Pomeroy's numbers tell the story

The Nate Silver of college basketball isn’t perched at a coach’s elbow on Tobacco Road. He isn’t a cog on a huge analytics team in Bristol, Conn., feeding numbers to the anchors. Instead, he is a lone wolf, sitting in his basement office in Salt Lake City and single-handedly shaping the sport.

What makes meteorologist Ken Pomeroy motivated to be a basketball stats guru? “I’m really interested in the predictive side of things,” he says.

It is there that a former US government meteorologist and teacher named Ken Pomeroy hops onto his MacBook, culls through mounds of in-depth data on 347 Division I teams, swims in spreadsheets and computer code and makes mathematical sense out of the chaotic, unpredictable world of college hoops.

The world Pomeroy inhabits values points per possession over points per game. It’s a world that counts player efficiency rating as a far more valuable statistic than points, rebounds and assists and tries to adjust players’ numbers based on their teams’ pace of play to create something called “tempo-free stats.”

Pomeroy’s world has done nothing short of transform the way we understand the sport.

The field of basketball analytics was unheard of in the early 1990s, occupied a niche in the early 2000s, and now consumes entire departments of NBA teams and the minds of college coaches and basketball writers.

Just like the baseball sabermetricians who followed the path of Bill James and were made famous by Michael Lewis’ book “Moneyball,” basketball numbers gurus such as Pomeroy take pride in how their in-depth analyses of statistics often buck conventional wisdom.

For example, the rankings system of Pomeroy’s website KenPom.com — popular not just among college hoops enthusiasts but among coaches too — recently scoffed at Kansas State being ranked 11th in the country in the Associated Press poll. The Wildcats had only two losses, but Pomeroy had them ranked 47th. Why? K-State had struggled in wins against bad teams, winning by only three against Delaware and eight against UMKC, and it won a one-possession game at West Virginia that easily could have been a loss.

Sure enough, Kansas State dropped its next two games to stiff competition, Kansas and Iowa State, and dropped to 18th in the national rankings. This week, it’s back up to 10th.

While it was falling in the AP poll, Kansas State moved up more than 10 spots in Pomeroy’s ranking system — close losses against good teams. But he's still not a believer in the Wildcats; they are 40th in his rankings.

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Then there’s the case of the University of Pittsburgh, which recently climbed back into the AP poll for the first time since dropping three of four games in the first two weeks of the new year. The 20-5 Panthers are 16th in the AP poll this week, but Pomeroy has them ranked fifth in the country, six spots ahead of 20-4 Kansas, because most of Pitt’s losses have been close games to good teams, and many of its wins have been blowouts, such as a 28-point victory over Georgetown.

If the season plays out as Pomeroy expects, Pittsburgh will outperform most people’s expectations, Kansas State will underperform, and the national champion could be a team that hasn’t topped the AP poll all season: Florida, which has topped Pomeroy’s rankings nearly every day since mid-December. (Then again, the chaos of basketball can often throw wrenches into the order of math — as it did this past week, when Arkansas, then 62nd in Pomeroy's rankings, blew out Florida; when TCU, ranked 251st, and Oklahoma stunned Kansas; and when Indiana and Michigan were upset in Big Ten play.)

How dependable is his system? In 2008, before the NCAA tournament began, he calculated that eventual champion Kansas was the top team in the country and eventual runner-up Memphis was second-best. In 2010, eventual national champion Duke sat atop Pomeroy’s rankings much of the season.

Perhaps it’s instructive that it took someone from outside the college basketball industry to figure out how best to use numbers to predict a team’s likely performance. Pomeroy is trained as a meteorologist. The connection might seem tenuous at first: Where do cumulonimbus clouds and their accompanying thunderstorms intersect with Pythagorean strength of schedule and a supposedly bad team’s odds of beating a better one?

But look deeper. “I’m really interested in the predictive side of things,” Pomeroy told FOXSports.com. “I always wanted to develop a sports rating system. There’s crossover. I love making forecasts. Weather is the ultimate test of that. It can be unpredictable. You have to use your judgment. And everybody is affected by weather. I just have a passion for predicting things.”

What’s humbling about Pomeroy’s new career path — he quit meteorology six months ago to focus on his blog full-time — is that it means his world happens in a small sphere. Outside that sphere, nobody cares about what he does. While everyone wants to talk about the weather, only a select few want to debate why Kelly Olynyk’s offensive rating is so much better than Mason Plumlee’s. Explaining his career to buddies in his bowling or hockey leagues often draws blanks, while people such as Brad Stevens, the Butler coach who is the darling of basketball analytics fanatics, calls Pomeroy’s data irreplaceable.

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“Ken’s site is so helpful in analyzing data and trying to figure what teams’ trends are and how they perform usually,” Stevens told FOXSports.com. “But one of the things that’s scary about basketball is you just look at the numbers, and you don’t figure out what a team is capable of. You’re figuring out trends — the usual performance, but not what they’re capable of. You have to balance that with film.”

Pomeroy might be the standard-bearer for the in-depth number crunching in today’s college hoops. But he’s not the godfather of the field.

In the 1980s, when Bill James’ work in baseball was still on the fringe, a teenager named Dean Oliver, enamored with James’ work, was inspired to apply it to basketball. Oliver took exhaustive notes from games — where the ball went, when the ball was passed from one player to the next, when the other team got the ball and started a new possession — and tried to make sense of it all. It sounds elementary for today’s developed field, but Oliver’s eyes first opened when he comprehended that since teams alternate possessions, each team has equal opportunity to score — which makes the most important statistic not points scored or allowed but offensive and defensive efficiency.

It’s a measure of how far the game has come that Oliver has gone from a lonesome numbers cruncher to someone who has worked for the Denver Nuggets and now ESPN.

“We don’t have to throw a lot of clichés around anymore,” Oliver said. “It helps us understand how basketball works, why players aren’t just good but they’re good at one thing or another. If there is something that annoys me most, it is anointing someone who scores a lot as a star.”

A great scorer such as Allen Iverson is good, but far better is a player like LeBron James, who scores efficiently, hands out assists and makes the game easier for his teammates.

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Iowa State uses Pomeroy as a consultant. Head coach Fred Hoiberg, who used to work in the Minnesota Timberwolves front office, calls Pomeroy “the best stat guy in the business.”

Hoiberg values things like Pomeroy’s shot-distribution charts, which show a player’s shooting percentage from different parts of the court. A guy might shoot 50 percent overall, but when you realize he’s only 4-for-32 outside the paint, you give him the outside shot. If you realize a player shoots only 11 percent on the left wing outside the paint but inside the free-throw line, you push him to that part of the court.

“It just shows a player’s tendencies,” Hoiberg said. “You go out there and play the percentages. Is it going to be exact science? No. But it shows where a guy is comfortable, and you take away a guy’s comfort zone.”

Pomeroy can tell you that a team that won a game by a point or two at home will lose more than 75 percent of the time when it plays the same team on the road later in the season. He can tell you that comparing the points per game of Indiana’s Cody Zeller to the points per game of Wisconsin’s Jared Berggren is like comparing apples and oranges, even though they play similar Big Ten schedules (Indiana has one of the fastest-paced offenses in the nation; Wisconsin has one of the slowest). Pomeroy is confident that his analysis will help you pick some of the upsets during March Madness.

What he won’t do is preach.

“One thing I’ve never wanted to do is convince somebody not open to this kind of stuff that it’ll make their life better,” Pomeroy said. “If you’re not into this, if you don’t think it will help your enjoyment of the game, that’s fine. It’s not for everybody. I’m content to carve out a niche for people who are into this stuff.”

Follow Reid Forgrave on Twitter or email him at ReidForgrave@gmail.com.