Archive for Stock Watch

Starting Rotation

The top of the Royals rotation is set with Ian Kennedy, Yordano Ventura and Edinson Volquez taking the first three spots. After those two, the rotation gets a little fuzzy for the 4th and 5th spots. Unless an injury happens to one of the first three, I think five other pitchers may cycle into these final two spots: Kris Medlen, Danny Duffy, Chris Young, Kyle Zimmer and Miguel Almonte. I listed them in the order I think they will get a chance to start. Here is my take on how I think it will shake out for each pitcher.

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David Price signed with the Red Sox

As a whole, the David Price signing doesn’t change his perception or ranking. He is back in the AL East where he made a majority of his career starts. Fenway is a bit of a hitter’s park, so he could see a bit of increase in his ERA and WHIP. Also, the Red Sox’s roster is not set yet, but its defense could vary greatly depending on its final configuration.

The biggest impact will be which of the other starters gets moved to the bullpen or the minors. I would not be surprised if they keep all of them. Buchholz’s disabled list paper work is already typed out and ready to be signed. The rest of the staff, Rick Porcello, Wade Miley, Eduardo Rodriguez and Joe Kelly, all struggled at some point during the 2015 season. Right now it looks like Joe Kelly is the odd man out, all that could and probably will change by opening day.

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Javier Baez has been getting quite a bit of acclaim since returning to the Cubs with his reduced strikeout rate. In 2014, Baez had a 42% strikeout rate (K%) in the majors and 2015 value of 22% K% looks to be a huge improvement. Don’t get too excited about this small sample of data as his swing strike rate (SwStr%) points to a strikeout rate which will likely increase quickly.

Historically, a hitter’s strikeout rate correlates almost identically to their swinging strike rate. The reason to use SwStr% instead of K%  is because it stabilizes a bit faster. I took all hitters since 2002 who had at least 200 plate appearances in a season and found the linear correlation between their strikeout rate and swinging strike rate. The R-squared between the two values was .947 with the equation working out to:

K% = 2.25 * SwStr%

With this little bit of information, here is a look at Baez’s stats in the majors the past two seasons.

Season: SwStr%, Predicted K%, Actual K%
2014: 19.2%, 43.2%, 41.5%
2015: 18.5%, 41.6%, 22.2%

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If you’re a H2H league owner, September could be a frustrating time. It’s when veterans sometimes take a seat as their out of contention teams choose to give young hitters a look and young pitchers reach their innings limits and get shut down. The worst part of it is that these may have been the players that helped you achieve the best record in your league, yet come playoff time, you can’t even count on them to contribute to your championship run. So let’s discuss some of the pitchers who are definitely or possibly on an innings limit. Whether their teams decide to skip a start here and there to keep the innings down or just shut him down with two weeks or so to go, I don’t know. But either way, an innings limit would take a bite out of the pitcher’s value the rest of the way.

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Fantasy owners are heavily influenced by the forces of recency bias. A hitter is in the midst of a hot streak, having hit .400 over the last week with a pair of long balls? Pick him up! Unfortunately, we know that such streaks have limited, if any, predictive value, resulting in this strategy usually being a losing one. But that’s not always the case, as a hot streak could lead to increased playing time and we’re always chasing at-bats (and innings pitched). So let’s take a gander at which players have been added the most in CBS leagues over the last week and determine whether picking them up is a good move. Obviously, context plays a huge role in decisions like these, but since we have no such information, we’ll do our best.

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It’s no secret that I loved Carlos Carrasco heading into the 2014 season. His spectacular performance over his final 10 starts last year vaulted him into the not actually a sleeper sleeper territory during this year’s draft season. By this I mean that he was hyped as a sleeper by just about everyone, but that meant that everyone who paid attention knew how awesome and legit he was and bid him up to or drafted him at fair value. But his first eight starts of this year have not gone the way we all expected. His ERA sits at a disappointing 4.98 and he has averaged just about 5.4 innings per start.

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I have essentially stripped the terms “buy low” and “sell high” from my vocabulary, so I now prefer to call the former buy low guys acquisition targets. One would think that offering for a player off to a slow start would have to come at some sort of discount, even if a minor one. And since slow starts are usually just that and have little predictive value for the rest of the season, getting anyone at a discount to his pre-season value should yield a nice profit.

As usual, the easiest way to identify your targets is to calculate the difference between a pitcher’s ERA and SIERA and then sort. Those pitchers with SIERA marks most below their ERAs are typically your targets, though that’s not automatically the case. Often times a pitcher could be carrying an ERA over 7.00, but still sporting a 4.50 SIERA. Sure, he’s been unlucky, but he also hasn’t been very good either! So you still don’t want him on your team.

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We’re not a month into the season, so it’s finally time to start putting the hitter batted ball distance leaderboard to work. Back in late January, I unveiled my xHR/FB rate equation, which included three components, batted ball distance being one of them. Unfortunately, I don’t have the data for angle and standard deviation, so I cannot calculate xHR/FB rate marks yet and share the biggest discrepancies. However, simply looking at batted ball distance could do a reasonably decent job at identifying those who might be in for a HR/FB rate surge or decline. We’ll start with the potential surgers. These are the hitters whose distance is top notch, but for whatever reason, have posted mediocre or poor HR/FB rates.

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The buy low and sell high strategy has been a favorite one of fantasy leaguers for as long as fantasy sports has existed, I would imagine. Unfortunately, it’s nearly dead given the wealth of freely available information and the deeper knowledge we now possess about how to evaluate player performance. Nearly dead, not completely dead. To buy low or sell high on a player, you need a story, a narrative that essentially offers up confirmation bias and makes the owner you’re dealing with feel all fuzzy inside when agreeing to the trade.

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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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