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Articles Tagged Regression 

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Before we can attempt to figure out why a player improved or regressed, we have to figure out how much his performance actually changed.

Quick, which player had the greatest change in on-base percentage from 2011 to 2012? Did you say Houston Astros pitcher Aneury Rodriguez? In 2011, Rodriguez went 0-for-9 with two sac bunts. In 2012, Rodriguez appeared in only one major-league game, but he came to the plate once and got a hit. Rodriguez went from a seasonal OBP of .000 to 1.000. It doesn't get bigger than that.

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September 8, 2012 12:34 pm

Overthinking It: The Mechanical Flaw Fixers

2

Ben Lindbergh

Your team's struggling star just made a mechanical tweak. Is a rebound just around the corner?

There's nothing worse than not knowing why something went wrong. Pinpoint a problem, and it immediately seems more manageable. At some point, you’ve probably caught yourself doing something silly like sitting in a certain position while watching a playoff game, suspecting that the slightest movement could cause your team to stop scoring. Jason Parks displays a signed portrait of Warwick Davis when he wants the Cowboys to win. Only a fool would discount the power of Warwick Davis, but no team triumphs every time, even with Wicket on its side.

We know this, but we perform these little rituals anyway, because they give us the illusion of control. The unsettling alternative is accepting that we can’t do anything to affect the outcome. There’s a famous prayer that starts, “God, grant me the serenity to accept the things I cannot change.” Sports fans aren’t seeking that serenity. They’re too busy trying to hold their heads at a 45-degree angle to keep the rally alive.

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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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June 14, 2012 5:00 am

Resident Fantasy Genius: Ignoring the Trend Line

7

Derek Carty

It is always tempting to think a year-by-year trend will continue, but regression is more powerful than momentum.

If you missed it, I filled a guest spot on the Fantasy Baseball Roundtable Radio show last night alongside industry friends and show regulars Patrick DiCaprio, Mike Podhorzer, and Greg Marta.  We talked mostly about buy-high and sell-low players—you can listen to the whole show here, if you’re interested—but there was one more theoretical topic that came up in passing which I found interesting but didn’t have a chance to jump into: trend analysis.

When discussing “buy high” third basemen, Pat mentioned how he was questioning the utility of trend analysis, specifically in regard to Hanley Ramirez.  Despite a four-year trend of declining power, Hanley has bounced back this year to a level that falls between his 2008 and 2009 seasons:

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Which players do the BP staff expect will come back to the earthly realm this season?

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We're retiring SIERA. Here's why.

Recently, there has been a lot of digital ink spilled about ERA estimators—statistics that take a variety of inputs and come up with a pitcher’s expected ERA given those inputs. Swing a cat around a room, and you’ll find yourself with a dozen of the things, as well as a very agitated cat. Among those is SIERA, which has lately migrated from here to Fangraphs.com in a new form, one more complex but not necessarily more accurate. We have offered SIERA for roughly 18 months, but have had a difficult time convincing anyone, be they our readers, other practitioners of sabermetrics, or our own authors, that SIERA was a significant improvement on other ERA estimators.

The logical question was whether or not we were failing to do the job of explaining why SIERA was more useful than other stats, or if we were simply being stubborn in continuing to offer it instead of simpler, more widely adopted stats. The answer depends on knowing what the purpose of an ERA estimator is. When evaluating a pitcher’s performance, there are three questions we can ask that can be addressed by statistics: How well he has pitched, how he accomplished what he’s done, and how he will do in the future. The first can be answered by Fair RA (FRA), the third by rest-of-season PECOTA. The second can be addressed by an ERA estimator like SIERA, but not necessarily SIERA itself, which boasts greater complexity than more established ERA estimators such as FIP but can only claim incremental gains in accuracy.

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What does the future hold for Derek Jeter, and how can we tell?

Before we can talk about Derek Jeter (and yes, I think there’s still something to say about Derek Jeter that you haven’t already heard this season), we should probably clarify which Derek Jeter we’re talking about. There really are two Derek Jeters—the one who exists in fact, and the one who exists in myth.

The actual Derek Jeter is interesting enough as a player that one wonders why the myth was necessary—always an exceptional hitter, Jeter has always been a player who could’ve had a job on any team in the league. He will go into the Hall of Fame on the first ballot, and nobody will bat an eye. Then there’s the Captain—the athlete whom ad agencies consider akin to Tiger Woods and Roger Federer. The player so exceptional that he can displace a generational talent like Alex Rodriguez from his natural position.

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October 1, 2010 8:00 am

Ahead in the Count: Pitch Data and Walks

4

Matt Swartz

Is having pitch data available helpful in determining a pitcher's walk rates?

Last week, I looked at Predicting Strikeouts with Swing and Whiff Rates, breaking down pitch-by-pitch data to see if things like swinging-strike rates could provide more enlightenment when combined with the previous year’s strikeout rate to predict future strikeout rate. The answer was mostly negative. This was primarily due to two reasons. One was that much of the data on pitch locations is poor, and ensuing discussions highlighted just how poor it is. The other reason, however, is that strikeout rate is the quickest statistic to stabilize over small samples, so one year of strikeout data does a very good job of predicting subsequent strikeout data already. However, this week I will look at walk rate, and attempt to determine whether this data is more useful in predicting future walk rates. There is certainly evidence of value added in this case, far more so than with predicting strikeouts.

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Pitch data shows that the amount of swinging strikes is not predictive of strikeout rates.

When I wrote about pitchers with major divides between their ERAs and SIERAs two weeks ago, a reader inquired why Clay Buchholz had such a pedestrian strikeout rate while having an above average swinging-strike rate. Buchholz has mustered just 6.2 K/9, nearly a full strikeout below the 7.1 league average, but has induced batters to swing and miss on 9.5 percent of his pitches according to FanGraphs, a full percentage point above the 8.5 percent league average. The question was apparent: Do pitchers who get a lot of whiffs increase their strikeout rates over time?

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May 3, 2010 7:05 am

Baseball Therapy: Why Are Games So Long?

29

Russell A. Carleton

Many factors contribute to lengthy games but none more so than the number of pitches.

A few weeks ago, umpire Joe West caused a stir when he publicly called out the New York Yankees and Boston Red Sox for doing what they do best: playing games that take forever to finish.  He’s certainly not the first person (nor will he be the last) to wonder aloud why it is that baseball games last so long (particularly between those two teams).  Is there a way to shorten the great American game?  If there was, should we try?

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March 23, 2010 10:42 am

Ahead in the Count: Predicting BABIP, Part 1

26

Matt Swartz

BABIP isn't as luck-driven as many suggest, not after you drill down into the numbers.

If you don’t put your bat on the ball, you’re not going to get a hit, and if you don’t hit the ball over the wall, someone might catch it. This series begins with what happens the rest of the time as I develop a model to predict a hitter’s Batting Average on Balls in Play (BABIP). In Part 2, I will explain some of the current BABIP superstars then some of the players where my system differs from PECOTA will be the topic of Part 3.

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April 8, 2005 12:00 am

Averages and Extremes

0

Michael Rawdon

While its star has been dimmed by the emergence of OBP and SLG as performance metrics, looking at batting average can provide useful information, particularly when it jumps up or down by a lot across seasons.

Three decades of sabermetric analysis has diminished the once-proud Triple Crown stat through bites (on-base percentage) and nibbles (batting average on balls in play). It's enough to drive any self-respecting free-swinger to distraction.

But batting average is important. In 2004, hits accounted for more than 70% of the on-base events in on-base percentage across the majors. The first base of each hit accounted for more than 60% of total bases in the majors, a key to slugging average. A single is more valuable than a walk, because it carries runner-advancement potential the walk mostly lacks.

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