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Articles Tagged Stabilize 

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How long fielding stats take to stabilize.

A little more than a week ago, Jon Heyman of CBS sent out a tweet wondering why it was that Starling Marte and Bryce Harper had the same WAR. Heyman was quoting Baseball-Reference's version of WAR, which at that moment in time showed Marte and Harper tied at 1.7 wins. Harper had clearly been the superior hitter, but drilling down, it turned out that the fielding metric used by Baseball-Reference loved Marte's defense enough (and thought Harper's was average enough) to call them equals.

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When pitching stats stabilize.

Of course. He's a pitcher.

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July 24, 2012 5:00 am

Baseball Therapy: It Happens Every May

6

Russell A. Carleton

When we say that certain stats "stabilize" after a certain point, we don't mean that they'll stay stable.

It happens every May. Someone on your favorite team is having an uncharacteristically good (or bad) year. This year, David Wright got his groove back, while his former teammate Jose Reyes lost his way. Edwin Encarnacion and Carlos Ruiz started hitting home runs for no apparent reason. For a while, Albert Pujols (!) was stuck in a very public home run drought. Early in the season, analysts and fans have learned to (properly) dismiss these runs as small sample size flukes. They’re something to keep an eye on, but... he'll be back to normal soon.

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Russell reruns the numbers to determine when hitter stats stabilize.

Who said sabermetrics hasn't gone mainstream? We've now reached the point where even mainstream analysts are yelling "small sample size!" at one another. There's always been some understanding that a player who goes 4-for-5 in a game is not really an .800 hitter, but now, people are being more explicit in talking about sample size. I consider that a victory. Hooray for sabermetrics!

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July 16, 2012 5:00 am

Resident Fantasy Genius: To Platoon or Not to Platoon?

3

Derek Carty

Derek lists the factors you need to consider before deciding to platoon two players on your fantasy team.

On Thursday, reader “jimcal” asked me in the comments section of my article to give my thoughts on platooning players in fantasy baseball. While platooning is a bit of a complicated subject, I’ll do my best to tackle it all in one article today. When considering platooning, there are two main concepts that the discussion can be distilled down to: sample size and opportunity cost.

What most people don’t realize is that very few players truly need to be platooned. We tend to look at a player’s performance versus same-handed pitching either for the current year or even over a three-year period when making such decisions, but this isn’t nearly enough data to make a reasonable guess as to whether the player is best used in a platoon (absent scouting data that supports his performance, which makes this a more complicated decision).

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What does it take for assorted pitching stats to stabilize?

Last week in this space, I updated a study originally run four years ago by former BPer Russell Carleton (then monikered “Pizza Cutter”) at the now-defunct MVN’s StatSpeak blog. The study examined how long it takes for different stats to “stabilize.” Since I looked at hitting last week, I’ll be looking at pitching this week.

Before I get started, I wanted to make one quick announcement. After my first chat was such a success, I’ll be holding my second-ever live BP chat tomorrow afternoon at 1 p.m. EST to answer all of your fantasy questions.

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In a return look at Russell Carleton's original study, Derek tries to find at what point stats stabilize and can be trusted.

Four years ago, former BPer Russell Carleton (then monikered “Pizza Cutter”) ran a study at the now-defunct MVN’s StatSpeak blog that examined how long it takes for different stats to “stabilize.” Since then, it has become perhaps the most-referenced study in our little corner of the internet.

It has been a while since the initial study was run, and since there are a few little pieces of the methodology that I believe could be improved, I decided to run a similar study myself.

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