Dan Straily is on his way to becoming a Marlin. According to reports, the Reds have agreed to deal the soft-tossing, veteran righty for a trio of prospects. We’ll have more on the trade in a bit. For the moment, here’s what my KATOH system has to say about the players who are newly employed by the Cincinnati Reds organization. KATOH denotes WAR forecast for first six years of player’s major-league career. KATOH+ uses similar a methodology with consideration also for Baseball America’s rankings.

*****

Austin Brice, RHP (Profile)

KATOH: 0.9 WAR
KATOH+: 0.9 WAR

After an underwhelming tenure as a starter in the minors, Brice had success in the bullpen last year. Following a move to the pen in June, he posted a 2.10 ERA and 2.90 FIP between Double-A and Triple-A, earning him a September call-up. Brice’s recent minor-league numbers suggest he’ll have a future in the show, even if it’s a short-lived one. KATOH gives him a 50% chance of pitching in the majors again. But as a soon-to-be 25-year-old relief prospect without much track record, he isn’t likely to make a big impact. KATOH considered Brice to be the 10th-best prospect in the Marlins’ system, which says more about the Marlins’ system than it does about Brice.

To put some faces to Brice’s statistical profile, let’s generate some statistical comps for the hard-throwing righty. I calculated a weighted Mahalanobis distance between Brice’s performance this year and every Double- and Triple-A season since 1991 in which a pitcher recorded at least 350 batters faced. In the table below, you’ll find the 10 most similar seasons, ranked from most to least similar. The WAR totals refer to each player’s first six seasons in the major leagues. A lower “Mah Dist” reading indicates a closer comp.

Read the rest of this entry »

Below is an analysis of the prospects in the Cincinnati Reds farm system. Scouting reports are compiled with information provided by industry sources as well as from my own observations. The KATOH statistical projections, probable-outcome graphs, and (further down) Mahalanobis comps have been provided by Chris Mitchell. For more information on thes 20-80 scouting scale by which all of my prospect content is governed you can click here. For further explanation of the merits and drawbacks of Future Value, read this. -Eric Longenhagen

The KATOH projection system uses minor-league data and Baseball America prospect rankings to forecast future performance in the major leagues. For each player, KATOH produces a WAR forecast for his first six years in the major leagues. There are drawbacks to scouting the stat line, so take these projections with a grain of salt. Due to their purely objective nature, the projections here can be useful in identifying prospects who might be overlooked or overrated. Due to sample-size concerns, only players with at least 200 minor-league plate appearances or batters faced last season have received projections. -Chris Mitchell

Other Lists
NL West (ARI, COL, LAD, SD, SF)
AL Central (CHW, CLE, DET, KC, MIN)
NL Central (CHC, CIN, PIT, MIL, StL)
NL East (ATL, MIA, NYM, PHI, WAS)
AL East (BAL, BOS, NYY, TB, TOR)

55 FV Prospects

Relevant/Interesting Metrics
Dramatically increased ISO (.170 as a sophomore, .243 as junior) at University of Tennessee in 2016 and stole 25 bases at an 86% clip.

Scouting Report
A young-for-the-class SEC hitter with a long track record of success, Senzel was the most polished bat available in the 2016 draft. I saw him early in the year during a four-team round robin in Arizona and thought he’d go somewhere in the top 10-15 picks. While facing pitching far beneath the quality of arms he’d see later in the year during SEC play, Senzel finished the weekend 8-for-13 with four doubles, six walks, five of those on the final day of play. Despite my own enthusiasm, when a scout told me they thought he had an outside shot at going 1-1, I scoffed. Senzel was drafted No. 2 overall by Cincy in June. There are probably a few reasons for this, beyond a potential misevaluation of Senzel’s talent. Prospects ahead of Senzel on my board at that time (such as Jason Groome, Delvin Perez, Alec Hansen) all saw their stocks dip for one reason or another during the spring, while Senzel continued to rake. Moreover, he was one of the safest prospects in a draft class without huge, risk-worthy talent up top.

Read the rest of this entry »

While the 2016 campaign is over and the flurry of moves after the season has come to a halt for the moment, a whole year’s worth of data remains to be examined. Today’s post is an easy one and a fun one. Let’s find the best pitches that were thrown regularly last year.

Before we begin: the word “results” appears in the headline, but I’m not going to use results judged by things like singles and doubles and the like. The samples gets pretty small if you chop up the ball-in-play numbers on a single pitch, and defense exerts too much of an influence on those numbers. So “results” here denotes not hit types, but rather whiffs and grounders.

I’ve grouped all the pitches thrown last year, minimum 75 for non-fastballs, 100 for fastballs. I combined knuckle and regular curves, and put split-fingers in with the changeups. So the sample per pitch type is generally around 300 — a lot less for cutters (89) and a bunch more for four seamers (500) — but generally around 300 pitches qualified in each category. Then I found the z-scores for the whiff and ground-ball rates on those pitches. I multiplied the whiff rate z-score by two before adding it to the ground-ball rate because I generally found correlations that were twice as strong between whiff rates and overall numbers like ERA and SIERA than they were for ground-ball rates.

The caveats are obvious. Pitches work in tandem, so you may get a whiff on your changeup because your fastball is so devastating. This doesn’t reward called strikes as much as swinging strikes, so it’s not a great measure for command. On the other hand, there isn’t a great measure for command. By using ground-ball rate instead of launch-angle allowed, we’re using some ball-in-play data and maybe not the best ball-in-play data.

But average-launch-angle allowed is problematic in its own way, and ground-ball rate is actually one of the best ball-in-play stats we have — it’s very sticky year to year and becomes meaningful very quickly. Whiff rates are super sexy, since a swing and a miss represents a clear victory for the pitchers over the batter — and also because there’s no room for scorer error or bias in the numbers. And while the precise way in which pitches work in tandem remains obscure in pitching analysis, we can still learn something from splitting the pitches up into their own buckets.

Read the rest of this entry »

Bryan Price doesn’t believe in limiting pitchers. That much is clear based on his response to a question I posed during last week’s Winter Meetings. I asked the Cincinnati Reds manager — and former minor- and major-league pitching coach — if there are any changes he’d like to see in the way the organization develops pitchers.

I expected a more cautious answer than I received. Rather than pussyfoot, Price proffered a strong opinion. The way he sees it, babying pitchers in the minor leagues compromises their ability to work deep into games once they reach Cincinnati. Not only that, it can hinder their chances of becoming a top-notch starter.

Note: Price’s comments, which were delivered in a group setting, have been edited for clarity and continuity.

———

Bryan Price on developing pitchers: “The big challenge for me, personally, is a world where we want pitchers to throw less. I think they need to throw more. And not just necessarily bulk innings; I think pitchers need to throw more on the side. We have pitchers come through our system who throw bullpen sides of 25 to 30 pitches when we get them. I would like to see them have a bigger workload on their side days. I would like to see some of them throw twice between starts. I would like to see us build our starting pitchers to where they can carry a heavier workload in the minor leagues.

Read the rest of this entry »

The 2016 season featured the second-most home runs in baseball’s history. Though a few people around baseball want to attribute it to the placement of power hitters higher in the lineup or better coaching based on better data, the evidence that both exit velocity and home runs per contact are up across the league refutes the first, and the evidence of the latter is minor. It’s a bit of an open mystery, but it’s certainly possible that the ball is different now.

In any case, the fact that homers are up is irrefutable. And it’s on the game to adjust. So I asked many of baseball’s best managers a simple question: with home runs up, how have you adjusted how you approach the game? Lineups, rotations, bullpens, hooks: is anything different for them today than it was two years ago?

*****

Terry Collins, New York Mets: No, really doesn’t. The game has changed, that’s the game now: home runs. And we’re lucky we got a few guys who can hit ’em. That’s where it’s at. As I said all last year, our team was built around power, so you sit back and make sure they have enough batting practice and be ready to start the game. We’ve got a good offensive team. Neil. Getting Neil Walker back, that’s big. David back and Ces and Jay and Granderson. We got a bench full of guys that could be everyday players. We’re pretty lucky.

I watched the playoffs, too, and I know what you’re talking about. I talked to Joe Maddon a couple days ago about how the playoffs may change and he said, ‘We didn’t have your pitching. I’ll leave ’em in.’

Read the rest of this entry »

Some people track the passing of time through watching their children. Other people track the passing of time by looking at what time it is, and comparing that to a previous time, from back in the past. I tend to track the passing of time by thinking in baseball terms. I can’t really help it, and sometimes it takes me by surprise. It feels like just yesterday that Billy Hamilton was one of the most exciting and polarizing prospects in the sport. Now Hamilton is the subject of some trade rumors, because he’s entering his arbitration years and the Reds aren’t going to be good any time soon. Life comes at you fast. (Faster than Billy Hamilton!) (But not actually that fast.)

I don’t need to explain Hamilton to anybody. At least, not anybody on FanGraphs. Runs fast, doesn’t hit. It feels like a somewhat typical profile. Maybe thinking about Hamilton causes you to think about Willy Taveras. We’ve all seen players kind of like this. I’d like to demonstrate that Hamilton is particularly extreme. While Hamilton has maybe disappointed a few observers, he’s been his own sort of player.

Read the rest of this entry »

I’ve been attempting recently to better understand changeups through the prism of spin. A relationship might exist, but it’s difficult to identify. I’m working on it — and, if I find anything, I’ll share it here. In the meantime, though, there still remain some dependable pitch-level metrics which can reveal the quality of a changeup — namely, drop, fade, and velocity difference. While it’s true that there are a multiple pathways to success for the changeup, those which are notable by these criteria also tend to be notable for their effectiveness. Movement, for example, is what allows Zack Greinke’s hard change to work. The velocity gap between the change and the fastball, meanwhile, becomes more important for those changeups which feature less of Greinke’s signature movement.

Over the course of this past season, a few changeups improved in these regards. We should take notice because, even in today’s era of spin, a nasty changepiece can really pull an arsenal together.

Read the rest of this entry »

Shortly before Thanksgiving, I wrote an article about how Chris Sale had been hurt last season by lousy receivers. That was an interesting observation from the data, but it wasn’t the only interesting observation from the data. According to Baseball Prospectus, Sale lost the second-most runs from his pitch-framers. Brandon Finnegan, however, pitched to the worst strike zone, his framers costing him an estimated 7.8 runs. Meanwhile, from the same source, Madison Bumgarner pitched to the best strike zone, his framers helping him by an estimated 11.0 runs. That’s a 19-run difference from catchers alone.

Maybe you don’t believe the spread was really that big. It’s easy to believe there was some spread — Bumgarner pitched almost exclusively to Buster Posey, while Finnegan pitched to Tucker Barnhart and Ramon Cabrera. One should also be wary of putting everything on the catchers. Pitchers with better command are easier to receive than pitchers with worse command, and Bumgarner throws with greater accuracy than Finnegan does. So, in part, the zones were the pitchers’ fault. But one thing we know for sure is that, in the end, Bumgarner’s strike zone was more generous. Arguably the most generous. So here is how the Bumgarner and Finnegan called strike zones compare:

Pretty interesting! Here is an alternate view of the same information. Note this is also from the catcher’s perspective. This shows called-strike rates out of all called pitches:

Both pitchers are southpaws. Bumgarner got the far better zone high. He got the far better zone arm-side. He got the far better zone low. Glove-side, it’s about equal, if not in favor of Finnegan. That’s of some note — Finnegan wasn’t losing strikes everywhere. It seems like he frequently tried to target that glove-side edge, but he’d often miss, and his catchers were probably worse at receiving missed locations. So it goes. It’s another example of a point to be debated. Bumgarner got the way more generous strike zone than Finnegan did. Some of this is because Bumgarner hit his spots better than Finnegan did. That reflects well on Bumgarner’s talent! But with an automated strike zone, the gap in performance between the pitchers would’ve been narrowed. Bumgarner’s zone would’ve been worse, and Finnegan’s zone would’ve been better. You either like the way things are, or you don’t. They’ve been this way forever, even if we’ve only recently taken to measuring it.

An estimated gap of 18.8 runs. This compares the two extremes, but there was about the same difference in WAR last year between Max Scherzer and Carlos Martinez. Individual ball and strike calls seldom make a big difference in the moment, but, holy hell, can the differences ever add up.

Some time ago, in another InstaGraphs post, I mentioned something that could potentially become true about the 2016 Reds. We spend a lot of time writing about things that could potentially become true, and inevitably, a lot of those paces fall off. There are reasons for that, and that would be a subject for another post. But the 2016 numbers are official now, dammit. There’s no more “on pace for;” there only is. Here is something that is:

That’s bad! Boy, it gets worse. Here are the worst team pitching staffs since 1900, by our version of WAR:

To be absolutely clear about what we have here: By our numbers, the Reds just became the first pitching staff in modern history to finish with a negative WAR. It’s only slight, sure, and the difference between them and those 1915 Athletics is less than one win, but that negative symbol is conspicuous. It pushes the digits over to the right, so they can stand out. The Reds, as a collective, featured a major-league pitching staff that was a worse-than-replacement-level pitching staff. That’s almost unfathomable, is what that is.

Did the Reds really have the worst pitching staff ever? I mean, hell, I don’t know. Their pitching staff had one of the biggest home-run problems ever. By actual runs allowed, they were a little bit better than replacement-level, but you know where we stand on all that. There’s no way to actually compare across seasons or eras, not with the desired level of precision. We just don’t understand pitching that well yet, and we understand it even less the further back we go into history. We can say this: If you wanted to talk about the worst staffs of all time, you might use FanGraphs WAR as a starting point. It couldn’t make the Reds look any worse.

Reds pitchers, month by month:

• April: -1.3 WAR, 30th place
• May: -1.1, 30th
• June: -0.6, 30th
• July: +1.9, 20th
• August: +1.0, 26th
• Sep/Oct: +0.2, 30th

The first half is what did the Reds in. In the second half, they accumulated 3.2 WAR, good enough to edge out the Twins, Braves, and Diamondbacks. In each of the last three months, the Reds’ staff finished in the black. Yet it’s appropriate that, in the final stretch, they were dead last again. All they needed were one or two more good games, to avoid finishing in the…red. But a league-worst September and October locked the Reds into place. They had a chance to run away from history, but instead they suffer its embrace.

A negative WAR. It’s not that there weren’t some success stories. Anthony DeSclafani was pretty good. Dan Straily was all right. Raisel Iglesias adjusted well to the bullpen. Brandon Finnegan got stronger in the second half. But let me tell you: 32 Reds pitchers pitched. Twenty of them finished below 0.0 WAR. Alfredo Simon allowed more runs in 58.2 innings than Jon Lester allowed in over 200. J.J. Hoover allowed more runs in 18.2 innings than Zach Britton’s allowed the last two years combined. For the Reds, 2016 was never going to be about winning. Yet it also definitely wasn’t supposed to be about this.

I’ve been thinking a lot lately about the Rangers’ success in one-run games. They actually lost by one run yesterday, but if you’ve been paying attention, that was the first time that’s happened all season, probably, and one game doesn’t upset the whole pattern. The regular season is just about done, and the Rangers have put together an incredible stat. That’s — well, it’s incredible. I don’t need to provide any other words.

It’s tricky to write about these things, and I wasn’t looking to cover this in the familiar way. We’ve all read a number of articles about what the Rangers have done. We’ve all read articles before about similar teams doing similar things. It’s boring to say “luck,” and it’s tired to say “luck,” and with the playoffs around the corner pointing toward luck is additionally irrelevant. The Rangers have done what they’ve done, and their fans have been able to enjoy it. There’s no taking any of that enjoyment back for math-y purposes.

I’ve just been amazed by how the Rangers have stood out. They’ve won 77% of their one-run games. The Yankees are in second at 69%. Then you have the Tigers at 62%. Thinking about the Rangers got me wondering: Is this the most extraordinary team statistic of the year? I’ll tell you right now: It’s not! Follow along below.

Read the rest of this entry »