In recent weeks, fans have asked for ESPN to publish its college Football Power Index (FPI) formula. Although there have been multiple explainers of FPI (like this one), we are more than willing to open up the black box and provide insight into the process.
As you will see below, FPI is not a simple equation -- such as X + Y – Z = FPI -- or even a single regression, where we could list all of the variables and coefficients in the model. There are a number of inputs that interact with one another to produce each team’s FPI rating and season projections. Add in a complex opponent adjustment and the fact that FPI is built off play-by-play data for every FBS game and you can see how this is not the simplest formula to share.
That being said, in the interest of transparency, below is everything you need to know about college FPI.
What is college FPI?
FPI is a predictive rating system designed to measure team strength and project performance going forward. The ultimate goal of FPI is not to rank teams 1 through 128; rather, it is to correctly predict games and season outcomes. If Vegas ever published the power rankings it uses to set its lines, they would likely look quite a lot like FPI.
Correctly predicting game outcomes can’t be done by evaluating teams’ records because some teams are stronger than their records (lots of close losses), and others have favorable schedules, which are reflected in the game- and season-level projections.
It is important to note what FPI is not -- FPI is not a playoff predictor, and it is not designed to identify the four teams most deserving of making the College Football Playoff. ESPN has other metrics, including Strength of Record, that can be used to identify the most deserving teams.
What goes into FPI?
Each team’s FPI rating is composed of a predicted offensive, defensive and special teams component. These ratings represent the number of points each unit is expected to contribute to its net scoring margin on a neutral field against an average FBS opponent.
"It is important to note that prior seasons' information never completely disappears, because it has been proven to help with prediction accuracy even at the end of a season."
In the preseason, these components are made up entirely of data from past seasons, such as returning starters, past performance, recruiting rankings and coaching tenure (more on preseason component below). That information allows FPI to make predictions (and make determinations on the strength of a team’s opponents) beginning in Week 1, and then it declines in weight as the season progresses. It is important to note that prior seasons’ information never completely disappears, because it has been proven to help with prediction accuracy even at the end of a season. Vegas similarly includes priors when setting its lines.
Once the season is underway, the main piece of information powering these offensive, defensive and special teams predictions is past performance from that season’s games, in terms of expected points added per game. Expected points added is the backbone of most of ESPN’s analytical metrics, including FPI, Total QBR and team efficiencies. Expected points added per game takes into account yards, turnovers, red zone efficiency and more to determine how many points each unit is contributing to its scoring margin. For example, if a team wins by an average of 10 points per game, maybe plus-7 of that is offense, plus-4 is defense and minus-1 is special teams. Because expected points added is built on play-by-play data, it’s fair to say that FPI looks at every play of every game in the season.
Expected points added on offense, defense and special teams are individually adjusted for each game based on the strength of the opposing unit faced and where the game is played. Additionally, FPI applies a capping of sorts to each of these components to minimize effects of blowout games and improve prediction accuracy. As we learn more about the true ability of each team, FPI retroactively readjusts each game within the season using the team's latest predicted components.
In conjunction with the opponent adjustment, FPI uses a Bayesian regression to update each team’s offense, defense and special team components, which combine to produce the rating. This is an iterative process that is constantly updating and improving itself after every game of the season.
What goes into the preseason ratings?
As noted, there are four components to the preseason rating: prior performance, returning starters, recruiting rankings and coaching tenure.
--Prior performance is built off the expected points added framework. The most recent year’s performance is by far the most important piece of information powering preseason FPI, but three more years are added to measure consistency and account for outliers in performance. The most recent year counts almost twice as much as the three years before it.
--Returning starters on offense and defense, with special consideration given to starting or transfer quarterbacks with starting experience, is the second piece of information powering preseason FPI. Because starters interact with other inputs, it’s not as simple as saying an extra returning starter is worth one point. Nonetheless, a starting quarterback is worth about 3.3 points per game to a team returning an average offense (all else equal), and a transfer quarterback is given half the weight of a starter. For more on the addition of transfers, click here.
--FPI uses four recruiting services -- ESPN, Rivals, Scouts and Phil Steele -- to measure the talent on a team’s roster and add an additional piece of information about which teams are on the rise. The addition of recruiting has been a controversial piece of FPI, but it’s worth noting that it is a very minor component that helps with prediction accuracy. If recruiting were very significant to the ratings, Baylor and TCU would not have ranked second and third, respectively, in 2015’s preseason FPI.
--Coaching tenure is primarily a way to capture the addition of a new head coach. With all else equal, a team’s predictive offensive, defensive and special teams ratings will regress slightly to the mean with the addition of a new coach.
"If preseason FPI had been used with no update to predict every game of the 2014 season, the FPI favorite would have won 71 percent of FBS-versus-FBS games (Vegas closing line was 74 percent accurate)."
Preseason FPI debuted in 2014, and you can read more about how it performed in this recap. In short, if preseason FPI had been used with no update to predict every game of the 2014 season, the FPI favorite would have won 71 percent of FBS versus FBS games (Vegas closing line was 74 percent accurate).
FPI’s game and season predictions
FPI’s 1-through-128 rankings are fun to debate, but the ultimate goal is to correctly handicap games. FPI’s game predictions begin with each team’s FPI and then add information on game site, number of days of rest, distance traveled and game type (bowl game, conference championship game, regular season or non-FBS).
For example, an additional 5½ days of rest more than your opponent is worth one point per game (all else equal), and every additional 1,000 miles traveled more than your opponent costs you a point.
Over the last 10 seasons, the FPI favorite has won 75 percent of FBS-versus-FBS games, which is a comparable percentage to the Vegas closing line. If you want to follow along with how FPI performs throughout the season, feel free to go to the prediction tracker website. It’s important to note that in the other 25 percent of the games, FPI wasn’t “wrong”: The results of analytics such as FPI are not black-and-white -- they give us likelihoods of outcomes, not certainties.
Each team’s schedule is simulated 10,000 times to produce season-level outcomes such as each team’s chance to win its conference, enter bowls undefeated and make a bowl game.
In the season projections, the importance of a team’s schedule and path to a conference championship cannot be stressed enough; two teams with the same FPI can have drastically different projections, given their schedules. Even when those teams are in the same conference, their chances to win that conference can differ significantly given their divisions and competition within those divisions.
FPI and all of ESPN’s other metrics are a result of an objective, data-driven process. For more background on the process of creating these metrics, please read this Q&A with the developers of our NFL version of the Football Power Index. Full FPI rankings are available at ESPN.com/fpi, and each team’s game projections are available by clicking on that team from the FPI page.