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Stanford vs. Kansas State: Odds, betting lines, and computer predictions

A look at the data from Las Vegas and several computer predictors to preview Stanford’s season opener against Kansas State on Friday.

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NCAA Football: Central Florida at Stanford Kyle Terada-USA TODAY Sports

The beginning of the college football season is always about uncertainty. Sure, there are a few things that we can predict with relative confidence. For instance, Christian McCaffrey will provide many, many yards for Stanford in every possible way. Rushing, receiving, returning — even passing. While history and trends can give thoughtful insight, there are frequently enough unknowns that make each season opening game day a compelling watch.

Despite that, the professional prognosticators don’t view Friday night’s contest at Stanford Stadium to be much more than a formality for the Cardinal. Everyone has David Shaw’s men by more than two touchdowns.


The sports books opened Kansas State at Stanford with the Cardinal favored by 16.5 points and has sense moved to Stanford by 14.5. The change in the line reflects that early betters have laid their money down on Kansas State to cover the spread.

Vegas lines and odds aren't meant to be predictive. They are made to entice betting in equal portions on each side of the spread. However, combining the line and the over/under usually ends up close to some computer models. After all, Vegas is very good at this and it is a lot of fun.

Combining the line and the over/under, the Vegas combo has Stanford winning 31-17.


Some computer rankings are designed to provide a built-in predictive element by comparing the ratings of two teams.

Some of the best ratings out there come from Football Outsiders. The most famous is Jeff Sagarin's for USA Today, previously used in the BCS computer rankings. I've included a couple others from around the web as well.


F/+ is a combination of Bill Connelly's S&P+ and Brian Fremeau's FEI ratings. The ratings are usually pretty solid in factoring all the many variables involved in ranking college football teams that have a relatively low level of common opponents.

F/+ does not predict a final score, but does give an expected margin. F/+ likes Stanford by 17.2.

Football Outsiders site only lists the ratings in order, but Connelly posts predictions on his SB Nation site Football Study Hall.

Bill's S&P+ picks predicts Stanford by 18.5 points (winning 40-22) and gives Stanford a win probablity of 85.7%. Connelly picks Stanford to cover the -14.5 Vegas spread.

During the 2015 College Football season Bill's S&P+ picks were 150-27 (84.7%) when yielding a win probability in the range of 80-89%.


Stanford is ranked #6 with a rating of 90.28.

Kansas State is ranked #53 with a rating of 73.62.

Sagarin’s formula currently values home field advantage as worth 2.61 points. So subtracting the difference between the ratings and then adding 2.61 in favor of the home team, Stanford, Sagarin has Stanford favored by 19.5 points (19.27).


Billingsley's ranking was also previously used by the BCS. With the BCS restriction to remove margin of victory no longer a consideration, Billingsley has created a version of his formula that accounts for margin of victory.

Stanford is ranked #9 with a rating of 102.742.

Kansas State is ranked #60 with a rating of 86.779.

The difference is 16 (rounded up from 15.963) points. Billingsley does not provide a home-field advantage factor, but lets apply the standard 3 points and say Billingsley has Stanford by 19 points.


Donchess boils down the ratings directly into digestible scores and probabilities, no math required.

Donchess predicts a Stanford win 38-20 and gives Stanford a win probability of 88.5%.


There are a lot of computer ratings that aren’t packaged with a predictive ability. There are also a ton of computer ratings, period. Kenneth Massey, whose ratings were also part of the old BCS computer formula, hosts on his site a composite ranking of 106 computer ratings across the internet.

In that composite, Stanford ranks #5 and Kansas State ranks #58.