Author Archive: Mike Podhorzer

Yesterday, I issued my first challenge. Sparked by Brandon McCarthy’s bizarre outing on Monday, I asked you to prove that his HR/FB rate was not bad luck. The challenge led to some great discussion, which is exactly what I had hoped it would do.

Now it’s time to move on to the second, and likely final, challenge. It’s a topic that I am more interested in and has been debated ad nauseam. Of course, I’m talking about pitcher BABIP. We have been taught that pitchers will tend to regress toward the league average, which has sat around .295 in recent years, as hitters actually possess the majority of control over how often balls in play falls for hits. So early on, we eventually came to accept this.

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In two starts spanning 12 innings, Brandon McCarthy has allowed six home runs. Out of 12 fly balls. For a 50% HR/FB rate. After witnessing the last of those homers in Monday’s game, I Tweeted about it. Because that’s what all the cool kids do nowadays, Tweet, right? After a couple of back and forths, I then Tweeted the following:

@RotoLance Anyone who claims to have evidence for why McCarthy, or any pitcher, has allowed an inflated HR/FB rate is lying or just wrong.

— Mike Podhorzer (@MikePodhorzer) April 14, 2015

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Yesterday I analyzed the ultra small sample size of one outing when discussing four starting pitchers. But that’s kinda okay because fastball velocity stabilizes quickly and instantly provides useful information. Since I don’t know what else one writes about a week and a half into the season, let’s talk about a couple of more names with regards to fastball velocity.

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Fastball velocity has seemingly received increasingly greater attention over the past couple of years. Perhaps it’s because it just keeps rising. A quick Google search yielded this interesting article detailing recent trends and confirming that average fastball velocity has risen every year since 2008. For us fantasy owners, velocity is important because a spike is often the precursor to a breakout. So let’s talk about a couple of pitchers and what we have seen from their velocity in the early going. These guys have all started just one game, which is as small a sample size as ever. But, velocity stabilizes very quickly, so it’s still worthwhile to discuss.

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Last week, I posted the first iteration of the American League starting pitcher tiers. Naturally, I couldn’t possibly include every starting pitcher, even if they conceivably have the upside to push their way into the rankings at some point. So let’s discuss a couple of names that could quickly make a debut appearance.

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Baseball in 2015 has finally begun! Well, the version that actually counts has. So it’s time to dig deep and uncover those hidden gems that could lead you to victory. As usual, the deep league wire will include names owned in 10% and less of CBS leagues and usually be players whose value is confined to deep mixed or mono leagues, unless otherwise noted.

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So, it’s been a busy preseason and I had a list of all the articles I wanted to publish before the season officially began. Unfortunately, I failed. And as a result, Eno beat me to the punch. But I’m going to do it anyway. A whole three years ago, with help from math wizard Matt Swartz, we discovered that spring pitcher strikeout and walk rates actually do hold value and using them could improve projections, even if just marginally. This was validated recently by another math wizard, Dan Rosenheck. So with that in mind, let’s take a look at which pitchers enjoyed a strikeout rate surge during spring training.

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Opening day is finally upon us! I conclude this year’s (condensed) Pod’s Picks series with starting pitchers. If you missed them, here are the infielders and outfielders. The bullish group will only include those I ranked within my top 75 and the bearish only players the consensus ranked within their top 75.

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Yesterday, I opened 2015 Pod’s Picks season with my infield bullish and bearish selections. Today I’ll finish my look at hitters by moving into the outfield. The bullish group will only include those I ranked within my top 60 and the bearish only players the consensus ranked within their top 60.

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Due to the busy preseason schedule of posts I had to publish, the 2015 version of Pod’s Picks is being unveiled later than ever before. But I refuse to skip a year because it’s always fun comparing my rankings to the rest of the rankers and discovering who was closer at season’s end. Rather than drag things out by posting just one position a day like I have in the past, I’m grouping them into infield, outfield and starting pitchers to bring us into the start of the season (finally!).

I calculated the average rank of the three rankers in the Rotographs Rankings Update and then compared to my ranking within each position. As usual, I will limit my Bullish picks to those I have ranked as startable players in a standard 12-team league and Bearish picks to those the consensus has ranked as startable.

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