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: Hello friends
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: Welcome to Tuesday live FanGraphs baseball chat
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: I’ll be your host, apparently
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ON TIME!? |
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: Foolish guest
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Which CLE pitcher do you see most exceeding expectations? |
This is it. This is the year Adrian Beltre finally declines.
Yep, you heard it here first, folks. Adrian Beltre is donezo. I mean, come on — dude’s about to be 36 years old. He’s logged 10,001 plate appearances since he entered the league in 1998, a number topped by only Derek Jeter. His defense has declined significantly the past two seasons, no matter what metric you use. He only hit 19 dingers last year after averaging 32 over the previous four seasons. Clearly, all that wear and tear has taken its toll on Beltre. The jig is up! The fat lady has sung.
Read the rest of this entry »
Evaluating the Prospects: Rangers, Rockies, D’Backs, Twins, Astros, Cubs, Reds, Phillies, Rays, Mets, Padres, Marlins, Nationals, Red Sox, White Sox, Orioles, Yankees, Braves, Athletics, Angels, Dodgers, Blue Jays, Tigers, Cardinals, Brewers, Indians, Mariners, Pirates, Royals & Giants
Top 200 Prospects Content Index
Scouting Explained: Introduction, Hitting Pt 1 Pt 2 Pt 3 Pt 4 Pt 5 Pt 6
Draft Rankings: 2015, 2016 & 2017
International Coverage: 2015 July 2nd Parts One, Two & Three, 2016 July 2nd
The A’s made a ton of moves this off-season, turning over their big league roster and moving a lot of prospect pieces around. This is a function of how Billy Beane sees prospects, which are a means to an end of winning at the big league level. Every player is available for the right price and, if you’re known as a guy willing to make trades, teams are more likely to talk to you and let you know when there’s asymmetry in how teams value various players. Since Beane is always trying to win now and thinks the future is overrated, the A’s, in general terms, tend to pounce on 25-26 year old players who aren’t on lists anymore but still have tools, while trading the shiny new object that hasn’t failed yet.
The amateur talent acquisition has been solid, but this system is more a function of what trades presented themselves in the last few years and the strength of the big league team, than a commentary on whether the scouting/player development executives are excelling. Picking low in the draft, not having a ton of extra picks and only spending what they’re given internationally means the A’s aren’t the kind of team that this sort of list-making process is likely to reward, which I’m sure doesn’t trouble them. I have them in a glut of teams around 25th in the org rankings, but I’ll work out the specific slot in a few more weeks when the lists wrap up.
On Friday, I talked about the current iteration of the Royals, and their propensity toward making contact on a lot of pitches outside the strike zone. In one of the graphs I created, I presented the relationship between O-Contact% and ISO. After some spirited comments on the article about the lack of correlation (given the small sample size and lack of R2), I got to thinking: What is the actual relationship between the percentage of times a batter makes contact on pitches outside of the strike zone (O-Contact%) and offensive production, especially power?
We know certain facts related to the topic of the impact of plate discipline statistics — like players that swing at more pitches out of the strike zone tend to have lower walk rates — but today we’re interested in just O-Contact% and the headline maker, power. This is in large part due to my sometimes unhealthy fascination with the Royals of the past few years, who have been known for winning (at least last year) while not exactly crushing the ball. They only hit 20 home runs through the first 43 games of 2014 and were dead last in ISO (.113) at the end of the season. They also came within a game of winning the World Series, because baseball.
While the Royals might make a great case study, we shouldn’t be too quick to jump to conclusions given their unusual plate discipline statistics and lack of power: we should let the much larger sample size I’m about to go over tell the story. We’re going to focus on two statistics today in relationship to plate discipline: one is ISO, so we can look at raw power, and the other is wOBA, so we can have a look at a more general, catch-all measure of offensive value. Then we’re going to look at a player who truly stands out in the data.
Ben and Sam answer listener emails about Yoan Moncada, sabermetric broadcasts, the replacement-level high-five rate, and more.
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Episode 534
Dave Cameron is both (a) the managing editor of FanGraphs and (b) the guest on this particular edition of FanGraphs Audio — during which edition he discusses the risk and potential reward attached to the $63 million spent by Boston on Cuban defector Yoan Moncada.
Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.
You can subscribe to the podcast via iTunes or other feeder things.
Audio after the jump. (Approximately 33 min play time.)
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Part 1 is over. Part 1 was figuring out which team was going to sign Yoan Moncada, and now we know, with the Red Sox having given up more than $60 million for the right to try to make him into something. Most conspicuously, the Sox beat out the Yankees; less conspicuously, the Sox beat out everyone else. Moncada joins an organization with a silly amount of talent and resources, and he is now presumably Boston’s No. 1 prospect. Not a whole lot of prospects better than Blake Swihart, either. So that’s meaningful.
Now we move on to Part 2. What’s Part 2? Figuring out what Yoan Moncada is going to be. You can kind of deduce what teams expect him to be — based on the price, and based on all the attention, Moncada figures to be some kind of big-leaguer, with a high ceiling. But what have we seen from prospects like this before? Moncada’s going into his age-20 season. We can put some numbers to this, trying in a way to project the unfamiliar. Let’s scan some historical top-prospect lists.
I’m pleased to announce that FanGraphs now has an auction calculator!
In terms of methodology, we are using a method that is pretty similar to the Last Player Picked methodology.
Besides all the usual features of an auction calculator, we have a couple of unique features that are worth some addition explanation:
– There is an “experimental” check box, which adds in replacement level value for players with incomplete playing time. If a player was to have a .300 batting average for the season in 450 plate appearances, it would add in an extra 150 plate appearances at a .220 average (numbers for illustration only) for that player and calculate the auction values off his new batting average.
This is something that could be useful if your league allows you to carry a lot of bench spots and you have the ability to supplement potentially high risk injury players with a replacement level player. Chad Young wrote about this a few years ago.
Please feel free to check the box and see how it changes player values if you feel it’s appropriate for your league. And like the option says, this is still an experiment and should be considered a “beta” feature.
– There is also an option to artificially increase or decrease relief pitcher value. Since we don’t project holds, this might be particularly useful for ottoneu leagues or other leagues where holds are considered. By not taking into account holds for a league that might consider them, relief pitcher values will most likely be inflated.
This could also be a useful option if the players in your league generally undervalue (or over value) relievers and you would like to put relief pitcher values more in line with reality as opposed to theoretical value.
Please let us know if you run into any issues!
My last article introduced the concept of estimating a pitcher’s ERA using a simulation called SERA. As I pointed out throughout the article, SERA was strictly an estimator, not a predictor. That is, a pitcher’s SERA in one season wouldn’t do a great job predicting that pitcher’s ERA the next season. It’s more similar to FIP than it is to xFIP; descriptive rather than predictive.
But what if we want to create a simulator that predicts ERA for the future instead of just estimating what the ERA should’ve been? Some things are going to need to be changed — not just the code for the simulation, but also the inputs.
For the last few months, the baseball world has been speculating about Yoan Moncada. The question of who would sign him was less interesting, as the structure of the deal — a 100% tax on the signing bonus, due by the middle of the summer — meant that this was a bidding war that only teams with significant cash flows could justify winning. From the beginning, the Red Sox, Yankees, and Dodgers were identified as the heavy favorites, and in the end, Boston won the battle of the big spenders.
More interesting was the question of how much Moncada would sign for, because this was a bit of a unique situation in MLB. Because Moncada could only be lured with a signing bonus, and because of the tax on the signing, teams were being asked to spend significant present dollars for a chance to buy potential future wins. While this happens on a small scale in the draft and with other young international prospects, teams generally do not have to make these kinds of short-term investments without getting short-term rewards.
The last time I wrote about Moncada, I noted some similarities between signing Moncada and paying the posting fee for a player coming over from Japan, which pushed over $50 million for both Daisuke Matsuzaka and Yu Darvish. Those players also came with a steep up-front cost and hadn’t proven themselves as big league contributors, but neither one spent a day in the minor leagues before jumping into their team’s rotations; they were viewed more as major league free agents, just without the track record that other big league free agents bring.
Moncada has the short track record in common, but unlike Darvish, Matsuzaka, and Masahiro Tanaka, he’s not big league ready. The consensus is that he needs a year or two in the minors, and given that he’s just 19, that might even be aggressive. It wouldn’t be at all strange for him to not make a significant impact at the big league level until he’s 22 or 23, as even the prospects teams are most sold on don’t always develop as quickly as expected. So, the Red Sox $63 million investment — once you double the signing bonus to account for the tax — will likely return little or no value for several years, and because even very good prospects still have high failure rates, there’s a real possibility that this investment never returns anything at all.
