top of page

NFL Betting: How to create your own NFL Power Ratings: Part 2

This article was originally published on Cold-Brewed Bets.

In our last issue discussing NFL betting, we talked about how to find a starting point for creating your own NFL power ratings by using the previous year's market rating of each team.

If you didn’t read that, you probably should - otherwise today’s issue isn’t going to make a whole lot of sense.

Okay, well, it actually might. But I still want you to go read it.

I’m going to preface this article by saying that most of what I share today is going to be subjective, compared to the data-driven, analytical breakdown we did in Part 1.

That means that there are no ‘rules’ about how to use what we’re going to talk about today. It’s much more going to come down to your individual perception.

The other important thing to understand is what I am going to break down below is just my process. I am in no way saying this way is the right way or is going to help you win millions of dollars.

When it comes to subjectivity, our own biases ultimately are going to come into play as well. We’re going to have views and opinions on certain teams based on what we watched on the field last year and during the offseason that affect how we rate them.

So in an attempt to try and minimize that bias as much as possible, we’re going to pull some hard data from the 2022 season, as well as projected data for 2023, to help counteract that a bit.

Lastly, I am not going to share with you my exact ratings for 2023, or how I adjusted each team because, 1) this is about creating your own, and 2) remember this is subjective - so you may see things differently than me.

What I will do is tell you what I consider when making my adjustments, and you can decide for yourself how - if at all - you want those factors to affect your own ratings.

We're going to consider 3 factors:

  • 2022 Pythagorean Win Expectations

  • Offseason Roster Moves

  • 2023 Season Win Totals

I’ll use all of this information to then adjust the numbers we found in Part 1, upgrading teams a certain number of points based on the factors below, and downgrading others.

But before we move on just a quick note on team ratings:

As a general rule of thumb, going into the season I will have all teams ranked between -7 and +7 - meaning that my highest-rated teams will be no more than 7 points better than an average team, and my worst teams will be no more than 7 points worse than an average team - with average teams being rated 0.

The reason for this is I find it really hard to say with any conviction that before any games have been played, the best team in the league would be more than 14 points better than the worst team on a neutral field.

So if you give yourself the parameters of -7 to +7, and that all teams will fall somewhere in there, it gives you a good boundary to help narrow down your ratings.

Alright, with that out of the way, let’s get into it…

NFL Betting: Pythagorean Win Expectations

The first place we’re going to start is by looking at all team's Pythagorean Win Expectations (PWE) from 2022.

PWE projects a team’s expected win total based off of point differential - aka the number of points they scored and the number of points they allowed.

Popularized in baseball betting, what PWE gives you is a good understanding of the strength of a team beyond their overall W-L record.

Were they lucky in one-score games?

Did they beat up on bad teams but struggle against good teams?

These are the types of questions PWE helps answer.

You probably saw the word Pythagorean and thought, “Oh god, I didn’t know there would be math…”

Don’t worry, I took care of the calculations for you. The table below shows each team's actual wins in 2022 vs the number of wins they were expected to have based on their point differential:

NFL Betting: Pythagorean Wins Expectation

Teams that under-performed against their win expectancy are shaded towards the green. Teams that over-performed against their win expectancy are shaded towards the red.

A few things stand out:

  • The team that everyone and their mother (except maybe their fans) thought was overrated based on their record was the Minnesota Vikings. They won a whopping 4.6 more games than they were expected to.

  • Both Super Bowl teams, KC and Philly, played pretty far above expectations as well, but still were expected to win the 4th and 3rd most games, respectively.

  • Despite their roller coaster at QB, San Francisco was the most successful team in living up to their win expectancy, and actually had the highest amount of expected wins of any team based on their performance.

So what do all these numbers tell us? And more importantly, what can they tell us when considering our 2023 ratings?

What I look at most when considering this data is which teams are candidates for a possible regression, either positive or negative.

Do I want to downgrade teams that over-performed their win expectation last season?

Do I want to upgrade teams that underperformed?

I don’t make changes based on this alone, but it’s helpful information to have, especially when you then start to consider roster turnover, and key players that teams either lost or signed in the off-season.

This information will also give you insight into how the market may be rating teams. The Vikings are an obvious example but a good one to highlight this point: They won 13 games last year but their projected win total in the market right now is just 8.5.

Roster Turnover

A more obvious piece of team assessments is going to be roster turnover for the upcoming season. This is also going to be the most subjective piece, because you have to ask yourself questions that don’t have obvious data points to back them up.

When I’m looking at roster changes from one year to the next, I’m looking at a few areas:

  • QB changes

  • Positional Groups

  • Head Coach

  • Rookies

Everyone is going to assess these differently, but here’s how I look at each of them…

QB Changes

No individual player means more to a point spread than the quarterback. Just consider the Packers/Chiefs game from the 2021 season…

On Tuesday before the game, the Packers were a 1-point favorite on the road vs KC. Then on Wednesday, Rodgers was ruled out with COVID and the point spread moved to KC -7.5 - a whopping 8.5 point difference from one player's inactivity.

Now, there are other factors involved in considering a starting QB value, such as who their backup is, the team they’re playing that week, etc.

So it’s not always going to be the same.

However, this highlights how much a QB is worth to a team's overall rating.

In my experience, the average drop-off from a starting QB to their backup is worth about 3 points on a team's rating.

So when considering off-season QB changes, start there. Because remember, while the NFL is a team game above all other sports, the perception of how good a team is going to be is based a lot on how good their QB is.

Positional Groups

Outside of QB, there is probably no other individual player worth more than half a point on a team's rating.

But, when you have multiple changes at one or more positional groups, that will impact a team's rating.

Did a team sign a bunch of skill position players or defensive backs?

Did they lose multiple starting linemen or pass rushers and not do a good job replacing them?

These are the types of changes during an offseason that will have a bigger impact on a team's rating than any one player alone - outside of a QB.

Head Coach

In my experience, no other single person has a bigger impact on a team's rating after the QB than the head coach.

A great head coach can elevate teams to the next level (think Mike Tomlin’s consistency year to year, or what Brian Daboll did for the Giants last year), and a bad coach can drag down a talented roster (like Todd Bowles or Kliff Kingsbury).

Coaches are involved in so many aspects of a team's success - from game plans during the week to high-impact decision-making moments during the game.

So when it comes to making adjustments for coaches, I look specifically at teams changing coaches, and coaches going from Year 1 to Year 2.

If a team has a first-year head coach, I will usually give them a little upgrade. My reasoning for this is that if a team had to hire a new head coach, it’s usually because they fired a terrible coach.

So even with a first-time head coach, chances are there’s going to be some improvement.

The other adjustment I’ll make is a coach going from Year 1 to Year 2, because by this point a coach will have likely shown you if they are either capable or if they suck.

So a team with a coach in their second year more often than not will either get a small bump up or down.


With rare exceptions, it’s almost impossible to discern the impact of rookies on a team before the season. So I really don’t consider individual rookies when doing pre-season ratings.

Where I will make a small adjustment up - possibly - is if a team addressed a position of need.

So if a team struggled on defense last year, and drafted multiple defensive players early on in the draft, or they needed offensive weapons, and took a bunch of skill position players, I may upgrade them.

Win Totals

The last thing I will look at when considering my pre-season rankings is current season win totals.

We talked a lot about this part of the process being more subjective than Part 1, however, current season win totals give you an idea of how professional bettors and bookmakers are ranking teams going into the current season.

Thus, this can give you something to compare your ratings to, in terms of where teams may fall.

According to one of the sharper offshore sportsbooks, here’s how they have teams rated going into the 2023 season, according to win totals:

NFL Betting: Market Win Projections

Column 2 is the current market win total for each team. Columns 3 and 4 show the price and where the market is leaning towards in terms of if they think the team will go over and under that win total.

So for example, right now the Chiefs are projected to win 11.5 games, -135 odds to the over - meaning bettors and bookmakers believe there's a stronger likelihood they will go over than under that number.

Conversely, the next team on the list, Cincinnati, has the same win total, but -145 odds to the under - meaning the market thinks it's more likely they will go under that number.

Teams at -115, the market doesn’t consider them any more likely to go over or under that number.

This is great information to consider because if you have a big discrepancy between where a team falls on your list, and where the market projects them to finish in terms of win totals, then you may want to consider adjusting them.

Checking Your Work

There are no right or wrong answers when it comes to creating your own power ratings. At the end of the day, what these are supposed to be is a reflection of how you view teams so you can find potential edges in the market, and make valuable bets.

The nature of your power ratings is that there are going to be some differences between your numbers and the market, and it’s up to you to decide if those differences give you a reason to make a bet.

However, what I do recommend doing is checking your work against available point spreads in the market, and see how closely your numbers match up against what sportsbooks have posted.

I’ll use two examples from my own ratings that I compared to the Week 1 point spreads we currently have available…

In the opening game of the 2023 season, the Detroit Lions (yes, the Detroit Lions in the opener…) are playing at the Kansas City Chiefs. In the market, the Chiefs are currently a 7-point favorite.

When I look at this matchup using my numbers, I make the Chiefs as an 8-point favorite.

So to me, at least at this point in the offseason, my number is close enough to the market number that this tells me I probably have a pretty good read on where these teams rank.

An example on the other end of the spectrum would be the Miami Dolphins at the LA Chargers. My rating for this game is 0, or more commonly called a pick ‘em - meaning I see no difference in how these teams are rated for this game.

However, when this number opened, it came out as the Chargers as a 3-point favorite, and even moved up to 3.5.

Now, at that point, I had to consider if either my rating for one or both of these teams was way off, OR, if I was confident enough in where I rated these teams that I should keep my rating and potentially make a bet.

I reviewed my process above, and came to the conclusion that I liked where I had these teams rated, and earmarked this game to potentially come back to and make a bet later.

However, at the time of writing this article, the point spread has moved down to the Chargers as only a 2.5-point favorite - meaning, that at least for the time being, bettors in the market seem to agree with my assessment that these two teams should be rated closer together.

I did this exercise with every game for Week 1, and used this information to ‘check my work’ on how my ratings compared to the market. It helped me find some adjustments to make to some teams, and it also helped me find some bets I may potentially make.

So there you have it - my entire process for creating my own set of NFL Power Ratings that I use to make point spreads for every game.

These numbers will change during the season as we actually get to see how good teams are, but at least starting out, these give me a general sense of how I see teams going into the season, and helps me decide where I may want to make some bets.

Hopefully, this process can help you do the same.


This article was originally published on Cold-Brewed Bets.

Jorden Pagel is a successful sports bettor, a life-changing Personal Fitness Trainer—Mikey can attest to that—and a terrific human being. Follow him on twitter, LinkedIn and SubStack.

PS - Heads up! If you were planning on subscribing to BBFF's All-Access Pass this season, the early bird discount ends on 6/1! Get yours here!

24 views0 comments


bottom of page