2015 Relief Pitcher Ball-in-Play Retrospective – AL

Over the last few weeks in this space, we’ve conducted a ball-in-play based analysis of position players’ and starting pitchers’ 2015 performance, the most recent post featuring an examination of starting pitchers in the AL West. Next, we’ll take a similar look at relief pitchers. It’s admittedly a little dicey to evaluate relief pitchers in this manner. The sample sizes are much smaller, and filled with more noise. Still, it’s a worthwhile exercise that can show us the different manners in which closers, set-up men, et al, get it done.

First, some background on the process. I identified the 214 relief pitchers from both leagues who yielded the most batted balls in 2015, making sure that all team save leaders were included in the sample. From that group, I selected 28 pitchers from each league for further scrutiny. Pitchers are listed with their 2015 league 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:

Relief Pitcher BIP Profiles – AL
AVG MPH FB/LD MPH GB MPH POP% FLY % LD% GB% ADJ C K% BB% ERA- FIP- TRU-
A.Miller 86.13 86.66 86.31 3.3% 30.0% 18.3% 48.3% 80 40.7% 8.1% 50 51 44
Uehara 85.92 88.23 80.50 9.0% 47.0% 17.0% 27.0% 59 29.4% 5.6% 53 61 44
O’Day 84.88 85.89 86.60 5.2% 39.6% 20.1% 35.1% 67 31.9% 5.5% 37 59 45
Britton 89.93 94.83 87.93 0.0% 9.5% 11.4% 79.1% 71 31.2% 5.5% 47 48 49
Fields 88.18 91.81 83.06 6.7% 40.9% 18.3% 34.2% 64 32.1% 9.1% 88 53 50
C.Smith 88.08 88.75 88.45 1.3% 16.9% 17.0% 64.8% 75 32.4% 7.8% 60 54 52
Cecil 87.86 88.76 86.94 4.0% 25.4% 19.0% 51.6% 82 32.7% 6.1% 61 57 54
W.Davis 85.18 90.24 80.41 4.6% 36.5% 20.5% 38.4% 74 31.1% 8.0% 23 57 55
Gregerson 86.85 92.75 84.31 2.4% 20.8% 16.5% 60.4% 71 24.7% 4.2% 77 69 56
Street 86.82 89.33 83.15 1.7% 43.7% 20.1% 34.5% 58 22.4% 7.8% 83 95 57
Betances 84.04 90.25 81.07 3.9% 27.7% 20.6% 47.7% 93 39.5% 12.1% 37 59 58
Lowe 87.91 90.47 84.78 2.9% 29.5% 27.3% 40.3% 83 28.4% 5.6% 49 64 61
C.Allen 87.93 89.00 88.38 6.3% 34.8% 25.9% 32.9% 94 34.6% 8.7% 75 45 62
Kela 88.81 91.16 88.66 3.8% 25.0% 20.5% 50.6% 80 28.0% 7.4% 56 63 63
Madson 88.77 93.94 85.13 2.3% 29.3% 13.5% 55.0% 75 23.4% 5.7% 53 77 63
Soria 86.84 88.47 84.76 2.7% 32.5% 22.5% 42.3% 72 23.5% 7.0% 64 93 64
Hendriks 90.45 91.23 89.74 3.9% 27.2% 22.6% 46.3% 96 27.2% 4.2% 72 52 69
Osuna 88.18 88.96 88.26 3.9% 42.2% 19.7% 34.3% 93 27.7% 5.9% 63 73 69
Robertson 89.46 92.66 88.08 3.4% 30.8% 30.2% 35.6% 120 34.4% 5.2% 84 60 70
Perkins 91.34 92.18 93.14 5.2% 39.6% 21.5% 33.7% 89 22.7% 4.2% 82 94 73
Rodney 84.74 89.98 81.48 3.9% 27.6% 18.0% 50.6% 75 20.9% 10.5% 123 125 76
W.Harris 87.14 90.38 84.41 1.1% 28.6% 19.8% 50.5% 91 24.6% 8.0% 47 89 77
Herrera 85.85 91.13 83.02 1.0% 31.6% 22.6% 44.7% 84 22.4% 9.1% 67 86 79
G.Holland 87.30 91.08 84.12 6.1% 22.8% 21.9% 49.1% 81 25.4% 13.5% 94 82 80
Tolleson 88.15 91.56 84.06 4.5% 32.4% 20.7% 42.4% 103 25.5% 5.7% 70 83 80
Boxberger 86.59 88.75 85.30 5.6% 36.9% 21.3% 36.3% 102 27.3% 11.8% 96 108 87
J.Smith 90.61 92.96 89.29 1.6% 23.1% 23.2% 52.1% 101 21.0% 7.0% 94 81 90
Petricka 86.53 90.71 85.59 0.0% 17.1% 17.7% 65.2% 91 15.0% 8.2% 89 83 97

First, a little background. The larger group of 214 relievers had a cumulative strikeout rate of 22.2% and walk rate of 8.2%. Both rates are higher than the comparable marks for starters (19.8% and 7.0%, respectively). The larger group of relievers also conceded less authoritative contact than starters, allowing lesser overall (88.02 mph for relievers, 88.46 mph for starters), FLY/LD (91.24 vs. 91.78) and grounder (85.76 vs. 86.30) authority. With regard to BIP frequency, relievers outpaced starters in the key grounder rate category by 45.6% to 45.2%, and matched them in pop-up rate (3.2%).

The subset of relievers listed above generally represents the cream of the relief crop. 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 pitcher’s 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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Bryce Harper Is Catching Up to Mike Trout

Since the 2012 season, the question of the best player in baseball has been pretty boring. Mike Trout busted onto the scene with a +10.3 WAR season as a 20 year old, and he’s since dominated the sport in a way that has rarely been seen in the game’s history. There were good players having great seasons in Trout’s shadow, but no one put up any real serious challenge to the idea that they were a better player than Trout. But now, that might be changing, as Bryce Harper is putting together a realistic run at the title of the best player in baseball.

Obviously, Harper’s 2015 season was outstanding, as he won the NL MVP by wrecking opposing pitchers on a daily basis. But because of how good he was last year, it can be easy to forget that Harper is still just 23 years old, and he appears to be getting even better.

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Dan Szymborski FanGraphs Chat – 4/18/16

12:03
Dan Szymborski: *cough*

12:03
Dan Szymborski: Don’t worry, I won’t be inserting my coughs.

12:03
Chris Hatcher: On a scale from “blow it up and start over” to ” they’ll figure it out and be a strength”, how concerned should Dodgers fans be about me and my ‘pen mates?

12:05
Dan Szymborski: It’s a little late to blow it up. And they *still* have the #3 bullpen in the RoS projections – even if you apply some kind of suck factor and say they’re “only” 10th or something, how would they build a better bullpen than the #10 on April 18th?

12:05
Tom: Any idea why Tulo has bad offensive numbers since he got the jays?

12:05
Dan Szymborski: 2015 wans’t alarmingly worse given the sample size

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Domingo Santana Is Making the George Springer Adjustment

If George Springer’s rookie season was like a breath of fresh air, then last year represented a sigh of relief. The breath of fresh air, because Springer was not only great, but great in such a unique way. The sigh of relief because Springer’s uncommon profile made him an outlier in some potentially worrisome areas, and last year, he patched up his most glaring weaknesses. Namely, he made more contact, and while that didn’t boost his production, it didn’t hurt his production either, and it also made him feel like a much more certain thing. George Springer comes with fewer caveats now. His production is easier to explain.

I’ve compared Domingo Santana to Springer before. That comparison comes with the important disclaimer that Santana isn’t nearly as fast as Springer, nor does he appear to be as useful a defender, and so he’s never likely to be as valuable a package as Springer. But at the plate, they sure look similar, and Springer at the plate is one hell of a threat, as is. They’re both massive, freak athletes who swing and miss a ton but have enough power to where pitchers feel compelled to work around the zone, and both have good enough eyes to take their walks. They’re nearly identical in their aggression, swing plane, and penchant for going the other way.

And now, 2016 Santana is furthering the comp by making the same adjustment made by 2015 Springer. When I wrote that comparison piece last month, I included this paragraph near the end:

While being unique is interesting from the writer’s prospective, it also means that essentially nobody else is succeeding in the way Santana is attempting to, and that’s not exactly optimistic. It’s hard to be a big league player making as little contact as Santana does, and it’s hard to see Santana being able to put this all together and keep it up without making some adjustments to increase the contact rate, just like Springer did last year.

And now, for a few relevant statistics, comparing players with at least 50 plate appearances in each of the last two years to themselves:

Largest improvement in contact rate

  1. John Jaso, +14%
  2. Domingo Santana, +11%
  3. Joe Mauer, +10%

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KATOH Projects: Texas Rangers Prospects

Previous editions: Arizona / Atlanta / Baltimore / Boston / Chicago AL / Chicago NL / Cincinnati  / Cleveland / Colorado / Detroit / Houston / Kansas City / Los Angeles (AL) / Los Angeles (NL)Miami / Milwaukee / Minnesota / New York (AL) / New York (NL)  / Oakland / Philadelphia / Pittsburgh / San Diego / San Francisco / Seattle / St. Louis / Tampa Bay.

Last week, lead prospect analyst Dan Farnsworth published his excellently in-depth prospect list for the Texas Rangers. In this companion piece, I look at that same Texas farm system through the lens of my recently refined KATOH projection system. The Rangers have the fourth-best farm system in baseball according to KATOH.

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. Nomar Mazara, OF (Profile)

KATOH Projection: 8.8 WAR
Dan’s Grade: 55+ FV Read the rest of this entry »


Crowdsourcing Radio Broadcasters: Names and Places

It both seems like and also actually was just last week that the present author announced his intentions of revisiting the broadcaster rankings which appeared on this site roughly four years ago. The purpose of those rankings? To place a “grade” on each of the league’s television and radio broadcast teams — a grade intended to represent not necessarily the objective quality or skill of the relevant announcers, but rather the appeal those announcers might have to the readers of this site. By way of MLB.TV feeds, the typical major-league telecast offers four distinct audio feeds — which is to say, the radio and television commentary both for the home and road clubs. The idea of these broadcast rankings was to give readers an opportunity to make an informed decision about how to consume a telecast.

The results of that original exercise have been useful as a complement to the dumb NERD scores published by the author in these pages. Four years later, however, those results have become much less useful. In the meantime, a number of the broadcast teams cited in that original effort have changed personnel. It’s possible that the tastes of this site’s readers have changed, also.

Last week’s post represented the first step towards a new set of broadcaster rankings — namely, to assemble an actual list of all baseball’s main television broadcast teams. The current post is the natural complement: an attempt to identify all the relevant members of baseball’s radio broadcasts. The information here is taken from a combination of Wikipedia and MLB.com, but would benefit from readers who possess a more intimate knowledge of how each club’s broadcasts are executed.

Again, the idea is to identify the broadcasters most frequently found in each team’s booth in 2016. While many clubs have occasional color commentators and guest announcers, isolating the most regular contributors will make this process more efficient, if perhaps slightly less nuanced.

Below is the preliminary list. Teams marked with a “(?)” are the ones about which I’m least sure.

Arizona: Greg Schulte, Tom Candiotti

Atlanta: Jim Powell, Don Sutton

Baltimore: Joe Angel, Jim Hunter

Boston: Joe Castiglione, Tim Neverett

Chicago (AL): Ed Farmer, Darrin Jackson

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Evaluating the 2016 Prospects: Toronto Blue Jays

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 top of the Blue Jays system saw an almost complete overhaul with the trades and promotions of the past year. It obviously has been for the best, as many of the organization’s first-year contributors played well last season — even if the minor leagues appear a little barren at a quick glance. Fortunately, the system remains filled with a lot of upside at the lower levels, and recent drafts have only helped to strengthen that depth, even if it is of the higher risk variety.

Anthony Alford is the only impact bat I see, with a few potentially useful position players in above the 45+ future-value line. Rowdy Tellez and Richard Urena both have upside with the bats, but each has enough question marks to keep them from being reliable prospects to project at the big-league level. I still like Max Pentecost’s chances of becoming an average producer, though that possibility is very dependent on his ability to return to health.

The pitching side is a bit stronger at the moment, headlined by Conner Greene and Sean Reid-Foley. I like both of their chances of remaining starters and being solid contributors, and there are a slew of lower-level hurlers with interesting qualities that could jump up this list by next year.

The strength of this system may be in the 40+ FV players and those who are just off the list. That group is filled with tremendous raw athletes, bounceback candidates and recent draftees with moderate upsides. While those kinds of profiles are risky for counting on any one prospect, the sheer volume of guys they have in those categories bodes well for a couple of them putting things together and moving toward higher end of the list.

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Sunday Notes: Russell, Rays, Orioles, Barney, Biagini, more

The Pittsburgh Pirates fired John Russell following the 2010 season and replaced him with Clint Hurdle. It’s hard to argue with the results. The perennial also-rans went on to become one of the best teams in the National League.

Hurdle deserves the praise he’s received. Given a second opportunity to manage — Colorado had canned him in 2009 — he’s made shrewd in-game moves and overseen a cohesive clubhouse. Along the way, he has adroitly balanced his old-school instincts with the data-driven philosophy of the front office.

Could the Pirates have turned the corner had they not made the change? It’s not implausible. In many respects, Russell and Hurdle are the same type of manager. According to Pirates GM Neal Huntington, there are “similarities in their foundations,” and he described Russell as “a quality person (with a) willingness to embrace different schools of thought.”

He sees differences as well. In Huntington’s opinion, their “execution of the role” isn’t the same, and Hurdle represented “a different voice with a different approach and skill set.”

Russell — now the bench coach in Baltimore, under Buck Showalter — agrees that a different voice can be needed. That doesn’t mean he feels it’s always necessary. Read the rest of this entry »


The Best of FanGraphs: April 11-15, 2016

Each week, we publish north of 100 posts on our various blogs. With this post, we hope to highlight 10 to 15 of them. You can read more on it here. The links below are color coded — green for FanGraphs, brown for RotoGraphs, dark red for The Hardball Times and blue for Community Research.
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FanGraphs Audio: A Great Catastrophe with Jeff Sullivan

Episode 646
Jeff Sullivan is a senior editor at FanGraphs. He’s also the wholly endangered guest on this edition of FanGraphs Audio.

This episode of the program is sponsored by SeatGeek, which site removes both the work and also the hassle from the process of shopping for tickets.

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 1 hr 19 min play time.)

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