Away Games: A Minnesota Twins Blog

I’m watching the Twins-Rockies game on mlb.tv, and man is this Colorado broadcast team awful. An inning ago, the color guy talked over the play-by-play guy so he could finish some pointless story about eating on the road. And now they just got themselves totally confused about which Hernandez brother is which.

Announcer 1: “El Duque is ten years younger than him.”

Announcer 2: “What? What did you just say? This guy is ten years older than El Duque? He’s, like, 61″.

They went around like this for a while until they figured out that they had the whole thing ass backwards. Truly terrible. I didn’t think a TV baseball crew could be this bad without involving Hawk Harrelson.

For the record, the Detroit broadcast team is the best one I’ve seen while watching mlb.tv. That color guy really teaches you things about the game.

Also, I’ve always wondered when someone would do webstreaming alternative play-by-play that you could run concurrently with the video feed of a game while muting the official announcers. I feel like a lot of people would be psyched about that.

I had already finished and posted my Carlos Gomez analysis when the G-man went ahead and became the winning run in tonight’s exciting game. So of course I couldn’t go to sleep without writing up a coda on this game.

As Dick & Bert noted, this was only Gomez’s fourth walk of the year(!), so that in itself is noteworthy. Beyond that, though, I wondered: how did Gomez’s performance accord with my analysis? Any good scientist will tell you, after all, that one of the best tests of a model is how well it fits new data.

First, here’s a plot of all the pitches Gomez saw tonight:

After having just spent all day with Gomez’s pitch data, this graph immediately looked really weird to me. So much so, in fact, that I went and loaded up Gameday just to make sure I hadn’t plotted the data wrong.

What’s so odd? Well, the Red Sox decided to pitch Gomez inside tonight. And if you look back at the pitch plots in my earlier post, you’ll see that virtually no-one has done that this year. It’s been away, away, away.

Other than that, though, tonight mostly seems in keeping with my analysis of Gomez’s recent transformation into a better hitter. He laid off the pitches low and away, just as he has done since April 23rd. And the Red Sox didn’t give him much offspeed stuff, which is also consistent with the recent data. When Gomez did swing at pitches out of the strike zone, they were high pitches–again, consistent with what we’ve seen lately.

But the big news, of course, was that our man worked a walk. Here’s how he did it against Jonathan Papelbon. He got nothing but fastballs; he fouled off the ones in the strike zone, and he let the other ones go for balls. Simple as that. Observe how it’s done (red means foul, black means ball):

Of course, Carlos’s new plate discipline could still be a fluke. But you can’t help but love this at bat!

Meanwhile, the other hero of the game was Mike Lamb, who blooped a single to bring in the winning runs. That was a welcome change from what Lamb has done for most of this season, which is make tons and tons of outs. In fact, just as Lamb was coming up in the ninth inning, I was thinking that I needed to start working out my next in-depth analysis, tentatively titled “Why Does Mike Lamb Suck So Much?” And I’m still planning on doing it. But maybe if we’re lucky, tonight was the beginning of Lamb’s Gomez-like transformation from scrub into impact player.

Well, after that nice game where he got shelled in the first and then buckled down, Boof came out and did some garden-variety sucking tonight. How did he approach each batter? Here’s a plot, fresh and hot out the pitchf/x kitchen. Different at bats are color-coded, and the pitch result is marked by the symbol. Click to enlarge:

What immediately jumps out at me is:

1. Boof didn’t want anything to do with David Ortiz. And sure enough, he threw him one hittable pitch, and Ortiz hit it.
2. In three at bats, Mike Lowell didn’t see a single pitch on the inner two-thirds of the plate! Pretty cool.

Kevin Slowey made his return yesterday, and the results were uneven. I didn’t watch the game, but apparently he was doing OK until the fifth inning.

It’s crucial that Slowey contribute quality innings, especially with Pat Neshek injured. We’ll have to wait and see how things go for him.

In the meantime, here’s a chart I whipped up, comparing yesterday’s start to the one Slowey made in April. I don’t have any particular point to make with these. This isn’t an analytical post (unlike the Gomez post). This is more along the lines of, “I figured out how to get all this neat pitch data, so why not share it with the world!”

On the left you see Slowey’s location, with pitches coded according to pitch type and inning. This just use’s MLB’s somewhat inaccurate pitch classifications. On the right is a plot of pitch type using speed and “spin”, the latter calculated according to Fast & Nathan’s equation (see here for more.) I coded these pitches by their MLB classifications, and by the outcome of the pitch (ball, strike, or in play).

The graph isn’t really readable this small, so click on it to get the full size version. From what I can ascertain, Slowey is supposed to throw a fastball, a slider, a curveball and a changeup. I think I can pick them all out on the the speed/spin graph–the curveball on the lower left, the changeup on the upper left, the fastball on the upper right and the slider just down and to the left of the fastball. Or maybe that’s just a different kind of fastball, I don’t know. Either way, it looks like his pitches were a little less distinct this time than in his first start. You can also see that he hung a bunch of curveballs in the fifth, generally not a recipe for success. Not a lot to conclude from this, but it will be interesting to see what his next few starts look like

This blog is going to be a place for my commentary about the Minnesota Twins. Hopefully, it will be heavy on sabermetric analysis using pitch data from baseball’s pitch/fx system.

The name of the blog refers to the fact that I haven’t lived in Minnesota for almost ten years, yet I can’t quit my Twins. So as much as I love living here in New York, it always feels a little like an “away game” to me.

Check out the next post for my first attempt to crunch some numbers!

This blog exists because I learned how to extract pitchf/x data from the Major League Baseball website. So I’m starting with some pitch analysis!

After he hit for the cycle the other day, everyone started talking about how Carlos Gomez had turned his season around after a one-game benching on April 23rd. And he certainly looks better! Dave Studeman notes that “Gomez was hitting .230/.247/.310 when he was benched for a game on April 23, and has gone 13-for-30 (.433) with two homers and four steals in eight games since.”

But has Gomez really changed his approach, or is he just getting lucky? The problem he had early in the season was his tendency to swing at anything, especially breaking balls way off the plate. Aaron Gleeman showed recently that Gomez leads the Twins in swinging at pitches out of the strike zone (although the rest of the team ain’t exactly showing a Ted Williams eye at the plate either.) So I figured it would make sense to look at the pitch-location data from before and after April 23rd, to see whether Gomez has gotten any savvier about laying off junk pitches.

I downloaded the data for every pitch Gomez has seen, up through the May 8th loss to the White Sox. Then I divided the data into the games before April 23rd, and the games after. Gomez saw 307 pitches before his benching, and 119 after it, so the sample size, while not huge, is big enough for some exploratory analysis.

Below are two graphs showing the before-and-after versions of Gomez at the plate. Each pitch is shown where it crossed the plate (according to pitchf/x). The view is from behind home plate, looking at the pitcher–so the points on the right are away from the right-handed Gomez. The points are color-coded according the the outcome of the pitch: green points were called balls, red points were strikes (either called, swinging, or fouled off), and black points were put into play (for either a hit or an out).

So what do we see in these plots? Well, the plot above confirms that Gomez was swinging at a lot of bad pitches. All those red dots way out in the lower right are unhittable balls that Go-Go went hacking at. If I were a pitching coach looking at this graph, I would tell my pitchers to pitch Gomez low and away, and nothing but low and away.

OK, so what about the games after April 23rd? Well, it looks a heck of a lot better! In the graph above, there are are hardly any of those red dots low and away out of the strike zone. Gomez is still no Jason Giambi, but he seems to have learned to recognize pitches a little bit better. From this plot, his weakness now looks to be balls up and out of the strike zone, rather than low and away.

Now, the graphs above don’t tell us what kind of pitches those were. And the consensus seems to be that like a lot of young hitters, Gomez has particular problems with breaking balls and changeups. Some people have even suggested that he may be permanently cursed with poor pitch recognition. So let’s break down the analysis a little to see if this true.

Below, I have once again graphed pitch locations, before and after April 23rd. This time, I have included only those pitches that were either swinging strikes or fouls. These are the pitches that Gomez shouldn’t be swinging at, because he can’t make solid contact with them. I have color-coded the pitches according to the type of pitch. This classification is according to Major League Baseball’s system, and it is included in the pitchf/x data. These classifications aren’t perfect, and others have suggested better classification systems. But for my purposes, the MLB classifications are close enough, because they do a pretty good job of distinguishing fastballs from changeups and curveballs.

OK, let’s look at the graphs again. (A few pitches are missing in the first graph because they didn’t get classified by pitchf/x–see below for more on those.)

Again, the pattern for pre-April 23rd Gomez is striking. Those low-and-away pitches he was hacking at were almost all offspeed pitches, not surprisingly. It should be noted that that wasn’t his only problem, though–he was missing or fouling off a lot of fastballs, too, including some that were down the middle of the plate.

And after the 23rd? Again, it looks like there’s been a big change. Gomez is getting fooled on outside breaking balls far less often.

To get a better sense of what’s going on, let’s calculate some simple percentages. There are a lot of numbers below, but the conclusion is interesting–so bear with me!

OK, first off, is Gomez making better contact than he did before? Here’s how often he was missing or fouling off pitches in each period:

As a percentage of total pitches seen:
                       Swinging strikes         Fouls
  before 4/23              13.7%                22.5%
  after 4/23               13.4%                23.5%

OK, looks like that’s not what’s up. But what about the improved discipline we saw in the graph? Running the numbers does seem to suggest that Gomez has really improved:

Offspeed pitches only (Changeups, curveballs, sliders):
                      Swinging strikes         Fouls

  before 4/23              16.4%               24.6%
  after 4/23               18.9%               13.5%

It’s a mixed picure–he’s actually swung through a higher percentage of breaking balls in the second time period, but has fouled off way fewer. But remember that the overall swinging strike and foul percentages haven’t changed. So maybe Gomez is just missing lots of fastballs instead?

Fastballs only (including sinkers):
                      Swinging strikes        Fouls
  before 4/23             9.7%                20.6%
  after 4/23              11.0%               28.0%

That does seem to be part of it. He’s fouling off more fastballs, by quite a bit, and swinging through more of them too. In addition, Gomez’s improvement on offspeed pitches has been masked because he isn’t seeing as many of them now:

Pitch distribution:

                Fastballs     Offspeed    Unclassified

  before 4/23      50.5%       43.6%          5.9%
  after 4/23       68.9%       31.1%

Now, these numbers might be biased, because about 6% of the pitches in the pre-April 23rd dataset didn’t get classified by pitchf/x–so we don’t know what kinds of pitches they were. But even if all those unclassified pitches were fastballs, we would still conclude that Gomez is getting a lot more fastballs than he did before.

Now, why would this be? You have to imagine that the scouting reports on Gomez after the first few weeks emphasized his weakness for offspeed pitches. So if pitchers are nevertheless throwing him more fastballs, that suggests it’s because he’s no longer biting on the offspeed stuff. In other words, getting more fastballs is a result of Gomez’s improved performance, not the cause of it. But the numbers suggest that maybe Gomez hasn’t completely been cured of his tendency to whiff at breaking balls, so if he starts to see more of them again he could start to struggle.

So what’s the conclusion? With only a couple of weeks of the “improved” Gomez to go on, we can’t say anything for sure. But it certainly appears that he has shown some all-around improvement as a hitter. My quick summary would be:

1. Gomez is swinging at fewer offspeed pitches out of the strike zone.
2. Probably because of (1), when he does swing Gomez is not as likely to foul the ball off or miss it entirely.
3. Also probably because of (1), pitchers are giving Gomez more fastballs.

Given all this, I’m cautiously optimistic about Carlos’s future. There is certainly some reason to be concerned that this new level of performance won’t hold up. For one thing, his improved performance against offspeed pitches has been pretty dramatic, and I’m a bit skeptical that he’ll be able to sustain it. I expect to see some regression in the coming months–but hopefully he won’t regress all the way back to his early-April form.

I’ll revisit this question later, maybe around the all-star break. By then, we should be able to get a better idea about whether these results are a fluke, or whether they indicate a real step forward for Carlos Gomez.