This morning, we wrapped up our look at the guys who play the field in our Positional Power Rankings series; we’ll be tackling the pitching staffs next week. But for those of you interested in playing catchup or going back over the posts, I’ve collected them all in one handy place here; you’ll still always be able to reference all of the posts in the category, but I figured I’d make them a little bit easier to find here.
Yesterday, Forbes released its franchise values for all 30 Major League Baseball teams. Briefly, the team values are estimates of the price that the franchise is likely to sell if the team’s management group began fielding offers. There are always debates about the accuracy of revenue and valuation figures, and I would recommend reading one of the many FanGraphs articles that already has examined the methods and discrepancies in both Forbes and Bloomberg’s valuation metrics.
In this post, I want to provide some graphical context for Forbes’ data and allow you to explore the data in a different way than on a table.
Being a financial news outlet, the team value is the heart of the Forbes’ data. The graphic below shows that data as a simple bar graph. From this, there are four different tiers of teams. There’s a small-market plateau that constitutes the lower half of MLB teams. These teams are valued under $1 billion and come from smaller cities (except Toronto and Houston). The next tier has larger metropolitan areas or teams that are the secondary team in the largest markets (White Sox, Angels, Mets). The third tier is composed of ‘big market’ teams that come from the largest US cities. Finally, the Yankees are in a tier by themselves.
Last week, I suggested that the Dodgers don’t really need Hector Olivera because they already have something pretty similar in Justin Turner. Obviously, Andrew Friedman and his crew do not agree.
Source: Cuban INF Hector Olivera has agreed to a 6-year, $62.5 million deal with Dodgers. $28MM signing bonus. Check http://t.co/mkcBse7p5i
— Jesse Sanchez (@JesseSanchezMLB) March 24, 2015
Kiley McDaniel did a nice job breaking down Olivera a few weeks ago, and in that piece, he wrote this: “The Dodgers are the only team that’s in on Olivera that can afford to pay whatever they want.” And this signing is a reminder that they really can do just that; a team with the largest payroll in baseball and no obvious spot for Olivera this season just ponied up a $28 million signing bonus and $34 million in future salary commitments for a guy who probably doesn’t make a significant impact for them until 2016, when he’ll be 31 years of age.
Of course, it’s quite possible that my Justin Turner comparison was quite light, and perhaps Olivera is even better than Juan Uribe by the second half of this season, giving the team a bit of an upgrade at third base for the stretch run. It’s not impossible that Olivera will contribute this year, though he’d have to be pretty great to represent a substantial upgrade over Uribe, Turner, and whatever Alex Guerrero could potentially give them at third base.
Right now, we have the Dodgers third base contingent combining for about +3 WAR this season; Olivera might push that to +4 if he comes up quickly and is awesome, but this is unlikely to move the needle for LA that much this year. This is basically the Dodgers spending $63 million to solve a 2016 problem — when Uribe and Howie Kendrick are both set to hit free agency — a few months in advance. And they’re basically the only team in baseball that can still afford to do stuff like that.
It’s great to be smart and find all kinds of hidden bargains, constructing a good team out of undervalued pieces. It’s also great to just be able to outbid everyone for anyone you want. The Dodgers apparently are going to do both.
Using the FanGraph’s Depth Charts tool, I created a data visualization for batters’ offensive output using on-base plus slugging percentage (OPS) as the primary statistic. Pitchers have been excluded. The Depth Chart tool takes projections from both ZIPS and Steamer and accounts for playing time creating projections for counting stats (PA, WAR, etc.) and team performance. The Positional Power Rankings being released this week use the Depth Charts as well.
The histogram below creates an overview of the entire league showing the OPS distribution, which is normal with a skew to the right reflecting the infrequency of elite offensive players.
We’ve made some slight changes to the way WAR is calculated. The changes will impact players at most, about 0.5 wins, but the vast majority of individual player WAR will remain pretty unchanged.
1. Position player WAR now includes ground into double play avoidance (or lack thereof) with the stat wGDP. This will impact the very best players about +/- 0.5 wins. All but a few will fall in the +/- 0.2 win range. wGDP is also available as a separate stat in both the leaderboards and the player pages.
2. UBR has been updated to include advances and outs on WP and PB, as well as a few minor changes. Big thanks to Mitchel Lichtman for this and the wGDP inclusion.
3. Pitcher WAR park factors have been changed to FIP specific park factors. You can see all the new park factors under FIP in the FanGraphs Guts! Section. FIP park factors in general are considerably more compressed than runs park factors, so pitchers in extreme parks will be less impacted. Thanks goes out to Noah Baron for the suggestion.
4. We’ve adjusted the pitcher WAR league baseline to better even out the leagues.
Louisiana State plays Arkansas tonight in the second of a three-game series at the latter school’s home field. As the author has suggested elsewhere, the series is notable insofar as it features a number of players who currently rank among the SEC’s top hitters by (maybe) predictive stats — including, for example, LSU shortstop Alex Bregman and Arkansas center fielder Andrew Benintendi.
Who else tonight’s game, specifically, features is LSU freshman right-hander Alex Lange. In his most recent start for the Tigers, Lange recorded a 13:0 strikeout-to-walk ratio against 28 batters over 8.0 innings against Ole Miss (box). How he did it was largely by means of a hard curveball, footage of which the reader can find below with a view to whetting his or her appetite ahead of tonight’s 9pm (ET) first pitch.
An example of the curve from the second inning of that game against Mississippi:
Yesterday, the author published a post claiming to include the top players by (maybe) predictive stats from college baseball’s most competitive conferences.
What follows are the three weekend series likely to feature the greatest number of players whose names appeared within that post. KATOH+ and KATOH- are index metrics based on those (maybe) predictive stats and designed for batters and pitchers, respectively. In each case, 100 is average, while above 100 is better for batters and below 100 is better for pitchers. Read more about the author’s questionable methodology here.
Miami at Wake Forest
Who It Features
Three of the ACC’s top-10 hitters. From Miami: junior third-baseman David Thompson (97 PA, 128 KATOH+). From Wake Forest: sophomore first baseman Will Craig (93 PA, 142 KATOH+) and sophomore second baseman Nate Mondou (100 PA, 124 KATOH+). Among pitchers, Wake Forest sophomore right-hander Parker Dunshee (28.0 IP, 81 KATOH-) has produced one of the conference’s top-10 lines this season. Typically the school’s Saturday starter, he most recently worked in relief of Friday night starter and senior Matt Pirro (28.2 IP, 94 KATOH-).
When It’s On
Friday at 6:00pm
Saturday at 4:00pm
Sunday at 1:00pm
How to Watch It
Watch ESPN (link).
Adam Ottavino seems like a pretty awesome dude. Not only has he been excellent in relief for the Rockies the past two seasons, but he’s been an outspoken proponent of sabermetrics (and FanGraphs! Hi Adam!), and that’s refreshing to hear from a player.
He gave an incredible interview with Brian Kenny on MLB Now, where he admitted this Mike Petriello post from June caused him to change his approach. Then, this morning, David Laurila published a scintillating Q&A with Ottavino, in which he namedrops BrooksBaseball and PITCHf/x while talking about his three-in-one slider:
On his slider variations: “I throw sliders multiple ways. They all read the same – they read as sliders on PITCHf/x — but they are three different pitches. There’s more of an up-and-down, more of a slurve, and one with more of a straight lateral break. I do that with two different grips. As a pitcher who throws such a high percentage of breaking balls (47.3% in 2014), I don’t want to make them all exactly the same, Even if the hitter reads slider out of my hand, he can’t be totally sure where it will end up.”
The way Ottavino described the three sliders was fascinating, and I wanted to get a look at them for myself. I jumped into Ottavino’s PITCHf/x data, roughly identified the three different sliders based on horizontal and vertical movement and location, and split them into three buckets. (Update: I should note, that the usage numbers are super, super rough since I don’t know Ottavino’s intent behind each pitch and simply classified them by movement.)
| Usage | H. Mov | V. Mov | Spin rate | Spin direction | |
|---|---|---|---|---|---|
| Vertical | 28% | 6.1 | -3.9 | 1294 | 57.9 |
| Slurve | 48% | 9.5 | -2.3 | 1746 | 76.7 |
| Horizontal | 24% | 9.6 | -0.9 | 1709 | 84.7 |
In the numbers, you gain a sense of there being three different sliders within Ottavino’s one slider, but what good is getting a sense when you can actually see them for yourself?
Make sure you read the Q&A. It’s fascinating.
Zack Wheeler, last week, in explaining why his current elbow soreness was no big deal.
The second issue — recurring soreness in his right elbow — raises red flags.
“It’s something that I’ve had before and have had to deal with,” said Wheeler, who is expected to take his next turn in the rotation, which falls on Thursday.
…
“Every pitcher in here pitches through pain at some point, so it’s just a matter of dealing with it and going out there,” Wheeler said. “It wasn’t affecting me all that much so I could go out there and compete like I wanted to. So I was going to do it.”
Today, though, the MRI results have revealed a torn UCL, the injury that leads to Tommy John surgery. Assuming Wheeler doesn’t try to continue to pitch through the pain, he’ll be out until roughly mid-summer of 2016.
This is obviously a significant blow to the Mets, as Wheeler had emerged as a quality starting pitcher. This is where they depth comes in handy, however, as the drop-off from Wheeler to one of Rafael Montero, Steven Matz, or Noah Syndergaard isn’t that large. Here are the Mets current depth chart projections for their rotation candidates:
#14 Mets
| Name | IP | K/9 | BB/9 | HR/9 | BABIP | LOB% | ERA | FIP | WAR |
|---|---|---|---|---|---|---|---|---|---|
| Matt Harvey | 173.0 | 9.1 | 2.6 | 0.7 | .297 | 74.2 % | 3.07 | 3.08 | 2.9 |
| Bartolo Colon | 176.0 | 6.2 | 1.5 | 1.0 | .308 | 70.3 % | 4.00 | 3.80 | 1.3 |
| Jon Niese | 178.0 | 6.7 | 2.4 | 0.9 | .307 | 71.2 % | 3.91 | 3.83 | 1.1 |
| Jacob deGrom | 165.0 | 8.2 | 2.7 | 0.8 | .306 | 72.5 % | 3.53 | 3.40 | 1.9 |
| Dillon Gee | 98.0 | 6.7 | 2.5 | 1.1 | .300 | 70.5 % | 4.23 | 4.24 | 0.2 |
| Noah Syndergaard | 75.0 | 9.2 | 2.7 | 0.9 | .310 | 72.8 % | 3.54 | 3.37 | 1.0 |
| Rafael Montero | 28.0 | 8.8 | 3.0 | 0.9 | .302 | 74.1 % | 3.56 | 3.62 | 0.3 |
| Steven Matz | 37.0 | 8.4 | 2.8 | 0.8 | .306 | 73.4 % | 3.42 | 3.43 | 0.5 |
Zack Wheeler  |
56.0 | 8.8 | 3.5 | 0.8 | .307 | 72.8 % | 3.65 | 3.61 | 0.5 |
| Total | 984.0 | 7.7 | 2.5 | 0.9 | .305 | 72.1 % | 3.68 | 3.60 | 9.8 |
ZIPS and Steamer see Montero as Wheeler’s equal for 2015, while actually liking Matz and Syndergaard a little bit more. Of course, losing Wheeler means that one of these guys can’t replace another pitcher when a future injury occurs, so losing Wheeler is far from a good thing, but the Mets are at least positioned to absorb this kind of injury.
The problem will come if too many of Wheeler’s innings are allocated to Dillon Gee. He’ll likely step in and fill the void in the short term, but if he pitches like the projections expect him to pitch, he shouldn’t hold that spot for too long.
Earlier this week, the author published a post claiming to feature the top performances by (maybe) predictive stats from college baseball’s most competitive conferences.
What follows are the three weekend series — one from each relevant conference — likely to facilitate the greatest number of players whose names appeared within that post. KATOH+ and KATOH- are index metrics based on those (maybe) predictive stats and designed for batters and pitchers, respectively. In each case, 100 is average, while above 100 is better for batters and below 100 is better for pitchers. Read more about the author’s questionable methodology here.
North Carolina at Pittsburgh
Who It Features
A lot of pitchers who’ve been successful so far this season, including North Carolina sophomore right-hander Zac Gallen (16.0 IP, 77 KATOH-) and Pitt freshman right-hander T.J. Zeuch (27.1 IP, 78 KATOH-) in the Friday game. Probably right-handed Pitt sophomore Matt Pidich (12.2 IP, 77 KATOH-) in relief. And maybe also UNC senior right-hander Benton Moss (15.2 IP, 74 KATOH-), who’s exhibited a velocity spike but missed last week’s start with an injury.
When It’s On
Friday at 1:45pm ET
Saturday at 3:00pm ET
Sunday at 12:00pm ET
How to Watch It
College Sports Live (link).
