The Adjusted Pythagorean Record in the NFL Part II: Teams to Watch in 2019

Last week I reimagined one of my college football rating concepts, the Adjusted Pythagorean Record (APR), for professional football. At the end of the post, I offered a tease as to which teams might be poised for a rebound or due for some regression thanks their actual record differing significantly from their APR. I know you have been waiting with bated breath for that list of teams. But before we get to it, let’s look at the APR for the NFL as a whole in 2018. The following table ranks all 32 NFL teams according to their APR. Teams that qualified for the playoffs are highlighted.

At worst, the APR did a quality job of identifying the best professional football teams in 2018. While, the two Super Bowl participants ranked relatively low (eighth and ninth respectively) by this metric, the twelve teams that made the playoffs all ranked in the top-fifteen. While Bears fans may be trudging through a long offseason reliving the double-doink that ended their first playoff appearance since 2010, they can take solace in the fact that they topped the APR charts. Peruse and dissect the ratings at your leisure (and let me know how they over or under rate your favorite team).

As you may recall from last week, more than three quarters of teams since 2002 have finished with a final record within two games of their APR. I decided to use that as a somewhat arbitrary threshold when accessing teams that significantly over or under-perform. Those teams that over-perform by at least two games tend to come back to earth the following season and those teams that under-perform tend to bounce back the following season. In 2018, five teams either over or under-performed by at least two games and should be strongly considered for regression or progression when prospecting their final records in 2019. They are listed below.

The NFL season is very short when compared to the other professional sports leagues. A few clutch plays or lucky bounces can drastically alter a team’s record. With that in mind, I tabulated three statistics that are at least somewhat random and can help explain why these teams over or under-performed. They are:

1. Close Game Record: A team’s record in games decided by eight points or less. 
2. Turnover Margin: The number of turnovers a team committed subtracted from the number they forced (positive values are better). 
3. Non-Offensive Touchdown Net: The number of non-offensive touchdowns (defense or special teams) a team allowed subtracted from the number they scored (again positive is better). 

While these three statistics all involve a modicum of skill, they do not correlate well from year to year, but have a profound impact on a team’s record in a single season. The three teams that over-performed all did well in these metrics.

The Rams were triple crown contenders in these categories, posting a great record in close games, a fantastic turnover margin, and scoring five more non-offensive touchdowns than they allowed. Houston did not have a great close game record, but they had an even better turnover margin than the Rams and were nipping at their heels in non-offensive touchdown net. Miami was spectacular in close games (as they were for the totality of the Adam Gase regime). If you look closely at their final record, you will notice they did not win a single game by more than eight points. Now for the other side of the coin.

Denver was not exceptionally bad in close games, but their turnover margin and general poor coaching likely cost them a few victories. Minnesota’s Achilles heel was their propensity to allow teams to score against them in unconventional ways with Kirk Cousins contributing three pick sixes to the cause.

If you are an over/under win total enthusiast like myself, keep an eye on these five teams when placing your bets over the summer. Recent history indicates the trio of the Rams, Texans, and Dolphins might be in for a regression while the Broncos and Vikings could see their records improve in 2019.

The Adjusted Pythagorean Record in the NFL Part I

A few years ago (seven to be exact) I developed an adjustment to the Pythagorean Record for college football. Instead of using points scored and allowed, the new statistic, dubbed the Adjusted Pythagorean Record (or APR), used only a team’s offensive touchdowns scored and offensive touchdowns allowed. Touchdowns scored by the defense or special teams, field goals, safeties, extra points, and two-point conversions were ignored. The thinking was that the best teams were those that scored and prevented touchdowns at the best rates. While defensive scores, clutch place-kicking, and crafty two-point conversion plays can dramatically alter the result of any single football game, scoring touchdowns with your offense and preventing your opponent from doing the same is a better long-term predictor of success. I have compiled in-conference college football APR data back to 2005 and over the past four offseasons have posted an APR breakdown of each FBS conference (hold your applause). I also wanted to eventually conduct an APR analysis of the NFL, and well, you are in luck. I have calculated APR data back to 1970 (the first year after the AFL and NFL merged) and will be making sporadic posts this summer using that data. This first post will examine the accuracy of the APR in the NFL and research what happens to teams that win significantly more or less than their APR would lead us to expect. Enjoy.

As stated previously, I have calculated APR data going back to 1970. However, in the interest of focusing this particular post on the modern NFL, the data reported here will only consist of APR data going back to 2002. Why 2002? Well, that was the last time the NFL expanded and realigned. The league added the Houston Texans in 2002 and went from two conferences with three unbalanced divisions in each to two conferences with four divisions of four teams apiece. While 2002 may not seem that long ago, it does give us a sample size of 17 seasons and 544 individual team seasons. And perhaps just as important, there has not been a major work stoppage so each of the 544 individual teams played a sixteen-game regular season so we don’t have to make any adjustments to their raw data. Also, it bears mentioning that APR includes only regular season games. Preseason (duh) and postseason games are not included.

Let’s use a 2018 team that finished with a final record that was very close to their APR as a starting point. In 2018, the Cincinnati Bengals finished 6-10 (and finally fired Marvin Lewis). Over the course of sixteen regular season games, the Bengals scored 40 offensive touchdowns and allowed 49. Their APR was calculated as such.

(40^2.37) / ((40^2.37) + (49^2.37)) = 0.382023 

Their expected winning percentage was just north of 38%. This value is then multiplied by sixteen and yields 6.11 expected wins. As a shorthand, we say their APR was 6.11.

Obviously, NFL teams cannot win one tenth of a game (although they can win a half as ties are counted in my calculations as half a win), so Cincinnati finished .11 games short of where we would expect based on their APR which is pretty darn close.

How often do teams finish with records that closely match their APR? Pretty often.

About 44% of teams finish within one game of their APR and over three quarters of teams finish within two games of their APR. We’ll call that quarter of teams that finish more than two games above or below their APR outliers. And what tends to happen to those outliers the next year? Let’s start by looking at the teams that finish two games or more ahead of their APR. Since 2002 (not including 2018 since those teams have not had a next year yet), 60 teams finished with a record that was at least two games better than their APR. Collectively, here is how they performed the next season.

A little more than 63% of these teams declined the following season with the average team declining by just over two games. And for the teams that did decline, the downturn was typically steep. Nearly 60% of the teams in this sample declined by at least two games. So what about teams at the other end of the spectrum? Since 2002 (and once again ignoring 2018 for the moment), 63 teams finished with a record that was at least two games worse than their APR. Collectively they did this the following season.

Nearly three quarters of these teams improved the next season, with the average team improving by over two and a half games! Two thirds of the teams improved by at least two wins the following season.

So the APR looks like a solid measure of team strength in the NFL, and perhaps more importantly, it might be able to identify a few teams poised for regression or progression the next season. Which teams exceeded or failed to meet their APR in 2018? Ah, you’ll have to wait until next week to find out. See you then. 😀

2018 Adjusted Pythagorean Record: Sun Belt

Last week we looked at how Sun Belt teams fared in terms of yards per play. This week, we turn our attention to how the season played out in terms of the Adjusted Pythagorean Record, or APR. For an in-depth look at APR, click here. If you didn’t feel like clicking, here is the Reader’s Digest version. APR looks at how well a team scores and prevents touchdowns. Non-offensive touchdowns, field goals, extra points, and safeties are excluded. The ratio of offensive touchdowns to touchdowns allowed is converted into a winning percentage. Pretty simple actually.

Once again, here are the 2018 Sun Belt standings.

And here are the APR standings with conference rank in offensive touchdowns, touchdowns allowed, and APR in parentheses. This includes conference games only with the championship game excluded.

Finally, Sun Belt teams are sorted by the difference between their actual number of wins and their expected number of wins according to APR.

I use a game and a half as a line of demarcation to determine whether or not a team significantly over or under-performed relative to their APR. By that standard, Troy significantly over-performed and both Georgia State and Texas State under-performed. Troy was a little lucky to finish 7-1 in conference play as they were 2-0 in one-score games. Georgia State was 0-1 in one-score games and they finished next to last in turnover margin in Sun Belt play (-6). However, the main reason their APR is significantly better than their actual record is their performance in their lone conference win. In their Sun Belt opener, the Panthers rolled Louisiana-Monroe 46-14. In their other seven conference games (all losses of course), the Panthers permitted their opponents an average of five offensive touchdowns per game! Meanwhile, Texas State also under-performed relative to their YPP numbers and we discussed some reasons for that last week, so peruse the back catalog of posts to catch up.

Head Coaching Turnover in the Sun Belt
The Sun Belt will welcome four new head coaches in 2019. Appalachian State, Coastal Carolina, Texas State, and Troy will all be taking the field without the men who led them in 2018. Some of those teams lost coaches thanks to their great success (Appalachian State and Troy), others thanks to their lack of success (Texas State), and others thanks to retirement (Coastal Carolina). That head coaching turnover is tied for the most the Sun Belt has experienced since the end of the 2005 season. However, the turnover in the Sun Belt is even more significant when you consider the other year the league welcomed four new coaches was 2018. Even if you disregard Coastal Carolina’s coaching change entering the 2018 season (when Joe Moglia returned from a one-year sabbatical to deal with health issues), that still means seven of the league’s ten teams have changed coaches in the past two seasons. Blake Anderson (Arkansas State) and Matt Viator (Louisiana-Monroe) are the resident deans of Sun Belt coaches as they enter their sixth and fourth year respectively. To give you an idea of just how much turnover there has been, take at look at the following table. It lists all the Sun Belt coaching changes since the end of the 2005 season (counted in the table as the beginning of the 2006 season) along with the reason for the change.

So what does this mean for the Sun Belt in 2019? It means the league is in transition. Appalachian State and Troy, two programs that have won at least a piece of the last three Sun Belt titles and finished a combined 41-7 in Sun Belt play since 2016, lost their head coaches. In addition, Coastal Carolina, a perennial FCS playoff participant will also be without their head coach as they enter their third season at the FBS level. If a lower-level team was to make a run at the Sun Belt title, this might be their best shot. The Sun Belt has been won by a (current) team other than Appalachian State, Arkansas State, Georgia Southern, or Troy just once since 2006 (Louisiana-Lafayette tied for the title in 2013 with Arkansas State).

Well, that does it for our conference recaps. Unfortunately, we still have about twelve weeks before the season gets started in earnest (only eleven until some sweet Week Zero action). In the intervening weeks, I'll be making another trip to Vegas with a requisite betting recap post. In addition, I will also have some intermittent posts on the NFL. More specifically, the Adjusted Pythagorean Record (APR) in the NFL. Be on the lookout for that this summer. And, as always, thanks for reading.