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.

Two weeks ago, I published the first such report for the 2016 college campaign; last week, the second one. What follows represents the third installment of a possibly infinite series.

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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Previous editions: Baltimore / Boston / Chicago AL / Chicago NL / Cincinnati  / Cleveland / Colorado / Detroit / Houston / Kansas City / Los Angeles (AL) / Miami / Minnesota / Milwaukee / New York (NL)

Yesterday, lead prospect analyst Dan Farnsworth published his excellently in-depth prospect list for the Los Angeles Dodgers. In this companion piece, I look at that same LA farm system through the lens of my recently refined KATOH projection system. The Dodgers have the third best farm system according to KATOH, trailing only the Brewers and Astros. They have the most projected pitching WAR and the most WAR coming from 3.5+ WAR players.

There’s way more to prospect evaluation than just the stats, so if you haven’t already, I highly recommend you read Dan’s piece in addition to this one. KATOH has no idea how hard a pitcher throws, how good a hitter’s bat speed is, or what a player’s makeup is like. So it’s liable to miss big on players whose tools don’t line up with their performances. However, when paired with more scouting-based analyses, KATOH’s objectivity can be useful in identifying talented players who might be overlooked by the industry consensus or highly-touted prospects who might be over-hyped.

Below, I’ve grouped prospects into three groups: those who are forecast for two or more wins through their first six major-league seasons, those who receive a projection between 1.0 and 2.0 WAR though their first six seasons, and then any residual players who received Future Value (FV) grades of 45 or higher from Dan. Note that I generated forecasts only for players who accrued at least 200 plate appearances or batters faced last season. Also note that the projections for players over a relatively small sample are less reliable, especially when those samples came in the low minors.

1. Corey Seager, SS (Profile)

KATOH Projection: 12.3 WAR
Dan’s Grade: 65 FV

Seager showed what he’s capable of last September when he slashed .337/.425/.561 with the Dodgers. Prior to that, he hit a strong .278/.332/.451 in Triple-A. Seager’s 2015 numbers weren’t particularly gaudy, but he did manage to cut down on his strikeout rate, which was previously the one flaw in an otherwise promising stat line. Shortstops who hit that well at such a young age are few and far between. That’s why Seager has the chance to be a special player.

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The first thing to consider when we think about Hyun-soo Kim’s hitless, OBP-less first 23 at-bats is that it’s 23 at-bats, and it’s Spring Training. Not that everyone hasn’t been considering this all along, but it’s always worth a reminder. Jose Bautista had an 0-for-25 run last year, and those were in games that count, and that wasn’t his first time ever facing major league pitching. It happens. Sometimes, it even happens to the best of them.

Yet, it’s still fair to wonder on this a bit, because this is the first we’ve seen of Kim, meaning it’s all we’ve seen of Kim, and it’s not like dudes are running 0-fers over 23 at-bats all the time — it would’ve been the 12th-longest hitless streak of last year, and the third-longest streak of not having reached base. This was a notable stretch of futility, Spring Training notwithstanding. The past tense being used here, of course, because Kim has snapped the streak. He reached base for the first time this spring after being hit by pitch on Thursday, and later got his first hit — a bases-loaded, RBI single off a Yankees reliever named James Pazos.

Through 25 plate appearances, Kim’s spring slash line is now .042/.080/.042. The hit is the new story, but we can learn more about Kim through the 23 outs. Let’s see.

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Kim observation No. 1: Not all of this is on video

This one actually serves as a double-observation, with the latter half being a reminder that really, none of this too much matters. Proof of that being, not all of it is even televised. It’s 2016. If something matters, you can sit on your couch in your underwear and watch it on television. You can watch plenty that assuredly doesn’t matter, too, so it says something about those events which are consciously not televised. The first few games of Baltimore’s Spring Training weren’t televised, and neither was a select game in the middle. The rest were, though, and I watched 13 of Kim’s 24 hitless plate appearances and took some notes.

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Trevor May is a thinking man’s pitcher. He’s also a strikeout pitcher, which is something Minnesota has lacked for several seasons. Where he will deploy those traits — the rotation or the bullpen — is one of the biggest questions in Twins camp.

A starter by trade, May moved into a relief role last July. It was a switch dictated more by circumstance than performance, and the 26-year-old right-hander is hoping to once again assume an every-five-days work schedule. Based on his thought-process and his repertoire, it’s where he feels he’s best suited.

Originally drafted by Philadelphia, May came to Minnesota in December 2012, along with Vance Worley, in exchange for Ben Revere. His 2014 10-game cameo was rocky, but he was solid last year in his dual-role. In 48 appearances — 16 starts and 32 relief appearances — he logged a 3.25 FIP and a 8.93 K/9.

May talked about his continued development, and the cerebral approach he brings to the mound, last week in Fort Myers.

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Trevor May on his pitching philosophy: “I have a specific philosophy. I try to make it a step-by-step process with every pitch. There are three things you do every time you throw the ball. Read the rest of this entry »

Infielder Nick Senzel has been an impact player for Tennessee ever since he arrived in Knoxville, but his draft stock took a major jump forward last summer when he was named MVP of the Cape Cod League and positioned himself as a first-round candidate heading into the spring.

He’s built on his momentum in his first 12 games this season, hitting .396/.500/.521 while answering some questions about his glove and where he’ll play at the next level. I caught Senzel when the Volunteers visited East Carolina in Greenville, N.C., as part of the 13th Annual Keith LeClair Classic last weekend. The video below starts with his pre-game batting practice in ECU’s indoor cages, then moves to pre-game infield and concludes with his first three at-bats from the game.

Physical Description

Listed at 6-foot-1, 205 pounds, Senzel has a muscular, pro build that looks about five to 10 pounds denser. He’s barrel-chested with broad shoulders and, in general, well developed and proportioned. Though he won’t get much stronger than he already is, you probably don’t want him to, either, as added mass would just limit his flexibility and medium-twitch athleticism.

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This isn’t going to be one of those online quizzes where you answer a few questions and then some script determines what you are based on your feedback. This is a quiz where you answer one question, a question you might never have been asked before. Maybe you’re going to learn something about yourself. We’re all put here to learn about ourselves.

It should go without saying that, for the most part, FanGraphs is selective for baseball dorks. Sure, casual fans find themselves here from time to time, but mostly, we cater to people who just want to think about baseball in between all of the baseball. That requires a certain intensity, a certain passion for the material, and it’s why we’re sometimes able to write about such complicated subjects without constantly stopping to explain ourselves. The audience is smart, and all of us are dorks.

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Ben and Sam preview the Pirates’ season with Pittsburgh Tribune-Review Pirates beat writer Travis Sawchik, and Jeff talks to Pat Lackey of Where Have You Gone Andy Van Slyke? (at 23:58).

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I wouldn’t recommend watching a large percentage of the little spring-training videos they make available at MLB.com, but this is a fun one. Members of the Indians rotation are asked which individual pitch they’d like to borrow from one of their peers. The responses, arranged in my own preferred order for editorial purposes:

• Josh Tomlin: Carlos Carrasco’s changeup
• Corey Kluber: Danny Salazar’s changeup
• Carlos Carrasco: Corey Kluber’s curveball
• Cody Anderson: Corey Kluber’s curveball
• Danny Salazar: Corey Kluber’s slider, by which he means curveball

It’s a gifted rotation, blessed with a number of elite individual weapons, but you see all the support for Kluber’s hook. By how fast it goes, and by the way that it moves, it’s a pitch unlike almost any other, and it’s been a huge part of Kluber’s emergence. That’s easy to see in the numbers we have. What’s easy to see, as well, is that Kluber throws a cutter that’s been roughly as valuable as the curve. Kluber actually has two elite pitches. What if he pitched like it?

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As we become accustomed to a steady diet of spring-training baseball, 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 all the various infield positions — plus left field and center. Today, let’s complete our tour of the outfield by focusing on right fielders.

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. Let’s start with the AL RFs.

Ball-In -Play Overview – AL RF

Name	Avg MPH	FB/LD MPH	GB MPH	POP%	FLY%	LD%	GB%	CON	K%	BB%	OPS+	Pull%	Cent%	Opp%
N.Cruz	92.80	97.25	88.71	3.5%	30.5%	20.4%	45.7%	195	25.0%	9.0%	160	38.6%	36.5%	24.8%
J.Bautista	93.83	95.79	92.41	7.0%	41.8%	13.9%	37.3%	121	15.9%	16.5%	149	53.3%	28.1%	18.7%
JD.Martinez	91.86	95.95	85.66	2.1%	41.4%	22.3%	34.2%	181	27.1%	8.1%	140	41.1%	34.7%	24.2%
Springer	89.64	93.75	85.61	1.1%	29.0%	24.5%	45.4%	141	24.2%	11.1%	126	34.2%	38.7%	27.1%
Choo	91.63	95.86	88.52	0.7%	27.8%	20.7%	50.9%	136	22.5%	11.6%	125	44.1%	34.2%	21.7%
Beltran	91.63	93.76	90.03	3.3%	39.6%	21.6%	35.6%	111	16.0%	8.5%	121	44.4%	35.6%	20.1%
Reddick	89.00	91.74	86.82	3.7%	36.9%	21.0%	38.4%	94	11.2%	8.4%	113	35.6%	35.3%	29.1%
C.Young	85.13	89.06	84.18	8.9%	38.1%	17.4%	35.6%	110	20.5%	8.4%	111	58.8%	24.4%	16.8%
Trumbo	92.86	94.22	93.22	5.0%	35.3%	18.0%	41.6%	130	24.2%	6.6%	108	37.1%	32.9%	30.0%
Calhoun	86.87	91.23	81.86	2.5%	32.9%	22.8%	41.8%	115	23.9%	6.6%	104	42.6%	34.3%	23.1%
Souza Jr.	89.16	95.06	84.68	3.6%	31.1%	20.0%	45.3%	140	33.8%	10.8%	99	45.9%	34.2%	19.9%
Moss	89.39	94.48	83.25	3.1%	44.0%	20.4%	32.5%	118	28.1%	9.3%	90	49.4%	30.6%	20.1%
A.Garcia	88.91	92.68	85.77	1.7%	25.0%	24.5%	48.8%	100	23.5%	6.0%	89	36.1%	40.4%	23.6%
T.Hunter	89.09	93.00	85.61	3.4%	30.9%	17.3%	48.4%	90	18.5%	6.2%	89	40.9%	35.9%	23.3%
Chisenhall	87.25	90.14	86.07	8.3%	31.5%	19.5%	40.6%	84	19.1%	6.4%	78	40.2%	33.8%	26.0%
Rios	88.81	89.72	88.57	2.8%	35.2%	22.2%	39.8%	76	16.3%	3.6%	73	42.6%	35.8%	21.6%
AVERAGE	89.87	93.36	86.94	3.8%	34.4%	20.4%	41.4%	121	21.9%	8.6%	111	42.8%	34.1%	23.1%

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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