Who surprised last year and what does that mean for 2017?
Yesterday, George Bissell gave a rousing introduction to our bloated American landscape of low innings totals, high earned run averages, and higher ace valuations in turn. With managers increasingly inclined to limit third-time looks, workhorse starters are becoming as rare as split-ticket voters, and an old-world strategic play of bulking up rotation back-ends with average innings-eaters may just be gone forever by the wayside. Before we get too lost in nostalgia, let’s take a look at a few guys who either over- or under-performed in the category of ERA.
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Of pitching well, we mean. The question is why, and the even more important question is whether he can improve.
Last November, when Doug Fister was a year away from free agency, he received four down-ballot votes for the Cy Young Award. It seemed then that all Fister needed to do in order to enter the marketplace on good terms was remain healthy and perform in 2015 as he had in previous seasons. If he could do both, he would secure his place in the second tier of available starters, favorable standing for a pitcher whose "underrated" label was born from a) his inclusion in two one-sided trades and b) statistics that had outrun his stuff at every turn, giving them the feel of unsustainability.
Some nine months later, Fister's statistics have indeed worsened. His production this season has been so poor—entering the week his adjusted DRA was the 11th-worst among pitchers with 50-plus innings, a smidge better than the likes of Sean O'Sullivan and Jeremy Guthrie—that he is now outside the second tier of perspective free-agent starters; in fact, he's outside of all the tiers because he's no longer a starter. Late last week the Nationals officially moved Fister to relief, bumping their old heisted gem in favor of their newest: rookie sensation Joe Ross.
Pittsburgh's recent incredible record may be due to regress.
Over their last 30 games, the Pirates are 22–8. No other team in baseball is better than 19–11 over their last 30. The Pirates overall are 53–35, with a nearly equivalent Pythagorean record. They completed two straight comeback, extra-inning, walk-off wins over their archrivals heading into the All-Star break. In Andrew McCutchen and Gerrit Cole, they have two true superstars. McCutchen might be a top-10 position player in MLB, and Cole is one of the 20 or 25 best starters in baseball. Armed with Cole, two veteran starters (Francisco Liriano and A.J. Burnett) who owe their career renaissances to pitching coach Roy Searage, a bullpen stocked by a thorough and savvy front office, and a meticulous, aggressive defensive game plan co-crafted by that front office and the field staff under Clint Hurdle, Pittsburgh is allowing fewer runs per game than anyone, save the Cardinals. It's fun when the biggest story in baseball is the dominance of a small-market juggernaut, and that appears to be the case right now. The Pirates have one of baseball's most popular players, its most beautiful ballpark, and a delightful backstory.
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.
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.
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).
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:
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 likeSIERA, 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.
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.
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.