How does sagarin work

For instance, when Miami hosted Florida State on Jan. We saw something similar for the Arizona State at Utah game on the same day. The game ended in an push.

In a relatively small but growing sample size, our experience is that the KenPom rankings are more accurate in these situations. We are currently tracking mostly power-conference games from the season in which Sagarin and KenPom differ on the predicted outcome.

In brief, the results were as follows:. As a percentage …. When the actual point spread fell somewhere in between the KenPom and Sagarin predictions, KenPom was more accurate on 35 of 62 games. However, when the actual point spread was either higher or lower than both the KenPom and Sagarin predictions, the actual spread was closer to the final outcome than both metrics on 35 of 64 games.

As mentioned, we are still looking at a small sample size, yet the advantage is significant and we can draw a couple of tentative conclusions :. One limitation of KenPom and Sagarin is that they do not, generally, account for injuries. When a star player goes down, the calculations for his team are not amended. KenPom and Sagarin both assume that the team taking the floor tomorrow will be the same as the team that took the floor last week and last month. While sportsbooks are very good at staying up-to-date with injury news and factoring it into their odds, they miss things from time to time, and they will not immediately have empirical evidence which they can use to adjust the spread.

They, like bettors, will basically have to guess at how the loss of a star player will impact his team, and they are not always great at this. In the first game of the SEC conference schedule, No. The Aggies had been hit hard by the injury bug and had recently played some closer-than-expected games. Finally starting to get a little healthier, they were small 1. At least 16 or so hours before the game, word came down that leading scorer DJ Hogg would not suit up, along with third-leading scorer Admon Gilder.

Another notable example comes from the Notre Dame team. Again, the Irish covered with ease, winning straight-up. Sportsbooks had no idea what the team was going to look like without its star and wound up overreacting. There was good reason to think the Irish would be significantly worse since Colson was not only their leading scorer by a wide margin but also their leading rebounder and only real interior presence. However, there was also reason to think the Irish would be okay because Mike Brey teams are pretty much always ok.

But if you pay attention to injury news and use the metrics available, you may be able to reap the rewards. For complete transparency, below is the list of results we tracked when comparing the accuracy of KenPom and Sagarin versus the actual point-spread at a certain online sportsbook and the final results. Curious about other basketball ranking systems? Check out the rest of our guides on sports betting strategy ; we cover the best sports betting strategies that apply to everything oddsmakers dish out lines on!

Sascha was a hockey player in his youth, a lawyer in his capricious mids, and has now been an assigning editor, writer, and lead oddsmaker for SBD for over five years.

He covers everything you can possibly put odds on, but specializes in football, baseball, hockey, and basketball. We noticed you're from free and hanseatic city of hamburg where legal online sports betting is not currently available.

Enjoy risk-free action while you wait at SBD Play. Updated March 24th, Published February 4, The KenPom and Sagarin rankings are computer-based ratings systems which provide predictions for college basketball games. They are highly influential amongst bettors, and the actual spreads used by sportsbooks tend to factor in their predictions. Often KenPom and Sagarin agree on what is likely to happen in a game, but they also diverge significantly on a semi-regular basis.

When there is a discrepancy and the actual point spread lies somewhere in between, bettors can find value in siding with the more accurate model. But which is it? Matchup KP Spread Sag. Sagarin was more accurate than KenPom; the sportsbook was more accurate than both. KenPom was more accurate than Sagarin; the sportsbook was more accurate than both.

Baylor at Oklahoma Jan. KenPom was more accurate than Sagarin and the sportsbook; the sportsbook was more accurate than Sagarin. Georgia at Arkansas Jan. KenPom was more accurate than Sagarin. The sportsbook was more accurate than both. Tennessee at South Carolina Jan. Both were more accurate than the sportsbook. Pittsburgh at Clemson Jan. Sagarin was more accurate than KenPom. Kansas at Texas Jan. Lipscomb at Liberty Jan.

Sagarin was more accurate than KenPom and the sportsbook. The sportsbook was more accurate than KenPom. Ohio at No. Illinois Jan. North Carolina at Ga. Tech Jan. Virginia at NC St. NC St. Missouri St. KenPom was more accurate than Sagarin and the sportsbook. The sportsbook was more accurate than Sagarin. Marquette at Butler Jan. Indiana at Rutgers Jan. Providence at Seton Hall Jan. Providence covers. The sportsbook was also more accurate than KenPom.

West Virginia at Iowa St. Illinois at Minnesota Jan. UCLA at Wash. USC at Washington Jan. Iona at Marist Jan. Monroe at Coastal Carolina Jan. Miss at Fla. Int KenPom was more accurate Sagarin and the sportsbook. Temple at Houston Jan. KenPom rankings will predict that a lower-ranked team will win, depending on where the game is being played. When the KenPom was created in , it offered a new light for basketball bettors. These days, KenPom rankings set the point spread for reputable college basketball sites — or there and thereabouts, with predictions not deviating more than a point or two.

There is an exception to this rule when a significant injury or suspension is involved in the game. KenPom basketball rankings are still very much in operation for bettors today. The Sagarin college football rankings and Sagarin basketball rankings provide very much the same thing as the KenPom ratings but use a different calculation.

The reason these two predictions systems are grouped together is that they are closely aligned in their estimations. But there are literally hundreds of college basketball games being played each year, which means bettors will always find outcomes to be significantly different at some point. When there is a significant gap between the KenPom and Sagarin prediction s, typically sportsbooks will side with KenPom, but there this is never absolute and it really depends on the day.

As we mentioned briefly before, the one limitation of the KenPom and Sagarin ranking systems is that they do not take into account injuries and emotional factors. Sportsbook providers are nearly always on top of keeping the odds up-to-date, however they sometimes miss the adjustment when injuries happen or how the loss of a star player will affect the markets. A bachelor of science degree in mathematics from MIT is all that's required to become a major driving force in the multibillion dollar Bowl Championship Series.

This graduate of the Massachusetts Institute of Technology has become one of the most well-known sports statisticians around. But his ranking methodology is botching his all-important slice of the BCS rankings pie. Even by his own admission, the BCS is using the wrong rating system. Try as we might, the so-called experts can't manage to pull back the curtain on how these rankings work.

Each week, we so-called experts struggle to make sense of what the computer rankings really mean, and we're even more useless when trying to predict what the varying electronic brains will spit out next week.

One reason this is so difficult is the jealousy with which the various computer ranking methodologies are guarded. Jeff Sagarin and his systems —yes, plural—are no different. Sagarin actually compiles two different sets of rankings for college football. From the beginning way back in , Sagarin has been part of the BCS equation. Of course, the selections after the following season weren't much better, as any Auburn or Utah fan will tell you.

So why do we constantly get rating controversies? Sagarin, and others like him, won't release his methodology to anyone , and the masses are simply left to trust he knows what he's doing. But does he? Even if we ignore the unknown method he uses, what can we infer from his results?