FanGraphs Baseball

Ben and Sam preview the Brewers’ season with BP Milwaukee’s Ryan Romano, and Jeff talks to freelance writer Jack Moore (at 23:16).

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On multiple occasions last year, the author published a statistical report designed to serve as a mostly responsible shorthand for people who, like the author, possess more enthusiasm for collegiate baseball than expert knowledge of it. Those reports integrated concepts central to much of the analysis found at FanGraphs — regarding sample size and regression, for example — to provide something not unlike a “true talent” leaderboard for hitters and pitchers in select conferences.

What follows represents the first such report for the 2016 college campaign, which began last Friday.

As in the original edition of this same thing, what I’ve done here is to utilize principles introduced by Chris Mitchell on forecasting future major-league performance with minor-league stats.

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The Milwaukee Brewers had a good offseason. As Dave Cameron wrote earlier this week, “If you want to see a blueprint for how to rebuild, look at what the Brewers did this winter.”

David Stearns, who replaced Doug Melvin as the club’s general manager in September, has been the main architect. An assistant GM in Houston before coming to Milwaukee, Stearns is laying the groundwork for what he envisions as an Astros-like level of resurgence.

Stearns addressed offseason player-acquisition strategy earlier this week in Phoenix.

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Stearns on preparing for the offseason: “Preparation starts in August. You start to look at what your team might look like going forward — what your needs are, what the availability of other players might be. Read the rest of this entry »

One week into the college baseball season, Louisville head coach Dan McConnell’s decision to bat Corey Ray atop the order this year looks like it’s going to pay dividends for the next four months.

If you’re unfamiliar with what the star outfielder has done over the four games since he moved up to the leadoff spot from the three-hole last season, consider this cartoonish statline: .733 AVG (11-for-15); .750 OBP; 1.533 SLG; 1 double; 1 triple; 3 HR; 6 SB.

For sure, Louisville’s two opponents for those four games – Southern Illinois University Edwardsville and Eastern Kentucky – aren’t teams that we could have expected to offer much resistance. But no matter: it’s an exceptional beginning that deserves mention as the five-tool prospect looks to establish himself as the best position player in the 2016 draft class.

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When the home team enters the top of the 9th with a 3-run lead, they will win that game 98% of the time. That happens mostly because they get to pick and choose the reliever they want. If they chose a random reliever, they’d win 97% of the time. If they chose a poor reliever, they’d win 96% of the time. It’s pretty tough to mess up a 3-run lead, especially when the home team gets one more crack at it in the bottom of the 9th.

So, we have a SP that went 8, and he hands off to the reliever this 3-run lead. The ace reliever comes in. Let’s call him Armando Benitez. He walks the first batter, allows a HR to the second, then strikes out the side. The game ends, and his team wins. Armando even gets a “save”, whatever that is supposed to imply.

Since he was given a 3-run rope, and he only used 2-runs, he was able to turn a 96% or 98% chance of winning into 100%, all without the help of his fielders. Incredibly, things could have gotten worse, which does happen 2 to 4 percent of the time. In this case, he pitched just bad enough to win.

The other day, I asked you a stupid question: how excited are you about the coming baseball season? It doesn’t seem like that interesting of a question, and, let’s face it — we’re hanging out on FanGraphs, which means we’re all already total baseball dorks. Of course everyone’s kind of amped to have baseball coming back. It’s the reason we’re here.

Though it was a silly question, however, silly questions lead to data, as long as you’re keeping records. That’s what I was hunting for. That’s what I’m always hunting for. By putting up a poll for fans of every team, not only can I calculate an excitement rating, but I can also examine excitement ratings relative to the whole league. Out of a simple Internet post, I now have a whole spreadsheet that tracks how baseball fans feel, and if you’re curious to see how the polling shook out, just scroll down. You don’t even need to read the words if you don’t want to. Believe me, I won’t know.

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First thanks so much for the tremendous responses, both in the comments and just the participation in the polls. There’s been 700 to 1200 votes in each poll. Just overwhelming responses.

For now, let’s start the second inning by leaving aside the hitters and talk about defense. Now, when I refer to defense, I mean pitching+fielding. Remember, defense is the whole team, the pitchers and the fielders. We’ll worry about how to separate fielders from pitchers in a soon-to-be-asked question. Just not now. Cool?

Let’s say that one team defense allows 10 hits with 3 walks. But they are all scattered, and so actually end up with a shutout. Another team defense allows the exact same number of hits and walks. They even allow them in the exact same way. The only difference is the timing. They allowed them bunched up, and so resulted in eight runs allowed. From a team defense perspective, how do you see them in terms of assigning value?

It all makes the Orioles look bad, which isn’t fair. It was supposed to be easy enough for the Orioles to sign both Yovani Gallardo and Dexter Fowler. Then, within a few days, the Gallardo talks nearly fell apart, and the Fowler talks did fall apart. Instead of the Orioles and Fowler having an agreement, it turns out Fowler wanted a one-year opt-out, which the Orioles wouldn’t give him. That’s a perfectly defensible stance, but here’s where we are now: Baltimore doesn’t have Dexter Fowler. Fowler has gone back to the Cubs, for a year and $13 million. It’s all been a pretty stunning turn of events, and the breakdown in the Baltimore talks has allowed the Cubs to answer the last big question they had.

For the Orioles, it’s a bad look, and it’s frustrating, because now they have to keep poking around to fill a hole they thought they’d fill. It’s probably somewhat bad for morale, and now you can likely expect the Orioles to get in contact with the Reds about Jay Bruce. It’s not the worst fallback in the world. Yet this is all really about the Cubs. The Cubs get to keep Fowler, if only for a year. It reduces the uncertainty for what’s pretty clearly a World Series favorite.

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Camps are open, players either are or aren’t in the best shape of their lives, and everyone’s starting to tire of watching bullpens and PFP. Let’s continue to take a position-by-position look back at the ball-in-play (BIP) profiles of 2015 semi-regulars and regulars to see if we can find any clues as to their projected performance moving forward. We’ve already looked at first basemen and designated hitters and second baseman and shortstops; today, let’s complete the infield with a look at third basemen.

First, some ground rules. To come up with an overall player population roughly equal to one player per team per position, the minimum number of batted balls with Statcast readings was set at 164. Players were listed at the position at which they played the most games. There is more than one player per team at some positions and less at others, like catcher and DH. Players are listed in descending OPS+ order. Without further ado, let’s kick it off with the AL third sackers.

BIP Overview – AL 3B

Name	Avg MPH	FB/LD MPH	GB MPH	POP%	FLY%	LD%	GB%	CON	K%	BB%	OPS+	Pull%	Cent%	Opp%
Donaldson	92.43	96.71	88.50	3.6%	34.3%	17.3%	44.8%	156	18.7%	10.3%	155	42.9%	33.5%	23.7%
Valencia	92.90	95.57	90.61	2.6%	27.7%	17.2%	52.4%	149	21.2%	7.7%	134	47.8%	34.0%	18.3%
Machado	92.44	94.03	92.43	5.4%	33.1%	17.8%	43.7%	123	15.6%	9.8%	131	38.1%	36.7%	25.2%
Moustakas	89.85	91.47	90.64	6.3%	35.1%	18.8%	39.9%	103	12.4%	7.0%	120	39.2%	33.4%	27.4%
Seager	89.25	91.82	86.86	4.0%	36.8%	24.0%	35.2%	99	14.3%	7.9%	118	44.4%	31.8%	23.8%
Longoria	90.26	93.98	86.31	4.4%	36.0%	20.6%	39.0%	111	19.7%	7.6%	111	41.9%	32.1%	26.0%
Beltre	89.88	92.95	87.34	2.9%	32.8%	22.7%	41.6%	96	10.5%	6.6%	110	38.8%	38.6%	22.6%
Freese	89.56	94.29	86.28	1.9%	26.2%	17.5%	54.4%	113	22.8%	6.6%	109	38.1%	30.6%	31.3%
Valbuena	89.89	93.98	85.34	4.2%	41.3%	20.3%	34.2%	101	21.5%	10.1%	103	44.7%	29.3%	26.0%
Plouffe	90.81	93.39	88.57	4.9%	35.8%	18.2%	41.1%	101	19.6%	7.9%	99	42.7%	34.6%	22.7%
Castellanos	88.36	90.59	85.37	0.5%	39.9%	23.3%	36.2%	118	25.5%	6.6%	98	36.2%	34.5%	29.3%
Lawrie	90.06	94.39	87.11	1.9%	30.8%	18.5%	48.8%	111	23.9%	4.7%	92	38.1%	36.7%	25.2%
Headley	87.20	90.48	84.31	3.6%	26.8%	26.6%	43.1%	96	21.0%	7.9%	92	44.3%	35.6%	20.0%
Sandoval	89.20	91.95	88.85	4.3%	28.0%	18.8%	48.9%	74	14.5%	5.0%	76	29.8%	39.5%	30.8%
AVERAGE	90.15	93.26	87.75	3.6%	33.2%	20.1%	43.1%	111	18.7%	7.6%	111	40.5%	34.4%	25.2%

Most of the column headers are self explanatory, including average BIP speed (overall and by BIP type), BIP type frequency, K and BB rates, and BIP by field sector (pull, central, opposite). Each player’s OPS and Unadjusted Contact Score (CON) is also listed. For those of you who have not read my articles on the topic, Contact Score is derived by removing Ks and BBs from hitters’ batting lines, assigning run values to all other events, and comparing them to a league average of 100.

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