Archive for Head to Head

You can look at parts of Martin Perez’ profile and find yourself salivating over the upside. At the same time, there are parts of his profile that can make you question whether he’s a major sell-high candidate. Ranked around the 100-mark entering the season, Perez seems closer to proving doubters wrong but hasn’t yet validated believers.

To wit: Perez isn’t striking many batters out, but he’s not walking many, either; He’s improved his ground ball rate, but he’s also been gifted a 0.0 percent HR/FB mark; and he has a 1.86 ERA, one that’s surely helped owners early, and it’s backed by a healthy 2.42 FIP and 3.20 xFIP, but ZIPS and Steamer don’t like him any better than a 4.38 and 4.68 ERA, respectively, for the rest of the season.

The good-and-bad profile gets even tougher to figure out when you dive in deeper.
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In an industry league I joined this off-season, I inherited a team with Jean Segura as my starting SS and biggest trade chip. Having never been a Segura fan, I started shopping the Brewer speedster, and found myself relatively flush with offers. In a 20 team league, I think at least eight owners inquired, and deals were pretty solid.

This week, I finally traded Segura, and the return was not what it would have been three or four months ago. So what happened?

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Yesterday we looked at some sell high hitters. At the outset, I noted that selling high is mostly a thing of past – everybody knows it’s good to buy low and sell high. And everyone is a lot smarter about their player evaluation too. These days, the cool kids are buying high. To buy high, one need only identify which top, breakout performers are likely to remain among the top players. Sometimes, owners will sell these players at a relative bargain in their haste to sell high.

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Since 2009 when I started this whole “blogging” thing, I’ve had aspirations to write for FanGraphs. Now that I’m finally here, I don’t know what to say, so I’ll ramble for a bit and hopefully make some kind of point worth reading.

This is how LBJ must have felt when he finally became president: All those years of striving for something that seemed terribly elusive and just when you’re about quit on the whole endeavor, an opportunity arises. You are surrounded by “Harvards” and “Yales”—or in my case brilliant baseball minds—and you went to Southwest Texas State Teacher’s College—or in my case Dominican University of California—and you can’t help but imagine you are horribly inadequate and under-qualified. The good news is that, to the best of my knowledge, no one had to get assassinated for me to get here.

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Halfway through week two, here we are:

4-1
2.67 ERA
9.5 K/9
3.2 K/BB
1.13 WHIP

I think that’s about the best one could expect so far. Regression is coming though, right? I wanted badly to recommend Garrett Richards for this week (@WAS, @NYY), but his ownership rates in CBS leagues (76 percent) are far too high for me to appeal to my unwritten rule that at least two of the three leagues have to be under 50 percent (between Yahoo!/ESPN/CBS Sports).

So here’s who you get this week:

RHP Zach McAllister – 2.6% ESPN/9% Yahoo!/43% CBS – v. KC, @SF Read the rest of this entry »

When the Milwaukee Brewers selected Taylor Jungmann with the 12th pick in the 2011 draft, he was seen as a polished prospect with an advanced feel for pitching who would move quickly through the organization. If everything went to plan, Jungmann would be in the major-league rotation by late 2013, with a long career as a mid-to-back of the rotation starter ahead of him.

At the time, I wholeheartedly agreed with these sentiments. I saw Jungmann pitch several times during his college career at the University of Texas, and it was easy to see why he was viewed as such a sure thing. He had a mid-90s heater with a sweeping curve that projected as a plus pitch, and a change-up that seemed plenty good enough to avoid nasty splits.

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You’ll hear a lot about strikeout rates stabilizing sometime in April, anywhere from about 60 plate appearances to 110 depending on who you trust and who you reference. It makes sense we talk about this, of course, what with the small sample size police on patrol across Fangraphs. From a fantasy perspective, we try to be patient, but there’s nothing worse than holding a turd any longer than you really have to. Because, well, gross.

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Earlier this week, I wrote a piece looking at the other warning signs that surrounded Matt Moore. Velocity was just one of the many areas where Matt Moore was showing decline heading into the 2014 season. Moore’s rates were in a two-year decline (from 2012 to 2013) in each of the following areas:

• F-Strike%
• O-Swing%
• O-Contact%
• Z-Contact%
• Contact%
• Swing%
• Zone%
• SwStr%

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We always hear our not-so-favorite broadcasters mentioning a player’s stats against a certain pitcher. Well, I think we are all hopefully smart enough to not take the results of 15 meetings between a pitcher and hitter seriously. Instead, we split samples into larger groups like right-handed hitter vs. left-handed pitcher. I have decided to cut the difference and create a spreadsheet which takes a middle ground. I grouped pitchers by handedness, velocity and groundball tendencies and found how hitters performed against the different pitcher groups.

First off, I wanted to have this Excel-only spreadsheet available online before the season started. Well, I got it done and working in time. Since Visual Basic macros were used in the final view, it doesn’t have a online option which I wanted. So today, I am going to make it publicly available, but at some point I hope to have it working in all spreadsheet formats and/or online at a place like Google.docs.

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Selling high is generally a misnomer these days. Most of us are in competitive leagues, the kind where all the owners read or write for a reputable site. We learn how to use sites like FanGraphs to do statistical analysis. As a result, it’s really hard to find people to snooker with 15 days of fluky data. However, certain types of players can remain marketable even though everyone is looking for the pitfalls.

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