The number crunchers are headed for the NCAA offices.
What happens if you put the top basketball metric gurus in the same room and let them talk analytics? They’re about to find out in Indianapolis. Oh, how the formulas will fly when the NCAA hosts a meeting on Friday, Jan. 20 designed to speed the inclusion of more metrics in the selection process for the basketball tournament.From Jeff Sagarin and his golden mean, to Ken Pomeroy and his adjusted offensive efficiency, to Kevin Pauga and his KPI to Ben Alamar with ESPN’s BPI, they’ll all be there. A math geek’s dream team.
“It’ll be absolutely fascinating. I can’t imagine they’ve been together very much, if ever. There’ll be a lot of brain power in the room,” said Dan Gavitt, the NCAA senior vice president of basketball.
“I’m going to have to strap on in the meetings to stay up with all the calculus that’s going to be discussed, but I’m excited about it,” said Jim Schaus, the Ohio University athletic director who will be representing the Division I Men’s Basketball Committee.
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There’s a reason for this meeting of the math minds. The NABC, representing the coaches, has sent a message that it would like to look into the use of more advanced metrics in the selection and seeding process. An even more powerful microscope to go with the time-honored RPI. The NCAA listened and agreed. A group of coaches and committee members is now at work, and this get-together is for everyone to hear the possibilities for the future — from those who know.
“They’ve got some pretty strong thoughts on what a composite metric could look like and maybe should look like,” Gavitt said of the working group. “I also think they recognize their fallibility in advanced mathematical and analytical areas, so they feel that it’s important to engage experts in the field.”
So are advanced metrics coming to an NCAA tournament bracket near you? Yep, and soon. Gavitt can give several reasons why.
“I think it’s very important because it’s the way so many people engage with following sports these days, and in particular in this case, college basketball. In some ways, maybe young people are right at the top of that list.
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“You need to stay relevant in the age that you’re operating in. Certainly relevant today is embracing analytics and technology to the appropriate level.
“In an imperfect process, I think what the committee strives to get as perfect as possible is to have justification and rationale for their decisions. And the more that can be rooted in fact and in data, the more comfortable they can be with those decisions and the more justifiable they can be in explaining them.”
Or as Schaus said, “It’s one of the tools in the tool belt we look at when we try to differentiate teams."
“There’s many examples where when you look at team sheets and look at who they played and who they’ve beaten and where they played, there’s still not a lot of separation," he added. "I think it’s especially important when you look at teams that have very different backgrounds in terms of their schedule. Some teams have perhaps more ability and access to play higher ranked teams and to have their top 50 or top 100 wins than others. But when you look at those other things from a metrics standpoint, they kind of help level the playing field.”
So let the calculations begin. An aggregate metric could be an official part of the selection process as early as 2018.
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There will be some challenges in the process. One will be distilling all the systems down to something clear and defined. Lots of decimal points floating out there among these guys, who use them in various ways. As Gavitt said of Friday’s guest list, “It’s a good mixture of folks who value different things.
“They all have their top 50s, so when you’re talking about top 50 wins or top 100 wins or bad losses, you can use several different metrics right now. I think the thought here is, if we can get to a composite that is a combination of many of those and come up with one metric, then the opportunity for debate and criticism isn’t quite as strong.
“Not one of them’s perfect. And even a composite of all of them will still be imperfect. Hopefully it will be closer to perfect than what we currently have and I think that’s where the group feels it can be, and that’s why we think it’s so important to do this.”
Another hurdle is making sure metrics are a valuable resource, but not the end-all.
Schaus: “I think always the most critical things in terms of determining where teams are placed is always going to be who you play and who you beat and where you played those games.
“But I think when you go through the process you realize there’s still a lot of other information that’s valuable. We can look back at metrics over the last number of years, and see they have been successful in providing predictive information. But I think we understand, when you have a committee, there’s always going to be some subjectivity when you have a human element. That’s a whole lot better than trying to create some kind of a metric that all you do is plug in the numbers and then you kick out teams and there’s the tournament. I hope we never get to that, because sometimes there have to be judgments made that a computer just can’t make.”
Gavitt: “I go to a lot of games. I watch a ton of games. So observation is always going to be high on the list for me, too. I think the two work hand in hand. Data has a potential to verify the things that you’re seeing, or bring into question things that you’re seeing.
“Sport is imperfect and the game’s imperfect by its nature, and so things you couldn’t possibly measure by data and analytics will always be part of the season. This is a good example this year with so many key players missing large portions of games, a pretty significant coach [Mike Krzyzewski] missing games. How do you figure that with data? Some things can’t be.”
But a lot of things can.
“Strength in numbers,” Schaus called it. “We want to make sure we’ve taken our time to do it right.”
Which is why they’ll be having algorithms with lunch Friday at the NCAA.