NCAA Explores Use of Analytics in Bracket-Building has partnered with LexisNexis to bring you this content.

Copyright 2017 Spokane Spokesman-Review

Spokesman Review (Spokane, WA)


The NCAA basketball tournament used a seeding process for the first time in 1978.

Four teams in each region received automatic bids as conference winners that season, and they were seeded based on their conference's win-loss record in the five previous tournaments.

The tournament has evolved since, searching for methods to create the best possible bracket.

And, thankfully, it's not done yet.

On Friday, the NCAA will host basketball analytics experts to discuss including more metrics in the tournament selection process - something the National Association of Basketball Coaches had wisely requested.

Major League Baseball increasingly has relied on analytics in recent years. College basketball coaches can't get enough of number-crunching when scouting opponents. The NCAA selection committee should also use the available data - and there's more of it than ever - in the most intelligent way.

The goal Friday at the exploratory meeting is simple, said Kevin Pauga, who runs the increasingly popular metrics system on

"How can we make things better?" said Pauga, who also serves as assistant athletic director at Michigan State. "Let's help get more information that the committee can look at but look at it in an efficient way. Really, what can come out of this meeting is there are a lot of people that have all sorts of levels of understanding from all sorts of backgrounds and can provide knowledge (to decide) is a composite metric the way to go."

An aggregate metric could be a part of the selection process as early as next season, according to an article on The NCAA will tap into the minds of metrics gurus like Pauga, Ken Pomeroy and Jeff Sagarin along with ESPN's Ben Alamar and bracket predictor Jerry Palm.

The harshest criticism of the current model is typically aimed at the reliance on the Ratings Percentage Index. The RPI measures aspects like winning percentage, opponents' winning percentage and the winning percentage of opponents' opponents to assess teams and rank them into weighted categories, such as top 50 and top 100.

This system isn't nuanced enough given the availability of formulas that go deeper.

Many of the more complex systems weigh aspects like opponents' records and place more value on road victories than the RPI does, for example. Combining them for a composite to help guide the 10-person selection committee will help make the process more clear-cut.

"There's a pretty significant difference between beating 49 at home and beating 51 on the road," Pauga said. "The win over 49 at home is in that top 50. And that win over 51 on the road is not."

Palm said he hopes the NCAA does not pick just one system but uses a composite with transparent formulas. Each system can produce an outlier, which is another reason why it's important for the NCAA to go with a composite model.

Credit the NCAA for adapting and letting the selection process evolve.

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January 23, 2017


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