Tag: sabermetrics

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Tim Marchman takes the 200 position players and 200 pitchers with the highest career rWAR and converts wins above replacement to wins above average by subtracting two WAR for every 600 plate appearances or 200 innings pitched.

Starting Pitcher DL Projections

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Featured BtB contributor Jeff Zimmerman has posted the first part of his huge (in depth and possible impact) work on injury projections over at FanGraphs. "As the pitcher gets established in the league, his DL chances go down even though he is aging. Once he gets injured, his chance of going on the DL begin to go up at a decent clip." This is great stuff, and I can't wait to read the rest.

2010 Fans Scouting Report

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Tango requests your input for the 2010 Fans Scouting Report. Especially fans of the following teams: Arizona Diamondbacks Cleveland Indians Florida Marlins Houston Astros Washington Nationals

The Silliness of Pitching Wins (and Losses)

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In the wake of recent developments that reveal the irrationality of awarding Wins and Losses to pitchers, I felt it would be an interesting exercise to visualize the extent of the silliness. I attempt to express how W-L record fails as both a descriptive and a performance statistic for starting pitching by this stat, along with Win Probability Added (WPA) and Wins above Replacement (WAR) against a performance stat (xFIP) and a descriptive stat (ERA).

Here I go with that primer stuff again

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I got a new gig writing saber-primers once a week (along with other sabermetrically-inclined business). I'm starting simple, so that no one gets scared off by linear weights. Here, I talk about how context is everything in analyzing baseball.

Michael Lewis on Shane Battier

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I know this isn't baseball-related, but it certainly shows the influence and general usefulness of advanced statistics. Daryl Morey puts it perfectly when he says that the person who created the box score should be shot. It is definitely an example of statistics that go beyond what is seen in the game, as is the case with Shane Battier. It is definitely something that non-basketball fans can respect. Guys, the Houston Rockets are the new Oakland A's and Daryl Morey is the new Billy Beane.

Intro to Saber 101: Runs

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This article is a bit oversimplified, but I didn't want to talk too much in-depth about run estimators yet, and it's not as if people haven't already done it. I will go out there and simplify each of these run estimators eventually, but for the time being I thought it would nice to make sure everyone reading this stuff that's new to the scene that runs are the most important "currency" in the game. Feel free to drop by and comment however you'd like.

The New Fan Huddle Statistics Column

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Hate to advertise my own work here, but I've just started as the official saber guy for the new site Fan Huddle, and there I've got a biweekly column I'm going to call "Intro to Sabermetrics." In my column I'll be talking about the basics of sabermetrics, some history, some myth debunking, some player profiles, and trying to generally introduce this stuff to people who are interested. Come check it out when you get a chance and drop some feedback.

Using Expected Values in an NCAA Bracket with Upset Points

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Call it "Sabermetric Bracketology": I'm in an NCAA pool that awards bonus points for correctly picking underdogs. So, being the good little sabermetrician that I am, I applied expected values in attempt to game the system. It's worked well so far, too: I won my pool last year, and I'm out to a solid lead this year. The main link is to last year's introductory post, and here's this year's follow-up.

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