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Evaluating the 2016 Prospects: Pittsburgh Pirates

March 22, 2016

EVALUATING THE PROSPECTS 2016
Angels
Astros
Athletics
Blue Jays
Braves
Brewers
Cardinals
Cubs
Diamondbacks
Dodgers
Giants
Indians
Mariners
Marlins
Mets
Nationals
Orioles
Padres
Phillies
Pirates
Rangers
Rays
Red Sox
Reds
Rockies
Royals
Tigers
Twins
White Sox
Yankees

The Pirates have put together a stunning collection of players who possess strong hit-tool projections, sort of reminiscent of the strategy attributed to the Cardinals’ scouting and development heads in the last 5-10 years. Even just looking at the last three drafts, they have taken five hitters in the various first rounds – Kevin Newman, Ke’Bryan Hayes, Cole Tucker, Austin Meadows and Reese McGuire – and all but Tucker project for average-or-better hit tools as their likely future grades. In fairness, there’s a case to be made that Tucker deserves a 50 as well.

In recent years the Pirates’ player-development system has not been able to get the most out of many of their positional players’ power potentials, a trend that a number of their current prospects will have to hope changes course. You could throw pitcher injuries into the mix as well, but that may only be more apparent because of the dramatic focus on acquiring top-tier hitters over pitchers in the draft and international markets.

There shouldn’t be a ton of surprise rankings on this list, except for perhaps Reese McGuire. He looked like a totally different player in the Arizona Fall League, and it was substantial enough to buy into more of his offensive potential than I have before. Overall, this is just a solid system with plenty of front-line talent and a great mix of upside and floor filling out the next two tiers. It’s an exciting time to watch Pirates’ prospects.

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2016 Positional Power Rankings: Second Base

by Dave Cameron

March 22, 2016

2016 Positional Power Rankings Series

It’s our turn to Positionally Power Rank the second baseman. If you’re not familiar with this series, read the introduction, and then come back for a walk through the league’s most homogenous spot on the field. By which I mean that the keystone position in MLB is an eclectic mix of young contact hitters, aging contact hitters, contact hitters with some power, and Jonathan Schoop. But hey, let’s sort out which of these contact hitters are better than the others, and we’ll do that right now.

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2015 Starting Pitcher Ball-in-Play Retrospective – NL East

by Tony Blengino

March 22, 2016

Opening Day lies just beyond the horizon, though the weather forecasts in many parts of the country don’t seem to want to pay attention. Over the last few weeks in this space, we took a position-by-position look at the ball-in-play (BIP) profiles of 2015 regulars and semi-regulars to gain some insight into their potential performance moving forward. Next, we’re going to take a similar approach with regard to starting pitchers, division by division. We’ll begin today with the NL East.

First, some ground rules. To come up with an overall player population roughly equal to one starting rotation per team, the minimum number of batted balls allowed with Statcast readings was set at 243. Pitchers will be listed with their 2015 division mates; those who were traded during the season will appear in the division in which they compiled the most innings. Pitchers are listed in “tru” ERA order. For those who have not read my previous articles on the topic, “tru” ERA is the ERA pitchers “should” have compiled based on the actual BIP frequency and authority they allowed relative to the league. Here we go:

Starting Pitcher BIP Profiles – NL East

Name	AVG MPH	FB/LD MPH	GB MPH	POP %	FLY %	LD %	GB %	ADJ C	K %	BB %	ERA –	FIP –	TRU –
DeGrom	87.53	90.60	85.66	3.1%	31.6%	20.9%	44.4%	85	27.3%	5.1%	65	69	66
Scherzer	87.26	90.88	83.85	5.9%	39.5%	18.6%	36.0%	98	30.7%	3.8%	72	71	66
Harvey	87.74	90.35	85.91	3.5%	32.6%	17.9%	46.0%	83	24.9%	4.9%	69	78	68
Syndergaard	86.06	89.08	84.88	3.5%	30.1%	19.9%	46.5%	93	27.5%	5.1%	83	83	70
Strasburg	88.95	92.11	87.48	4.9%	29.4%	23.4%	42.2%	102	29.6%	5.0%	89	72	72
S.Miller	87.18	90.54	85.39	3.0%	31.1%	18.2%	47.7%	76	19.9%	8.5%	77	88	81
Hamels	88.16	91.33	86.30	3.8%	27.6%	20.9%	47.7%	105	24.4%	7.1%	94	89	89
Colon	89.07	92.05	86.77	2.8%	34.1%	20.8%	42.3%	101	16.7%	2.9%	107	98	95
Zimmermann	88.52	91.89	85.82	4.5%	31.8%	21.7%	42.0%	105	19.7%	4.7%	94	96	95
Niese	88.71	92.05	86.65	1.2%	23.5%	20.8%	54.5%	90	14.7%	7.1%	106	113	99
G.Gonzalez	88.58	92.28	85.99	1.2%	25.5%	19.5%	53.8%	105	22.3%	9.1%	97	78	99
Teheran	89.27	92.26	86.76	3.5%	32.8%	24.0%	39.7%	105	20.3%	8.7%	104	113	103
Roark	86.20	91.26	81.99	2.2%	28.4%	21.7%	47.8%	101	15.0%	5.6%	112	121	104
Latos	88.60	93.65	84.06	2.3%	29.6%	24.2%	43.9%	114	20.2%	6.5%	127	95	105
Koehler	89.98	93.58	87.98	2.5%	33.1%	18.4%	46.0%	99	17.1%	9.6%	105	116	107
A.Wood	87.92	91.00	85.76	2.4%	25.1%	23.0%	49.5%	107	17.4%	7.4%	98	95	109
Fister	88.22	91.04	85.89	1.2%	32.9%	21.3%	44.6%	106	14.0%	5.4%	107	117	111
Phelps	89.76	91.64	87.33	3.1%	32.1%	23.0%	41.8%	114	16.0%	6.9%	115	103	117
Harang	90.67	93.16	88.61	5.3%	38.4%	20.2%	36.1%	110	14.4%	6.8%	125	124	118
Wisler	90.66	93.40	86.89	5.9%	37.3%	23.2%	33.6%	118	15.1%	8.4%	121	126	128
J.Williams	89.13	92.57	85.99	2.3%	27.8%	22.8%	47.1%	121	13.4%	6.2%	149	134	129
W.Perez	90.32	93.69	87.96	1.1%	27.7%	20.3%	50.9%	126	14.2%	9.9%	123	125	141
AVERAGE	88.57	91.84	86.09	3.1%	31.0%	21.1%	44.7%	103	19.8%	6.6%	102	100	99

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 traditional ERA -, FIP -, and “tru” ERA -. Each pitchers’ Adjusted Contact Score (ADJ C) is also listed. Again, for those of you who have not read my articles on the topic, Unadjusted Contact Score is derived by removing Ks and BBs from opposing hitters’ batting lines, assigning run values to all other events, and comparing them to a league average of 100. Adjusted Contact Score applies league-average production to each pitchers’ individual actual BIP type and velocity mix, and compares it to league average of 100.

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2016 Pitcher Projections Visualization

by Sean Dolinar

March 22, 2016

Last week, I created a visualization of offensive stat projections for our Depth Charts, which use a blend of ZiPS and Steamer projections adjusted for playing time. It reflects the updates we make to the Depth Charts with injuries and roster moves. Below is its counterpart — pitching stats projections.

For our pitching visualization, I’ve included eight different stats we commonly use at FanGraphs: ERA, FIP, K/9, BB/9, HR/9, BABIP, RA9-WAR and WAR. For those not familiar with the different versions of pitching WAR FanGraphs hosts, our primary WAR calculations are based on a modified version of fielding independent pitching (FIP), which relies on strikeouts, walks, infield flies and home runs. RA9-WAR is based on runs allowed per nine innings. Each provides a different perspective on a value of a pitcher. I also chose to include batting average on balls in play (BABIP) this year to illustrate differences in expected BABIP, since some pitchers are able to affect the quality of contact of balls that are put into play.

The players are grouped into three categories: All Pitchers, As Starters, and As Relievers. These classifications are pulled from the playing time allotted to pitchers on the Depth Charts. A pitcher can be on both the starters graph and relievers graph; the number of inning he is projected to pitch will be different, along with WAR stats which are dependent on playing time. For “All Pitchers” playing time will be combined.

The circles on the graph represent an individual pitcher. The yellow line is the roster’s combined stat, which is specific to the category of pitcher you select. The gray bars represent the 25th and 75th percentile of the players shown on the graph. This illustrates the middle 50% of the pitchers available on the roster.

The data will update to account for roster moves consistently until the beginning of the season.

ERA

FIP

K/9

BB/9

HR/9

BABIP

RA9-WAR

WAR

All Pitchers

As Starters

As Relievers

2016 MLB Pitching Projections

FanGraphs Depth Charts

August Fagerstrom FanGraphs Chat — 3/22/16

by August Fagerstrom

March 22, 2016