It feels somewhat disingenuous to focus a second straight post on a member of the Texas Rangers because I have admittedly not spent much time watching them play baseball in recent years, and by recent years I mean my entire 23-year life. With that said, what little I have watched I can mostly attribute to my enjoyment of two of their current players: Rougned Odor and Mike Minor.

Drafted seventh overall in 2009 by the Atlanta Braves, Minor was a starting pitcher for parts of five seasons with the big league club, four of which were unremarkable but one (2013) which was actually quite good. In that 2013 campaign, he logged 204.2 innings, 181 strikeouts, a 3.21 ERA, and a 3.64 xFIP en route to a solid 3.3 fWAR. Soon afterwards, career-threatening shoulder issues emerged and caused him to miss the entirety of 2015 and most of 2016 before the Kansas City Royals signed him to a minor league deal. In 2017, he pitched 77.2 quality innings out of the bullpen at the major league level, quality enough that the Rangers decided to make him a member of their starting rotation in the following season, which some who were unaware of his pre-Kansas City history probably considered a bit puzzling.

The early returns on what was a somewhat risky and potentially costly investment yielded strong results, especially for a man who had not started a major league game in close to four years. He ranked 37th in fWAR among starters with at least 150 innings pitched, which put him in pretty decent company:

When accounting for the fact that Minor’s career-best 2013 slotted him just four spots higher despite pitching 47.2 more innings, the case can be made that even his micromanaged 2018 workload may have been even more impressive. The risk of the contract has almost evaporated entirely as well. After signing a three-year deal for $28 million, he has already delivered $24 million of value with just a season and change under his belt. A combination of his encouraging 2018 and the Rangers’ relative lack of pitching depth helped the 31-year-old Minor earn the starting nod for 2019’s Opening Day, which, no matter how extreme the dearth of talent may be, is quite meaningful. To be able to say that you had been the ace of a Major League Baseball team when all is said and done (which, barring an injury to a teammate, is usually implied by that honor) puts you in the company of very few people, and it is probably a pretty neat thing to have on a resume. Read the rest of this entry »

Over the course of his career, Marcus Semien has been nothing if not consistent. It’s quite remarkable, really — the 28-year-old shortstop has posted between a 95 and 98 wRC+ in each of his three full seasons (and one half season) since being traded to the Oakland Athletics by the Chicago White Sox in 2014. He has long provided a modest blend of power and speed, and his well-documented defensive improvements last year boosted him to a career-high 3.7 WAR and placed him squarely in the tier of not-great-but-pretty-darn-good shortstops in a league flush with some pretty darn good ones.

It may seem a bit strange, then, to suggest that such a player could be on the verge of a breakout, having already “broken out” last year and being on the wrong side of baseball’s aging curve. And yet, in the early weeks of the 2019 season, Semien appears to be suggesting that he is ready to do just that.

A bit of context: Semien has really flashed all the various facets of his potential at one time or another as he’s settled into a regular at shortstop for the A’s, but he hasn’t quite managed to put together a season that has wrapped it all up. He knocked 27 home runs in 2016 (although there was little in his batted ball profile to suggest any sort of adjustment), has consistently stolen around a dozen bags a year, and takes walks at a rate a tick or two above league average (8.2% across his career) — plus the aforementioned improvements on defense.

But, I ask you, what if he made a little more contact? Contact is good for hitters! It’s generally something you strive for. Allow me to present you with an incredibly simple graph:

That is what we in the industry (which one? Not sure) like to call “trending in the right direction.” A career-best 11.2 K% plus a stellar 10.3 BB% have helped Semien hit the ground running in 2019, posting a line of .311/.379/.505 over 116 plate appearances. Am I suggesting that Semien is going to hit .310 for the rest of the year? I am not (yet). Am I suggesting that an early display of improved plate discipline from him could foreshadow a step forward for him this year? We’re getting warmer! Read the rest of this entry »

While perusing through the newly introduced +Stats section released recently by FanGraphs, I couldn’t help but notice at the time that three Los Angeles Angels players held the top three spots for the lowest K%+ for 2019 thus far among qualified hitters, with an additional two Angels players joining them to round out the top 30. The first two players were David Fletcher and Tommy La Stella; these two players are roughly average hitters at best, but they have each run a far-below-average K% thus far in their professional careers, so seeing them at the top here isn’t too shocking in a small sample size. The third was of course Mike Trout, who has decided he doesn’t feel like striking out anymore while still maintaining his incredible hitting prowess. Out of all position players that have been qualified hitters in both 2019 and 2018, only Matt Chapman has lowered his K%+ by more in absolute terms (Chapman’s -67 to Trout’s -62), and nobody has lowered their K%+ in percentage terms more than Trout has, as detailed in the chart below:

Overall, no other team in baseball has more than two players in the top 30 of this K%+ measure, and by simple deduction, a handful of teams have not had one single player within that cutoff. Devan Fink has also written about how the Angels are not striking out in 2019, but I was curious to see how their players are stacking up with other recent seasons, so I set the parameters to include all qualified seasons from this decade, and the results were surprising.

Although this is in just a small sample size as mentioned earlier, it’s still noteworthy that those three players make up three of the top four qualified seasons since the beginning of this decade. I’ve also highlighted Andrelton Simmons‘ 2018 season, which was also another top-10 placing for the Angels. Although Simmons doesn’t appear in this chart for his 2019 season, he wasn’t far off with his K%+ of 46, ranking 12th for the season. With all of these Angels players posting such low K%+ figures, it had me even more curious as to how they stack up as a team historically, and whether this is an intentional approach they’re implementing. Read the rest of this entry »

Before we begin, here is the link to app being discussed: https://cargocultsabermetrics.shinyapps.io/Pitch_Design_Tool/

Two months ago, I wrote a blog post arguing José Berrios should learn a cutter. My argument hinged on the striking similarities between Berrios and Corey Kluber and the fact that Kluber has a good cutter and Berrios does not. Since then, I’ve developed a more objective way to evaluate a pitcher’s current pitches and make recommendations to guide the pitch design process. Pitch design is the process of a pitcher making changes to existing pitches or adding new ones, often using high-speed video and devices such as Rapsodo or TrackMan to get the spin axis of the pitch just right to create desired movement. The app I’ve built creates targets for pitchers and details ideal pitch characteristics to give objective, quantitative direction to the pitch design process.

My plan is to turn the tool into a service for college teams to use for their pitchers in pitch design, but I’ve also created a version which uses Statcast data to create pitch design plans for big leaguers that I’ve released for free. I figured this would be a good place to share the Statcast data version and give a brief explanation of how it works (if you’re interested in a more detailed explanation of the tool, check out this post on my blog). Read the rest of this entry »

Getting mad at an umpire, and then tossed from the game, may seem like an ineffective display of emotion since calls are never reversed after a little more yelling. But what about future calls? In order to answer this question, we need good data on a large number of adjudicated events. Close out and safe calls happen fairly rarely, and good data quantifying how close the play was would be difficult to collect. But the home plate umpire calls balls and strikes for every batter, and pitches at the edges of the zone provide plenty of opportunities to grow or shrink the zone slightly.

It’s difficult to measure the zone in a particular game since there aren’t enough pitches at each spot on the boundary of the zone, but by combining data from many games, we can get a clear idea of what the average zone looks like. As for quantifying the zone, it’s easy to get carried away with details (location of each side, correcting for player height, etc.), but with enough data, all of those variables should average out and we can focus on the simplest measure: zone size.

During the past four years, there have been 308 games featuring an ejection over the strike zone, containing about 47,000 pitches. Splitting by team (team with ejected player/coach/manager and opposing team) and before/after the ejection, we have groups with between 9,500 and 14,000 pitches, plenty for a good estimate of the strike zone.

The results, shown below, show two clear trends: first, one team is clearly justified in being upset as their hitters face a larger zone. Second, we see that umpires fix this, even over-correcting slightly, after making an ejection.

Umpires are Human

We all see the humanity of umpires in their fallibility, but it shows in other ways too: the zone shrinks on 0-2 counts and expands on 3-0 ones, showing that they don’t like ending an at-bat with their own judgement call. This doesn’t mesh well with the fiery persona of the umpire and their emotive strike-three calls, but we have to remember that they are playing a part, and their main goal is to keep the game firmly in their control. We see more evidence of this here: if umpires ejected arguing players out of a sense of holy wrath, we would expect no change in the strike zone at all.

Instead, we see a clear reaction in the direction that the arguing player desires. While the data cannot point to the exact mechanism, I see two distinct explanations: signaling and aversion to conflict.

In the signaling hypothesis, we suggest that players are frequently sending messages to the umpire, but the umpire considers these messages according to the cost in sending it. A few words muttered under their breath doesn’t cost them anything, and so it is usually ignored. An ejection is costly, so the umpire takes that signal seriously.

The second hypothesis is a simple human aversion to being yelled at in front of a crowd of thousands. It’s not a fun experience for anyone, so they take action to avoid it happening again.

About the Models

To measure the zone, I took two approaches, k-nearest neighbor (which knows nothing about the expected shape of the strike zone) and a logistic regression based model (which looks for a rounded rectangle). Error estimates were calculated using bootstrapped samples. Both gave similar results, and the code and data behind this post are available on Kaggle.

Trevor Bauer is a walking headline. Whether he is turning himself into some kind of pitching robot in a lab or calling out his peers for using a foreign substance to enhance their spin rate, Bauer tends to attract plenty of attention away from the field. However, Bauer’s most noteworthy accomplishments lately have occurred on the field. Last season, Bauer had more fWAR than Blake Snell, winner of the American League Cy Young Award, despite pitching fewer innings and landing on the injured list for over a month. Bauer, unsatisfied with last year’s performance, developed his previously sparingly used changeup in the offseason to complement his already ample repertoire. Taking a look at Bauer’s pitch usage this year shows a clear difference in the way he attacks righties as opposed to lefties.

Here is his pitch mix vs. righties this season:

And his usage vs. lefties:

Of course, the small sample size caveat applies at this point of the season, but Bauer has been featuring a changeup against lefties at a much higher rate than last season.

Here’s Bauer’s 2018 pitch usage against lefties:

Bauer now throws his changeup twice as often as last season against lefties, and so far the results have been good. The pitch has produced a 75% ground-ball rate when put in play, and opposing batters have only recorded a single hit off of it.

While Bauer has certainly adjusted his method of attacking lefties, an early breakdown of how he has attacked righties is even more intriguing. Here’s his 2018 pitch usage vs. right-handed batters:

Comparing Bauer’s 2018 and 2019 pitch breakdown against righties reveals a few monumental adjustments. Bauer has evidently abandoned his signature knuckle curve and replaced it with a sharp increase in the usage of a cutter. In my opinion, these adjustments were made in the name of tunneling. Sliders and cutters both have primarily sideways movement, which makes it more difficult for the batter to differentiate between them. Curveballs and changeups both tend to break downwards, causing the same confusion for batters. By pairing these pitches against righties and lefties respectively, Bauer decreases the chance that a batter can read the pitch correctly out of his hand.

Up until this point, Bauer has been sharp, using his new changeup and dedication to tunneling to strike out a third of the batters he has faced and firing seven no-hit innings on April 4th against the Blue Jays. Through five starts, Bauer has struck out 32.6% of batters and at least seven in each outing. As Bauer continues to tweak his approach, perhaps he could benefit even further by lowering his fastball usage, mimicking the strategy of many pitchers before him, in order to combat hitters who sit on the pitch ready to unleash uppercut swings. By lowering his fastball usage and further utilizing his tunneling ability, Bauer will be even more unpredictable to hitters.

Time will tell if Bauer’s new strategy will be successful all year, but based on his dedication to both analytics and his craft, he seems to be on pace for another Cy Young caliber season.

Gabriel Billig is currently a student at Baruch College studying data analytics.

In hindsight, it’s unfortunate that Ted Williams philosophies on hitting took so long to become universally accepted. His thoughts on batting were clearly ahead of his time and it has only been in the past few years that the more prevalent “swing down” views have largely exited the baseball community.

In his book, The Science of Hitting, Williams suggested an upward swing path that aligns the bat path and pitch path for a better chance of contact – about 5 degrees for a fastball and 10-to-15 degrees for a curveball. This research note is not about the total amount of loft in the swing today — everyone knows that swing loft is greater now than in Williams’ day. However, there are some very interesting findings in the data in terms of whether players are utilizing consistent amounts of swing loft for different pitch locations, which is implied in Williams’ book.

One observation that seems to hold in many sports is that the best performers are typically out in front of the popular views of the day in terms of changing mechanics for the better. However, as we will see in the data, this does not necessarily mean that these superior mechanics are being understood and directed by conscious understanding.

It turns out that there is a very important element that wasn’t considered by Williams in his book which the data shows the best hitters are “considering” — the amount of Vertical Bat Angle (VBA) in the swing. VBA can be defined as the amount of vertical swing tilt as viewed from the center field camera. The swings in Williams’ day as well as the illustrations in his book clearly have much less VBA than today’s hitters. While there is no broad data on VBA, a study of minor league hitters by David Fortenbaugh in 2011 showed the following averages of VBA at contact:

There is evidence which suggests that VBA goes well beyond player “style” and is more of a core swing mechanic that is associated with higher quality contact as well as superior levels of performance. Here is a chart showing VBA by playing level.

Read the rest of this entry »

I believe that pitches aren’t thrown in a vacuum, and the effectiveness of one pitch is certainly affected by the pitches that preceded it. Thus, I wanted to identify the most- and least-potent 1-2 pitch combinations in the 2018 Major League Baseball season. To accomplish this, I built a Pitch Combo Effectiveness Tool based on all 2018 pitches thrown in the major leagues.

The approach I took was to evaluate every pitch as the second pitch in a 1-2 combo (forcing us to exclude first pitches in an at-bat). I defined these pitch combos using the pitcher, the pitch types of both the first and second pitches (e.g. “four-seam fastball followed by a curveball”), and the pitch location change from the first to the second pitch (e.g. “the second pitch was further down and more inside than the first pitch”). I then gauged the effectiveness or value of these pitch combinations using the sum of the wOBA added for both the first and second pitches. Lastly, to ensure we were only looking at common pitch combos, we filtered the results to pitch combos observed at least 10 times in 2018.

The chart showing every pitch combo is below, and you can click it to go to the full tool and results:

Read the rest of this entry »

As the 2019 season begins, Las Vegas determines the annual over/under win totals for all 30 major league teams and gives us a chance to examine intriguing over/under win lines for the upcoming season. Not surprisingly, the Miami Marlins found a spot right at the bottom of the list at over/under 63.5 wins. Will the Miami Marlins, under the ownership of Derek Jeter and the tutelage of Michael Hill, elude the worst record in baseball? Call me crazy, but there are a number of reasons why Vegas’ determination of 63.5 wins is undervaluing the Marlins.

J.T. Realmuto, a 2018 All-Star and arguably the last star on the Marlins roster, was acquired by the Philadelphia Phillies for Jorge Alfaro, Sixto Sanchez, and Will Stewart this past offseason. While Sanchez is a potential budding ace pitcher and Stewart has a real future as a middle-of-the-rotation starter, Alfaro is the most interesting addition for the 2019 season. He rates as a guy with incredible raw power when he puts the bat on the ball, with the only issue thus far in his career being that his contact percentage is quite low:

The K% is good for 245th out of 247 players (min. 350 PAs) and the BB% ranks in the 8th percentile among those same 247. By looking at his O-Swing%, it’s good for second-to-last and 16% above the 2018 league average of 30.9%, and clearly he’s not making enough contact at 61%. However, when Alfaro does manage to put bat on ball, the results are quite impressive:

How about a video of the swing in action? This ball, at 115 mph off the bat of Alfaro, was absolutely crushed, and I think Junichi Tazawa’s reaction says it all…

With more patience and a better approach at the plate, the Marlins could have something special in Alfaro. It’s evident that this improved approach could be on it’s way by analyzing his second-half statistics from July 2018 to September 2018:

Alfaro managed to cut his K% and increase his BB%, while performing as an above-average hitter according to wRC+. He made strides at the plate by lowering his whiff percentage outside of the zone from 28% in the first half to 25% in the second half, and his batted ball quality improved against breaking pitches, which he had struggled with mightily in the first half, as his xwOBA increased from 0.246 to 0.338 in the second half and his whiff percentage on breaking balls decreased from 34.68% in the first half to 26.52% in the second half. Read the rest of this entry »

As far as breakout years are concerned, Rougned Odor did a bang-up job in 2016. His 33 home runs as a 22-year-old regular gave his baseball card a hefty amount of pop, but not as much as he gave Jose Bautista during their infamous run-in at second base.

I am not generally a fan of fisticuffs on the field, but this incident was and remains a touchstone for the 2016 season. However, in becoming so it may have, to the casual fan at least, reduced what was a solid season for one of the league’s youngest players to no more than a single moment. But Odor has, in fact, done more baseball things since that fateful afternoon, and the past couple of seasons paint a fascinating picture of a player who may not have improved overall, but one who has changed a whole lot and could very well have his best years ahead of him.
Over the past five years, he’s become a fixture at second base for the Texas Rangers, never appearing in less than 114 games during that span and accumulating a total of 7.2 fWAR. Save for his abominable 2017 campaign, which resulted in -1.2 fWAR, his career, despite no shortage of deep slumps and hot streaks, has been shockingly consistent: he’s totaled exactly 2.5 fWAR in three of the past four seasons. His career has played out much more interestingly than those identical numbers suggest, however, namely in that each campaign has played out quite differently (part of the fun of WAR!). The most pronounced changes, however, have occurred since that breakout 2016.

Though he posted identical fWAR totals in 2015 and 2016, the latter year was his first with at least 600 plate appearances, which helped him make quick work of his career-highs in the fan-favorite counting stats, namely home runs (33), RBIs (88), and stolen bases (14). A healthy-yet-not-unsustainable .297 batting average on balls in play (BABIP) anchored a solid .271 batting average, and 70 extra-base hits made for an impressive .502 slugging percentage. A paltry 3% walk rate kept his on-base percentage below .300 (.296), which limited his overall offensive production and kept his wRC+ at 103 (the league average is set at 100.) The 6.1 offensive runs above average remain a career high, but despite being 2.5 runs better than average on defense in the year prior, his -3.5 mark in 2016 remain a career low. Read the rest of this entry »