Understanding Sagarin Ratings in NCAA Basketball and Beyond

The Sagarin rating system, developed by sports statistician and mathematician Jeff Sagarin in the early 1980s, provides a data-driven approach to evaluating team strength and predicting game outcomes across various sports. This system has become a valuable tool for sports bettors looking to make informed decisions based on objective analysis rather than emotions. While initially focused on college sports, the Sagarin system has expanded to encompass professional leagues like the NFL, NBA, MLB, NHL, and even individual sports such as NASCAR and golf.

The Evolution of Sagarin Ratings

Jeff Sagarin, a graduate of MIT with a degree in mathematics, introduced his rating system, relying on two methods: Elo chess and BLUE (Best Linear Unbiased Estimator). The Sagarin ratings originally relied on two different methods: elo chess, based on the method created by Hungarian-American physicist Arpad Elo to rate chess players, and BLUE (an acronym for Best Linear Unbiased Estimator), which was based on game scores. However, Sagarin has since transitioned to a system based on three categories: Predictor, Golden Mean, and Recent. These categories are combined to determine an overall rating for each team.

Current Rating Categories

Predictor: Takes nothing else other than game scores into account.
Golden Mean: Another method that only takes the score into account. Sagarin defines it as a different method compared to Predictor, but since he doesn’t reveal his formulas, there is no way of knowing how Golden Mean and Predictor actually work.
Recent: In this method, recent games carry more weight than earlier games.

All three methods are then combined into the overall rating, which is the primary method used to rank the teams.

How Sagarin Ratings Work

The Sagarin rating system is based on cold hard numbers. The Sagarin rankings system is a computer-generated model. Two rating systems are offered, each of which gives each team a certain number of points. One system, “Elo chess,” is presumably based on the Elo rating system used internationally to rank chess players. This system uses only wins and losses with no reference to the victory margin. The other system, “Predictor,” takes victory margin into account. For that system, the difference in two teams’ rating scores is meant to predict the margin of victory for the stronger team at a neutral venue. For both systems teams gain higher ratings within the Sagarin system by winning games against stronger opponents, factoring in such things as home-venue advantage. For the Predictor system, margin of victory (or defeat) factors in also, but a law of diminishing returns is applied. At the beginning of a season, when only a few games have been played, a Bayesian network weighted by starting rankings is used as long as there are whole groups of teams that have not played one another, but once the graph is well-connected, the weights are no longer needed.

To use Sagarin ratings effectively, one must understand how to interpret and apply them to predict game outcomes. The core principle involves comparing the ratings of two teams, factoring in a home advantage bonus for the team playing at home.

Calculating Predicted Outcomes

To read these Sagarin ratings, the method is quite simple: You take the ratings for both teams and compare them, adding the home advantage bonus to the home team’s rating. Sagarin lists the home advantage points right under the rating column. The home advantage bonus changes over the course of the season.

Determine the Ratings: Obtain the Sagarin ratings for both teams involved in the game.
Apply Home Advantage: Add the designated home advantage bonus to the rating of the home team. This bonus varies depending on the sport and the time of the season.
Calculate the Difference: Subtract the visiting team's rating from the adjusted home team's rating. The result is the predicted point differential, favoring the team with the higher rating.

Home Advantage Bonus

The home advantage bonus varies from sport to sport, and varies as the season goes on. The home advantage bonus changes over the course of the season. For college basketball, Sagarin adds 4 points, while for college football, the home advantage is 3.

NFL: Add three points (or 2.18 for 2022) to the home team
NBA: Add 3.21 points to the home team
NHL: Add 0.15 points to the home team
NCAAF: Add 1.77 points to the home team
NCAAB: Add 3.15 points to the home team

Examples Across Different Sports

Let's examine how the Sagarin system can be applied to various sports:

NFL

Imagine the Buffalo Bills carry a 27.01 overall rating, and they visit the Miami Dolphins, with a 21.52 rating, the Bills are 3.31 points better. Why? Because 27.01 minus 23.70 (21.52 + 2.18 for home turf) equals 3.31.

NBA

For the NBA Sagarin rankings, take the Brooklyn Nets at 91.68 hosting the Golden State Warriors at 92.96. Normally, Golden State should be favored, but if we add the 3.21 home court points for Brooklyn, the Nets edge Golden State by 1.93.

Read also: Crafting Your NCAA Profile

NHL

If the Vegas Golden Knights, with a 4.42 overall rating, visit the New York Rangers at 4.11, who should be favored via the NHL rankings? If you answered Vegas, you’d be right. Sagarin is spotting just 0.15 to home NHL teams so the Rangers 4.26 (4.11 + 0.15) is still short of Vegas’s 4.42 rating.

College Football (NCAAF)

Say Ohio State (OSU) (with a 94.14 rating) takes on Michigan (with a 93.72 rating) in Michigan. You will then add 1.77 points to Michigan to give them 95.49. As such, they should be favored over OSU, based on Sagarin’s NCAAF rating.

College Basketball (NCAAB)

So when UCLA with an 89.06 overall rating hosts Baylor with 87.44, UCLA’s margin becomes 4.77. UCLA, as the home team, gets an additional 3.15 points. Thus, their 89.06 rating moves up to 92.21. If you deduct Baylor’s 87.44 from that, you get 4.77. That’s how you “calculate” Sagarin’s college basketball rankings.

Application to Individual Sports: Golf

When we look at the application of Sagarin, one thing stands out; it is used for team sports. But you can use it for individual sports, like golf. One of the most popular sports is golf. Sagarin’s rankings in golf are also posted on his site. And just like the principles with the other sports, you calculate “advantages” by pitting one golfer’s score against the other. Sagarin’s rankings in golf are also posted on his site. One important note though is that the lower the golfer’s score, the better. It lends itself to golf’s system of scoring based on how few strokes a player needs. A player like Calum Scott with a 67.02 rating is higher ranked than someone like Luke Potter with a 68.21 rating.

Strengths and Weaknesses of the Sagarin System

The Sagarin system is good for novice and experienced bettors alike, as it takes the emotion out of sports betting and backstops it with math. The Sagarin betting system has many advantages. New bettors, or those looking to use a system without emotional biases, can find benefits in using it. Mathematical models are usually more reliable than depending on intuition alone. However, as with most models, there are limitations to this system, so bettors must not rely entirely upon it. As such, Sagarin ratings may serve a better purpose as a complement to other betting strategies, rather than a conclusive device.

Pros

Objectivity: The system relies on data and mathematical calculations, removing emotional biases from predictions.
Accessibility: The Sagarin ratings are free to use and also relatively simple to understand. All it takes is a single subtraction to predict the outcome of a game.
Multiple Rating Methods: There are also four different rating methods to choose from, allowing the bettor to pick whichever one they find the most reliable.
Proven Success: The system’s success rate is 75 percent, and 53 on the point spread bets. The Sagarin system has an average success of 75% in predicting the winner, and around 53% against the spread. Even though it’s not perfect, the system can correctly point out the winner in 3 out of 4 matches, while also having a positive win rate in covering the spread. Overall, it is a helpful tool for bettors.
Long-Standing Popularity: The Sagarin system has been around for decades, and remains fairly popular because of its accuracy.

Cons

Failure to Account for Injuries: Now that we have mentioned injuries, this is the key weakness of Sagarin. It makes no allowances for players going down before or during a game. Because the system is based on cold hard numbers, star player injuries before the game have no influence. If a team loses its star player before an important matchup, sportsbooks will respond to it by aggressively shifting the lines. The Sagarin prediction, meanwhile, will remain the same, leaving the bettor in a tough spot.
The Human Factor: Another factor that comes into play when assessing two teams is the human factor. If we refer back to an NCAA college basketball example, a team playing for a tournament birth - March Madness or NCAA tournament - has a lot to play for as opposed to a team that has qualified or is out of contention come game time. When using the Sagarin ratings for betting, remember to factor in other important things. If a team is still trying to secure a spot in the NCAA National Championship, then it will naturally try harder than a team with nothing to play for. As much as prediction systems are extremely helpful in betting, the human factor must be taken into consideration as well.
Undisclosed Formula: Sagarin has never revealed his formula, which can make bettors uneasy about how the ratings are calculated.

Because the system is based on cold hard numbers, star player injuries before the game have no influence. It makes no allowances for players going down before or during a game.

Sagarin’s Impact and Legacy

Sagarin's ratings are particularly relevant in the world of American college football and basketball, where, with hundreds of teams in NCAA Division I competition, there is no way a team can play against more than a small fraction of its competitors. In addition, sports rating systems are generally of great interest to gamblers. His rankings, published weekly in USA Today, are part of the complicated formula that will be used to determine the pairing in the Fiesta Bowl.

From 1998 to 2014, the Bowl Championship Series (BCS) Committee used the Sagarin ratings to determine the BCS Bowl participants.

End of an Era: Discontinuation of College Basketball Ratings in USA Today

Sagarin College Basketball ratings were discontinued in 2023 after USA Today ended its partnership with statistician Jeff Sagarin, halting the official publication of his NCAA basketball rankings that had been a staple since 1985. This marked the end of a nearly four-decade run providing computer-generated power rankings used for team evaluation, tournament prediction, and betting insights. In early 2023, USA Today ceased publishing Sagarin’s college basketball ratings as part of broader editorial changes.

The Rise of NET Rankings

While Sagarin pioneered computerized rankings, modern alternatives offer greater accessibility and alignment with tournament selection criteria. The NCAA Evaluation Tool (NET) is now the official ranking system used by the NCAA.

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