A couple of years ago, Jose Bautista had some advice for Marcus Stroman. “He said I should screw with my timing more,” the Jays’ right-handed pitcher told me a couple weeks back. Maybe you’ve seen him employ the strategy this year. It’s a fun and makes watching him more interesting. The effect it has on his ability to prevent runs is less obvious, though.
“Grips are meaningless,” Oakland A’s starting pitcher Sonny Gray once told me. Maybe that’s why we haven’t yet had a good talk, despite calling the same clubhouse home half the time. He didn’t quite mean “meaningless,” it occurred to me, when we finally discussed his repertoire. But there’s another reason he’s found it difficult to talk the way pitchers often talk to me: He’s changing things from pitch to pitch, according to what he sees. That includes grips, finger pressure and pitching mix. It’s hard to say he’s been doing something different when he’s always doing something different.
It’s difficult to figure out the righty. His breaking balls, for example: One classifying system says he’s currently throwing more sliders than ever. One says he’s in a three-year high for curveballs. A third says he’s right about where he’s always been, but that his recent good stretch may have coincided with an increased use of his slider.
Is he throwing more sliders now that he’s healthy? Gray shrugs. “Even before I got hurt, I was throwing sliders, and I was throwing them at 88, 89 mph,” he says. No system has him throwing a breaking ball that hard. “Whatever people call the pitch is what they are going to call it. It’s a hard curveball, I guess. The grip is a little bit different, but it does have a curveball action.”
On Tuesday, I discussed MLB’s expected wOBA (or xwOBA) metric and one of its problems — namely, that guys with great speed might have the ability to outperform their xwOBA on a regular basis. I also pointed out that, despite this drawback, xwOBA should have considerable utility. This post looks at one potential aspect of that utility when it comes to projecting future performance when we have only completed just a small portion of the season.
Comparing wxOBA and wOBA for individual players over the course of a season, one find a pretty strong relationship — a point which I establish in that Tuesday post. To take things a step further, I’d like to look here at the relationships of these stats over the course of a couple seasons and see how they correlate from year to year. In order to establish a baseline, let’s look at how players with at least 400 at-bats in both 2015 and 2016 fared by wOBA.
So we see a decent relationship between wOBA marks in consecutive season. It certainly would be strange if there weren’t some relationship between a player’s offensive statistics from year to year, as players generally don’t get a lot better or a lot worse in such a short span of time — even if the players who do meet those criteria make for more interesting stories and analysis. So we see that, from 2015 to 2016, there is a relationship with wOBA. What about xwOBA?
Rich Hill is in the midst of a blister problem. It’s been going on since his breakout season last year. Since only three pitchers in 2016 threw more curveballs than Hill, it makes sense to blame the curve. Maybe there’s more at work, but also maybe not. It’s a pretty reasonable hypothesis.
I mean, for one, the pitcher himself believes it. “It’s right there, on the pad of my finger, where it touches the seams on my curveball,” said Hill on Tuesday night. Curious about the condition of his digit, I pushed: could I take a picture of the pad on his middle finger pad? “Nobody’s taking a picture of my finger,” he laughed. I didn’t pursue the matter any further.
Last Thursday, baseball got weird and the Mets and Marlins played past midnight. After Travis d’Arnaud hit the go-ahead homer in the 16th, the catcher slowly trotted around the bases, admitting afterwards that he needed the invigorating effects of that moment just to complete the task. “The emotions of the home run helped lift my legs a little bit,” he said to James Wagner after the game regarding his tired knees. After the dust had settled and all the exhausted quotes were collected, though, the teams had to play another game later that day. What sort of effect would the marathon game have on that game?
Intuitively, you might expect the teams to have trouble scoring runs the next day. Tired legs, tired minds, tired bats, you’d think. Turns out that instinct is accurate… sort of.
In honor of Opening Day 2017, we thought it would be fun to take a look back at the five craziest Opening Day games (or home openers), as defined by swings in win expectancy. So we did, in this video we just posted at our Facebook page! Happy baseball!
Thanks to Sean Dolinar for his research assistance.
As I mentioned recently on Twitter, a friend of mine asked how common it is for a pitcher to be drafted by a major-league team after he’s already undergone Tommy John surgery.
I honestly didn’t know the answer, but assumed the rate was rather low.
I grabbed data on Tommy John surgeries from Jon Roegele’s indispensable database and draft information from Baseball-Reference. I focused on drafts that have occurred since 1986 and just the first 10 rounds. I then isolated individuals drafted as pitchers and merged the two data sets based on player name.
The overall rate of teams selecting pitchers who have already undergone Tommy John surgery appears to be 1.8%. Now, that rate changes a bit over time. There are many reasons for this, I’m sure: increased prevalence of the surgery, teams becoming more comfortable selecting a player who has undergone the surgery, and simply better data in the Tommy John database for later years.
In any case, here’s the rate trend by year:
Starting in 2006, the rate begins to increase, with the highest rates coming the past three seasons. On average, teams are now selecting pitchers with a prior Tommy John surgery between 7-9% of the time.
Who’s getting selected and by whom also differs to some extent.
In baseball, luck is a tricky concept. In some cases, it’s used to describe an event that’s within the normal distribution of outcomes but far from the mean. In other cases, what we call luck might actually be the first signs of an outlying skill for which we simply lack a sufficiently large sample to identify.
We’ve developed a new understanding on one kind of luck in recent years — namely, the sort that occurs with a batted ball. With Statcast data, we can look at the shape and size of a ball in play and try to decide what the batter “deserved” from that sort of ball in play. Then we compare it to actual outcomes. The difference between the observed and expected outcome is luck.
What if you want to look at a luck on a specific pitch type, though? How would you do it? You could look at the results on the pitch and basically use the Statcast-type process from the other side of the ball. What sorts of balls in play did that pitch produce, and what sort of results should those balls in play have produced? The problem with that approach is that you’re slicing a pitcher’s repertoire into small samples when you start talking about balls in play off a specific pitch. Even David Price, for example — who led the majors in innings last year — allowed fewer than 300 balls in play on his most frequently thrown pitch, the fastball. Secondary pitches are, almost by definition, thrown much less often. Variance isn’t the exception in such cases, but the rule.
Major League Baseball has been floating a bunch of different ideas lately to help improve the game: automatic intentional walks, starting a runner on second in extra innings, and one that would likely have the most impact, raising the lower bounds of the strike zone.
If you feel like you’ve heard that last one before, it’s because you almost definitely have. Jon Roegele has been chronicling the expansion of the strike zone for years. It’s not just him, though. Just last year, there were reports that MLB planned to raise the strike zone. In response, August Fagerstrom discussed who might be affected the most. August isn’t around these parts anymore, so consider this post your update on the pitchers who might be negatively affected by a slightly higher strike zone.
First, consider the visuals below. They’re from a 2014 piece by Roegele and were reproduced by Fagerstrom last year. They documents how the strike zone has expanded downward over the last decade.
It’s pretty obvious from these graphs that pitches in the lower part of the zone were being called strikes more often in 2014 than five years earlier. But these images are from a couple seasons ago. Is it possible, given the talk last season about raising the strike zone, that umpires took it upon themselves to do it? To compensate for the lower-zone creep happening of late?
What happened to Clayton Kershaw in Game 6 of the NLCS? According to a new study by Northwestern University, maybe it was jet lag.
Looking at 20 major-league seasons and 40,000 games’ worth of data, researchers found that jet lag perceptibly “impairs” player and team performance. The study is likely to be passed around many major-league front offices and strength-and-training departments. In a sport where every team is looking for hidden value at the margins, the value of better rest and recovery is just beginning to be explored, understood and focused upon — and is perhaps a considerable inefficiency in the game.
Dr. Ravi Allada, a circadian-rhythms expert, led the study:
“The negative effects of jet lag we found are subtle, but they are detectable and significant. And they happen on both offense and defense and for both home and away teams, often in surprising ways….
“For Game 6, the teams had returned to Chicago from LA, and this time the Cubs scored five runs off of Kershaw, including two home runs. While it’s speculation, our research would suggest that jet lag was a contributing factor in Kershaw’s performance.”
One of the homers in question:
Of course, Kershaw did pitch on extra rest that start, and Kyle Hendricks himself did just fine after traveling back east, but perhaps the rest could not save Kershaw from the clutches of jet lag.
