colts 8.5 6.1 -2.4
Vikings 6.5 4 -2.5
Titans 6.5 4 -2.5
Commanders 6.5 3.2 -3.3
Eagles 10.5 6.8 -3.7


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Model Overview (How did we get these numbers?)

Our model utilizes 18 features that are a combination of game, team, and player level metrics.

Game level metrics include whether or not the game is in the postseason, weather predictions like wind speed and precipitation probability, and a home team indicator.

Some of the team level metrics include weighted points for and points against averages, both offensive and defensive weighted penalty yards, and some possession metrics in the form of snaps per game or drive. Each of these metrics is computed for the team’s past 7 games, with the most recent weighted more heavily.

We use a weighted 16-game average with our Total Points for the player metrics. We calculate the average Total Points for each skill (Passer, Rusher, Pass Rush, etc.) for every player per snap, and then aggregate the projected values for each game to the team level using each player’s projected snap counts for the game.

Then, we utilize Monte Carlo simulation to illustrate variance in player performance by simulating 1,000 games for each player. After each simulation, all of the metrics are incorporated into a Lasso regression model to predict the team’s point total. The distributions of the predictions are aggregated to an average and spread so that point estimates and alternate point estimates can be drawn from the distribution.

Now that there are lines for each game, we can simulate 1,000 regular seasons based on the moneyline output and take the average win total for each team.

Analyzing NFL Win Totals with the SIS Prediction Model - ( New Window )
Thanks for posting Eric,  
Section331 : 6/10/2024 10:22 am : link
interesting stuff, although, if you look at last year's results, SIS did little better than Vegas with their predictions. They had Carolina at over 7.5 wins!
RE: Thanks for posting Eric,  
Eric on Li : 6/10/2024 10:32 am : link
In comment 16533821 Section331 said:
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interesting stuff, although, if you look at last year's results, SIS did little better than Vegas with their predictions. They had Carolina at over 7.5 wins!


yeah just found a link to the model last year in august, they had nyg -.5 at 8 wins from vegas at 8.5.

functionally the rosters arent too different from each other though with the 3rd draft class, hopefully better OL (cant believe it until we see though), burns i think there's a better chance they exceed expectations than last year where everything went wrong.

i think daboll's o/u is 8. anything above that and he will get year 4 but anything under and i think there becomes loud talk for belichick/vrabel. im still relatively bullish on daboll i think.
Breaking Down The NFC Over-Unders, Team-By-Team - ( New Window )
RE: RE: Thanks for posting Eric,  
Section331 : 6/10/2024 1:25 pm : link
In comment 16533829 Eric on Li said:
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In comment 16533821 Section331 said:


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interesting stuff, although, if you look at last year's results, SIS did little better than Vegas with their predictions. They had Carolina at over 7.5 wins!



yeah just found a link to the model last year in august, they had nyg -.5 at 8 wins from vegas at 8.5.

functionally the rosters arent too different from each other though with the 3rd draft class, hopefully better OL (cant believe it until we see though), burns i think there's a better chance they exceed expectations than last year where everything went wrong.

i think daboll's o/u is 8. anything above that and he will get year 4 but anything under and i think there becomes loud talk for belichick/vrabel. im still relatively bullish on daboll i think. Breaking Down The NFC Over-Unders, Team-By-Team - ( New Window )


That sounds about right, although I can see him getting year 4 at 7 wins. I think 6 or less he's on shaky ground, but I'd be surprised if they win 6 or less.
Last year’s Giants defense relied on a flawed defensive strategy.  
Ivan15 : 6/10/2024 3:31 pm : link
You can’t rely on the opportunity to blitz on 3rd down, unless you can stop the run on first and second downs. Wink didn’t even try to do that with his 2-man front.
That Eagles prediction is interesting  
cosmicj : 6/11/2024 9:37 am : link
I wonder if they are overweight recent games which would emphasize the Eagles late 2023 swoon.
RE: That Eagles prediction is interesting  
Eric on Li : 6/11/2024 9:39 am : link
In comment 16534429 cosmicj said:
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I wonder if they are overweight recent games which would emphasize the Eagles late 2023 swoon.


they do, though i also count about 9 guys starting in their depth chart on ourlads right now that are new this year.

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Some of the team level metrics include weighted points for and points against averages, both offensive and defensive weighted penalty yards, and some possession metrics in the form of snaps per game or drive. Each of these metrics is computed for the team’s past 7 games, with the most recent weighted more heavily.

Might have some meaning  
HBart : 6/11/2024 3:44 pm : link
For some teams. Giants aren't one of them. There's little if anything to learn from last years stats (to the extent there even are any for many key players).
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