|03-09-2008, 06:17 PM||#1|
Join Date: Jun 2004
Royals’ Bannister unafraid to do the math
Very nice and interesting story from yahoo on Brian Bannister.
Royals’ Bannister unafraid to do the math
By Jeff Passan, Yahoo! Sports Mar 8, 2:48 pm EST
SURPRISE, Ariz. – The revolution is happening, of all places, in the Kansas City Royals dugout.
The sabermetric community, baseball’s cottage industry of thinkers and rapscallions, has been waiting 30 years for a player like Brian Bannister to come along. He understands them. He thinks like they think. He doesn’t look at baseball as a simple game, just bat and ball or pitcher against hitter, primal to the core.
“I joke about it, but it’s almost like I’m watching the game from the Matrix,” Bannister said. “You’re not seeing what everybody else sees. You’re seeing the numbers that create it.”
It starts with one believer, and Bannister, a 27-year-old right-handed pitcher, believes that statistics are going to make him a better major-league pitcher. Bannister is the first big-league starter to so publicly embrace sabermetrics – the advanced study of baseball data that draws conclusions big and small – and its practitioners, in turn, are adopting him.
This is rather fortuitous, because Bannister is the type of player the sabermetric community tends to frown upon, the one with seemingly middling stuff, a terrible strikeout rate and a flyball tendency. To them, Bannister is the pitcher you don’t want on your staff.
And yet he’s exactly the kind of person you do, the one who’s self-aware enough to realize that he can’t get by on just an 89-mph fastball and needs something supplementary to make him into the pitcher he wants to be. Bannister, a noted amateur photographer, sees pitching as an art, and for much of the 2007 season, he was Escher, the same incongruous scene playing again and again.
Bannister finished 12-9 with a 3.87 earned-run average, and that was after his two final starts kicked up the ERA nearly a half-point. Otherwise, in his rookie season, Bannister would have finished among the top five in the American League with a record well above .500 in spite of playing for the moribund Royals.
To explain Bannister’s success in spite of his inability to overpower hitters is the crux of the scouts vs. stats debate that has raged for years but took root with the arrival of “Moneyball” five years ago. Scouts attribute Bannister’s success to intangibles – wiliness, toughness and other -nesses – as well as the ability to keep hitters off-balance with his slow curveball.
Statistical analysts? Well, they just think Bannister was lucky.
Nearly 10 years ago, a man named Voros McCracken postulated that pitchers had little to do with batted balls dropping for hits. He called his numbers DIPS, defensive-independent pitching statistics, and the offshoot was: There tends to be so much variation year to year of batting average on balls in play (BABIP) that the only way to explain the difference is randomness.
DIPS was revolutionary. Bill James, the godfather of baseball analysis, confirmed its veracity. McCracken got a job with the Red Sox. And BABIP, all of a sudden, became another indicator of a pitcher’s likely future, depending on whether it was over or under the average, which is about .300.
Last year, Bannister’s BABIP was .264, among the best in the game.
“It’s tough because I’m a student of it, and all last year I was well aware I was among the league leaders in it,” Bannister said. “But what do you do? Just because you’re continuing to get outs, do you say, ‘Oh, this shouldn’t be happening’?
“I realize very well that I could regress to the mean.”
Translation: Far more of those batted balls could find the outfield grass instead of gloves.
Then again, his good fortune may continue. In a late January interview with Tim Dierkes that outlined much of his sabermetric leanings, Bannister theorized that he could keep his BABIP down if he got to two-strike counts more often. It was a brilliant hypothesis that melded the practical – hitters are taught to, and thus tend to, take more defensive swings with two strikes – with numerical data.
Analysts tested Bannister’s idea, and he was right: there is a difference, though not terribly significant. Still, Bannister’s interest prompted Mike Fast to run a detailed series of analyses on Bannister with Pitch f/x, the two-camera system that tracks a ball from the pitcher’s hand to the catcher’s glove and details its speed to the tenth of a mile per hour and movement to the inch.
If anything convinces pitchers to become converts, as on-base percentage has done with a generation of hitters, it will be Pitch f/x. Its uses are manifold, and when Bannister learned about it in the middle of last season and figured out how to download and sort the data, it was as though he’d found religion.
“I find Pitch f/x to be more useful than video,” Bannister said, “because you’re actually seeing what the pitches are doing late in the zone, and that’s what it’s all about. Everybody can throw a fastball, but if one guy’s explodes in the last 10 feet and the other’s goes dead straight, there’s a huge difference, even if they’re both throwing 95 mph. That’s where the magic lies: in tweaking your pitches in order to get the most out of your ability.”
In college at USC and in the low minor leagues with the Mets, Bannister was like every other kid who thought velocity would get him to the major leagues. He dialed up his fastball to 94 mph only to see it get smacked from line to line. Bannister needed to tweak his pitches.
He found that when he took 5 mph or so off his fastball, his natural arm action and the way the ball rotated off his fingers caused it to cut – moving away from lefties and in on righties. Sometimes, it darted as much as a foot.
The pitch explains one of Fast’s questions after his Pitch f/x study: Why did fly balls off the bats of right-handed hitters tend to lift toward right field? Perhaps it was random, but Bannister thinks his cutting action prevented them from pulling the ball.
He’s got all kinds of theories. Bannister would like to sit down with James, who lives about 30 miles down the road in Lawrence, Kan., or with McCracken, and ask them whether curveball pitchers tend to have lower BABIPs. He looks at the league leaders every year – Orlando Hernandez and Chris Young and A.J. Burnett and Barry Zito last year, Young and Josh Beckett and Pedro Martinez and Matt Cain the year before – and sees a wicked hook as the common thread.
“Numbers aren’t necessary for everybody,” Bannister said. “There’s pitchers in this league, and everyone knows who they are, who have such elite stuff that if they got in their own head too much, it might hurt their performance. A huge majority of guys, though, are a (No.) 2, 3, 4, 5 starter and need every advantage they can. You’re in the major leagues because you have major-league quality pitches, but you’re looking for that edge any way you can.”
Bannister got his first taste of sabermetric thinking from Mets pitching coach Rick Peterson, one of baseball’s most forward thinkers. Bannister remembers sitting in a room with Martinez and Tom Glavine, two of this generation’s greatest, and hearing Peterson break down batting averages in counts and situations.
From there, he started exploring more, reading books and perusing sabermetric websites, increasingly conscious that if he couldn’t be his father, Floyd, who once led the American League in strikeouts, he’d use any means to achieve like him.
“He’s in tune with all of it, and that’s a guy who knows he has to find every advantage he can to be as good as he can,” Royals manager Trey Hillman said. “And that’s impressive to me. When people talk about his stuff, they say it’s not great. That’s not true. It may not be overpowering, but he knows what to do with what he’s got, and that throws off the hitters’ timing and balance.”
On Friday, Bannister made his second start of the exhibition season and got clubbed. His ERA rose to 10.80. It didn’t bother him, as he’s trying to pace his arm so he’s as strong in September as April. What did vex him was the 1-2 pitch that Rockies outfielder Brad Hawpe hammered at least 425 feet.
“Guarantee I one upped ya,” said Kyle Davies, Bannister’s teammate, sitting a few lockers down.
“What do you mean?” Bannister said.
Davies: “I gave up two homers in my first inning.”
Bannister: “I gave up a pretty good one.”
Davies: “Yours was better. Combined, though, mine were longer.”
Bannister: “Eh, that’s all right. I only give up .8 per nine.”
Davies didn’t answer. What could he say? That he gives up 1.38 home runs every nine innings? A huge majority of major-league pitchers have no idea about their home run rates or what they mean. It’s simpler: Managers say to keep home runs down, pitchers try to comply.
For Bannister, that just doesn’t suffice. He wants to see which of his pitches get hit for home runs – the count, the situation, the speed, the break. He wants to know that in 0-2 counts, hitters are 3 for 53 against him in his major-league career, and, accordingly, he wants to figure out what pitches best get him to that count. He wants to increase his strikeout rate from 4.2 per nine innings – the sixth-lowest in the major leagues last year – to at least 5.5 and learn to do so with the same pitches he currently employs.
The first generation of sabermetrics – really, the first 25 years – served more as tools of retrograde analysis and, based on those numbers, future projection. Very little of it, however, translated to the field, because numbers aren’t playable.
Today’s data is. And so comes the revolution, one Bannister is happy to lead.
“I’m willing to be the guinea pig,” he said. “A lot of people would look at me from a scouting standpoint and go, ‘He doesn’t belong in the major leagues.’ I want people to never be able to question how much time and preparation I put into what I do.
“You can be the best pitcher in the world and break 10 bats in a row, and they can all go for hits. Or you can be the worst pitcher in the world, throw terrible pitches, and 10 guys in a row can pop out. It’s an amazing game.
“One thing sabermetrics and statistics have allowed me to do is relax. I know the odds. I know percentages. I know that three out of every 10 batted balls should go for hits, and I deal with it. It’s helped me be a better player.”
He sees it, in his own unique way, every day.