Tag Archives: sabermetrics

The top 30 Baseball broadcasters according to Moneyball fans

The sabermetrics (a.k.a. Moneyball) website, Fangraphs put together an offseason poll. In it they asked the geeky baseball fans to rate their hometown announcers, with a particular emphasis on sabermetric insight.

Then put it all together using a geeky formula to determine the top 30 Baseball broadcasters:

 

1. Los Angeles Dodgers (Home) – Vin Scully

2. New York Mets – Gary Cohen, Ron Darling, and Keith Hernandez

3. San Francisco Giants – Duane Kuiper and Mike Krukow

4. Houston Astros – Bill Brown and Jim Deshaies

5. Boston Red Sox – Don Orsillo and Jerry Remy

6. Chicago Cubs – Len Kasper and Bob Brenly

7. Milwaukee Brewers – Brian Anderson and Bill Schroeder

8. Detroit Tigers – Mario Impemba and Rod Allen

9. Oakland Athletics – Glen Kuiper and Ray Fosse

10. Tampa Bay Rays – Dewayne Staats and Brian Anderson
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Advanced Moneyball statistics for the 2012 Baseball season – WAR, FIP, and OPS

Moneyball (the movie) introduced the basic concept of advanced statistical analysis to a mainstream audience. Now that we’re talking about advanced stats (short-handed as sabermetrics, thanks to Bill James of the Society for American Baseball Research) and great sites like Baseball Prospectus and FanGraphs, let’s take a closer look.

 

OPS (On-Base Plus Slugging)

This is an easy-to-understand offensive metric that provides a huge advance beyond the “basic” stats of RBIs, batting average and home runs. OPS is simply on-base percentage plus slugging percentage (total bases divided by at-bats). It’s essentially a way to look at how a player contributes both in terms of getting on base and hitting for power.

2011 major league OPS leaders: Jose Bautista, Blue Jays (1.056); Miguel Cabrera, Tigers (1.033); NL MVP Ryan Braun, Brewers (.994); Matt Kemp, Dodgers (.986).

 

WAR: Wins Above Replacement

WAR, wins above replacement, is about as close to a “What does this player really mean to my team?” catchall valuation as we’re going to get. Its definition is straightforward: How many more wins does a player add above a replacement-level player?

Baseball-Reference’s key to WAR: 8+ WAR is an MVP candidate, 5+ WAR is All-Star Level, 2+ WAR is a solid starter, 0-2 WAR is a bench player (a 24th/25th man on the roster), while anything below 0 is replacement level.

According to FanGraphs, Jacoby Ellsbury led the majors with an otherworldly WAR of 9.4 in 2011. Kemp followed at 8.7, with Bautista behind him at 8.3 and Braun at 7.8. On the other end of the spectrum, Raul Ibanez registered a minus-1.3 WAR (probably one reason why he’s looking for work right now). On the mound, Halladay led all pitchers with an 8.2 WAR. Verlander had an impressive 7.0 WAR and NL Cy Young winner Clayton Kershaw was 6.8.

 

FIP: Fielding Independent Pitching

We’re all comfortable with ERA as a basic pitching statistic. But ERA gives us only the average of earned runs per nine innings. It’s simple and straightforward. Low ERA is good. Simple. But what if there was a way to factor out all the things that the pitcher can’t control?

Turns out some really smart guys devised FIP, a formula that includes the things pitchers can control — home runs, walks, hit by pitch and strikeouts — and eliminates everything else (hits, errors, quality of fielders, etc.). FIP does what it says: It looks at pitching independent of fielding and other variables that impact a pitcher’s performance.

FIP is an excellent way to predict a pitcher’s future performance.

Let’s take a look at some notable pitchers to see how their ERA and FIP looked in 2011: Roy Halladay (Phillies): 2.35 ERA, 2.20 FIP; Clayton Kershaw (Dodgers): 2.28 ERA, 2.47 FIP; Justin Verlander (Tigers): 2.40 ERA, 2.99 FIP.

All three had great years, but you’ll see that except for Halladay, all of them had higher FIP than ERA. Does that mean that a regression is in order?

You should look for pitchers with a higher FIP/ERA differential because that’s where the pitching values can be found. An example would be Toronto starter Brandon Morrow. His ERA was a not-great 4.72 but his FIP was a respectable 3.64. The 1.08 ranked as the third-highest FIP/ERA differential in the majors.

via ESPN Women – contains four more saberstats: wOBA, VORP, BABIP, UZR.

A real Moneyball story – the reinvention of pitcher Brandon McCarthy

SEVEN PITCHES. That’s how long it took for the verdict to come in. On April 5, in the first inning of his first start in an A’s uniform, Brandon McCarthy went groundout, groundout, groundout. It was a one-inning sabermetric masterpiece. For the game, he lasted eight innings — the second-longest start of his career — and threw just 89 pitches.

McCarthy’s filthy stuff was no laughing matter. “He’s not trying to strike you out,” says Hunter, who had long dominated the lanky pitcher — until last season. “He’s trying to get a ground ball. He’s keeping guys off balance, and he’s hitting his spots. He’s learned how to pitch.” (“The first time I got him out last year,” says McCarthy, “I was like, ‘Oh my god, I really did something!’ That just wasn’t possible before.”) A’s manager Bob Melvin says McCarthy’s new pitching approach reminds him of Greg Maddux, the 300-game winner and surefire Hall of Famer. Says Melvin: “He takes great pride in being able to throw the ball where he wants.” And when he wants.

He learned about FIP, or fielding independent pitching, a statistical aggregate that combines what a pitcher can control (homers, walks, strikeouts), ignores what he can’t (luck, defense) and is a truer barometer than ERA. He also learned about BABIP, or batting average on balls in play, a stat that indicates whether a pitcher has been especially lucky (under .300) or unlucky (over .300). He learned about WAR, or wins above replacement, the all-inclusive, apples-to-apples metric that tells how valuable a player is to his team. He learned about ground ball rates, strikeout-to-walk ratios and more.

via Saviormetrics РESPN The Magazine