While there are certain events (like strikeouts, walks, and home runs) over which a pitcher exerts more or less direct control, it seems pretty clear at this point that there are some pitchers who are better at managing contact than others. It’s also also seems clear that, if a pitcher can’t manage contact at all, he’s unlikely to reach or stay in the big leagues for any length of time.

Consider: since the conclusion of World War II, about 750 pitchers have recorded at least 1,000 innings; of those 750 or so, all but nine of them have conceded a batting average on balls in play (BABIP) of .310 or less. Even that group of nine is pretty concentrated, the middle two-thirds separated by .029 BABIP. The difference between the guy ranked 125 out of 751 and the guy ranked 625 out of 751 is just three hits out of 100 balls in play. Those three hits can add up over a long period of time, of course, but it still represents a rather small difference even between players with lengthy careers. For that reason, attempting to discern batted-ball skills among pitchers with just a few seasons of data is difficult. Thanks to the emergence of Statcast, however, we have some better tools than just plain BABIP to evaluate a pitcher’s ability to manage contact. Let’s take a look at what the more granular batted-ball data reveals.

Read the rest of this entry »

The defining characteristic of that period in baseball now known as the PED Era isn’t particularly hard to identify: it was power. Home-run totals increased across the game. The long-standing single-season home-run record was broken multiple times in a few years. And, of course, drug testing ultimately revealed that many players were using steroids and other PEDs specifically to aid their physical strength.

Attempting to find a similarly distinctive trend for the decade-plus since testing began isn’t as easy. For a while, the rise of the strikeout seemed to be a candidate. A combination of increased velocity, better relievers, and a bigger strike zone has caused strikeout rates to increase dramatically in recent seasons.

Over the last couple years, though, we’ve also seen another big rise in homers — a product, it seems, both of a fly-ball revolution and potentially juiced ball. We’ve also witnessed the aforementioned growth of the strike zone begin to stagnate, perhaps even to reverse.

The combination of the strikeouts with the homers over the last few years has led to its own sort of trend: an emergence of hitters who record a lot of strikeouts, walks, and homers — each of the three true outcomes, in other words — without actually hitting the ball in play all that often.

The players responsible for this development are the sort who swing and miss frequently while refusing to offer at pitches on which they’re unable to do damage. To get a sense of who I mean, here’s a list of the top-10 players this season by percentage of plays ending in one of the three true outcomes.

That’s a pretty representative collection of the sort of hitter I’m talking about. Not only are these guys refusing to hit balls in play, they’re being rewarded for it: all but two have recorded distinctly above-average batting lines.

And this group of 10 is representative of a larger trend across the league. Consider how TTO% has changed in the 20-plus years since the strike.

Read the rest of this entry »

During this series of articles that have comprised my FanGraphs Residency, I have updated my analysis of the free-agent market that I last researched over three years ago. The vast majority of my new findings have suggested that teams have gotten smarter about spending in line with true player talent, all the while spending roughly the same share of league revenue as they were spending before.

Perhaps my biggest finding is that the OPP Premium has declined. Teams used to receive significantly less WAR for signing other team’s players as they did for re-signing their own players, and this seemed largely related to private information that teams knew about their own players. As teams have become more aware of this phenomenon, the evidence suggests that they have become more careful and have driven up the price of their own players while being more reluctant to sign players on other teams.

This is especially true for pitchers, who used to have the largest OPP Premium. Hitters appear to have actually increased their OPP Premium, which is probably more related to a handful of expensive players who did not pan out rather than teams collectively getting sloppier about signing hitters.
Read the rest of this entry »

In my previous articles in this series, I have looked at trends in free-agent spending over time, and specifically I have reviewed more recent data to see if market inefficiencies that I discovered in earlier work have disappeared over time. In this piece, I will review the findings on pitchers in my 2013 Hardball Times Annual article. In that piece, I discovered that teams tended to overvalue old-school statistics that did not translate to actual value. This included wins for starting pitchers and saves for relief pitchers. I also noticed that free-agent pitchers with strong peripheral statistics (e.g. those with good FIPs, usually) were often undercompensated, suggesting teams did not all realize the importance of peripheral statistics in projecting future performance. Much of this seems to have been corrected by the market over the years, although a handful of players have created some noise.
Read the rest of this entry »

Talk to pitchers on the record, and the links they’re willing to draw between an increase in blisters and what looks like a tighter baseball are minimal. That makes sense — and it’s doesn’t seem to be concern for politics or press relations that’s holding them back. There are so many confounding factors that it’s the probably the right way to approach the situation.

Talk to a few pitchers off the record, though, and another link emerges, one that might provide some insight into the relationship between seams and blisters.

Read the rest of this entry »

Over at Baseball Savant, another Statcast leaderboard has been rolled out. This one relates to speed. They are calling it Sprint Speed, and the definition is as follows:

Sprint Speed is Statcast’s foot speed metric, defined as “feet per second in a player’s fastest one-second window.” The Major League average on a “max effort” play is 27 ft/sec, and the max effort range is roughly from 23 ft/sec (poor) to 30 ft/sec (elite). A player must have at least 10 max effort runs to qualify for this leaderboard.

While Sprint Speed has been used for a while, we didn’t have leaderboards until now. Mike Petriello over at MLB.com has a full article on the rollout which I would recommend. Among the highlights: Sprint Speed correlates well from year to year; it doesn’t require a large sample to become reflective of true talent (Petriello compares speed to fastball velocity); and it might be useful when attempting to identify injuries that could be slowing players down.

So, we know that the metric can tell us who is fast and who is not. That’s helpful. I wondered if it might also be able tell us anything about any other statistics.

Before trying to predict the future or look at past years, I thought it might be useful to compare speed to the stats we have and see how they compare. While the leaderboard over at Statcast features nearly 350 names (every player who’s produced 10 or more max-speed data points), those sample sizes might be a bit too small when looking at other statistics. As a result, I narrowed the sample for this study down to the 166 players who were qualified at the end of Monday’s games.

Read the rest of this entry »

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.

Read the rest of this entry »

“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.”

Read the rest of this entry »

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?

Read the rest of this entry »

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.

Read the rest of this entry »