Since opening in 1999, Coors Field has provided the most offense-friendly environment in baseball. Despite the inherent volatility in park factors for single-season data, Coors has “won” the park factor title in 15 of the past 20 years, never finishing lower than third. The dramatic increase in home runs may be the most striking effect of the thin air about a mile above sea level, but all balls in flight, including pitches, are affected. Due to the lower air density, the spin-induced movement of a pitch thrown at high altitude will be lower than that of a comparable pitch closer to sea level.

Check out the average movement on Adam Ottavino’s pitches in 2017 and 2018 separated by home (purple) and away (black).

You may recall Ottavino said recently that he is confident Babe Ruth couldn’t hit any of this stuff. Read the rest of this entry »

The Yankees kicked off their offseason by acquiring LHP James Paxton from the Seattle Mariners to bolster their starting rotation. You won’t find anybody willing to deny Paxton’s immense talent, but it’s natural for people to scrutinize big acquisitions, especially when the big acquisition is on his way to New York. This scrutiny is best exemplified by a conversation I had with my mother on the day the trade was made. My mom followed the Mets of the mid-to-late 1980s when she lived in Brooklyn, went years without watching baseball, and has watched the Yankees for the past decade by product of my fandom. This leads to the amusing circumstance that she is very familiar with current broadcasters Keith Hernandez and David Cone, all of the recent Yankees players, and almost nobody in between. Our conversation on the day of the Paxton trade went something like this:

Me: The Yankees picked up a hell of a pitcher named James Paxton. I think he’s going to do big things for the Yankees next year!

Mom: Yeah, sure. Isn’t that what you said about Sonny Gray?

Okay — she got me there.

Read the rest of this entry »

The Home Run Derby (HRD) is one of the most popular MLB events of the year, seemingly as popular among the players as among the fans. Everyone enjoys watching the best players in baseball launch 450-foot home runs while the non-participating All Stars towel the hitters off and cheer wildly for the most spectacular hits as they head over the outfield seats. But it is also one of the most controversial events, since it rewards something that every little leaguer is warned not to do — swing for the fences with every pitch. Some commentators believe that there is a pattern of derby participants exhibiting declining production in the second half of the season, and they argue that participation in the derby is to blame, because, they say, it ruins the swing plane of the participants. If we can put this theory to bed, then, if nothing else, it would take a little bit of stress off of a really fun night. If an effect does exist, however, it would be useful for front offices to know this before sending their stars to their potential demise.

It has become commonplace in the statistically minded baseball community to view the “Home Run Derby Curse” — the decline in productivity for HRD participants — as an example of misguided traditionalist folklore. The statistically savvy point out that people are selected for the derby exactly because they are overperforming their “true” talent level and because they will perform closer to that true talent level in the second half. Considering that, it is reasonable to assume their second-half performance will be worse than their first-half performance — a rather pedestrian example of regression to the mean. However, the argument usually stops here, as if somehow the concept of regression alone is enough to prove the non-existence of a curse.

The fundamental challenge in rigorously exploring whether or not the Home Run Derby caused a decline in production for an individual player is the same as for many arguments about causality — in order to firmly establish (or dismiss) the claim, we would need to imagine a counterfactual world in which that player did not participate in the derby and then we could see the difference in second-half production. That, of course, is impossible. One approach to addressing this challenge is to consider a collection of players whose statistics are similar to the HRD participant but who did not compete in the derby and look at the difference in second-half production. If we do this with all HRD participants, we should be able to see any general effects, if they exist. Read the rest of this entry »

Over the past several years, we have watched a number of hitters in the minors display good contact skills with average or below-average power be labeled with 45s and 50s only to burst onto the scene with an explosion of power they never showed any hint of previous. Mookie Betts might be the best example, along with guys like Jose Ramirez, who show up to the big leagues and announce themselves by mashing.  Naturally, prospect hounds, analysts, and the baseball community investigated how these guys went so overlooked (unless you were Carson Cistulli). It was surmised that contact quality mixed with good exit velocity and appropriate launch angles allowed hitters to maximize their output even without Aaron Judge levels of thump.

This investigation, however, is not a hunt for the next minor leaguer who will smash his way onto the scene, but rather a search for the pitchers who will try to stop them. With modern conditioning and institutions (read: Driveline) making it more possible than ever to gain velocity, one no longer must be naturally gifted a 6-foot-5 frame with easy 95 to be considered a prospect. Furthermore, with openers, bulk guys, firemen, and more, traditional pitching roles are going by the wayside.

This analysis attempts to seek out pitchers who possess above-average command or secondary offerings but lack the prototypical velocity grades we are seeing in today’s game. Identifying these pitchers would make them intriguing candidates for these high-intensity velocity training plans. While you may not find the next Luis Severino, you could uncover an explosive fireman reliever, matchup guy, or high-octane backend starter that pushes you closer to October glory.

The process for this analysis involved using the 2018 updated prospects list from THE BOARD, developed by Kiley McDaniel, Eric Longenhagen, and Sean Dolinar at this very site. I started by sorting for prospects who either currently have > 55 command or project for the same. This brought the sample to 85 pitchers. Next, I sorted out pitchers who have a present FB grade of > 55. Our sample now sits at 38 pitchers who have or project to have above-average command and an average-to-below-average fastball. Before diving into the next set of data, I wanted to provide some broader notes about this group. Notable pitchers with top 100–130 considerations on this list include Atlanta’s Kolby Allard and Joey Wentz, Miami’s Braxton Garrett, and the Angels’ Griffin Canning. There are 16 lefties and 22 righties. The Phillies lead the way with five of these guys, the Cubs and Rockies are tied with three each, and then the rest of the league has one or two on this list. Additionally, the average age of this group is 22.8 years old.

Now that we have our assorted pool, it is time to sort through this group’s off-speed arsenal. This part of the analysis was more subjective. I have attempted to group pitchers with similar traits that could fill a variety of roles. What follows is three tables of guys who could benefit most from additional velocity.

This first group features two right-handers with a current 60-grade pitch that projects for 70. Of the 38, these two are the lone members who feature a current 60 pitch. Of the two, Morgan has the higher upside based on his slider. Both have fastballs that sit around 90 mph, but additional velo training could push the value of these guys up a tier. Guys from this tier could be featured as openers or one-time-through-the-order relievers that rely on one elite pitch. The selling point of this group is that they have that elite pitch to lean on even without elite velocity.

The next group features players with multiple 55-or-better future offerings, led by Padres righty Pedro Avila, who is rocking two future 60-grade pitches. Previously mentioned notables Garrett and Wentz also fall into this category. This group represents backend starter types who are useful during the season but less useful during the postseason. Additional velo here could push these guys into strong No. 3 starters or high-leverage multi-inning guys.

The last group of guys profile as backend starter types who live on off-speed stuff and have no margin for error with their fastballs. I identified these players by adding their FV non-fastball pitch grades together, noted as ARS in table (ARS = FCH+FSL+FCB). These guys walk the command and off-speed tightrope to end up as backend starters in the best case, or just middle-relief guys or up-and-down starters. Occasionally these guys become Kyle Hendricks, Tanner Roark, or Doug Fister, but these are exceptions and not the rule. Almost everyone in this group is older for a prospect, so the ceiling is limited, however, additional velo for these guys could turn them into more dynamic multi-inning relivers, bulk guys, or high-end No. 4-5 starters.

I should also note that all these guys fall into different buckets of age, level, and body types. Arguably, the most critical component of a prospect on this list would be targeting high-makeup guys who would be willing to experiment and acknowledge that they could use more gas to ascend to the next level. Some of these pitchers may be maxed out physically or unwilling to change what already seems to work. This analysis also looks past statistical performance, level, and even present pitch value a bit. What this analysis does do is identify guys who could rapidly improve with additional velocity due to advanced command and secondary. The margin for error is incredibly slim for this type of pitcher, but through intense training and velocity gains, pitcher X throwing 90-92 bumping to 94-96 with already above-average command and secondaries would vault them into a new tier of player. For teams looking to squeeze every ounce of value out of their farm system, this could be another way to target undervalued talent that has yet to be unlocked and developed.

The Incredibles can be considered a masterpiece of modern cinema. Brad Bird’s 2004 Pixar film follows a family of superheroes in a world that’s openly hostile to their kind. As such, the family is forced to camouflage itself as a normal one. Mr. Incredible has an unfulfilling job. Mrs. Incredible thanklessly raises three kids. At the outset of the movie, we, the viewers, know the positive potential for superheroes from our prior knowledge of popular culture. For some reason, the movie tells us that the existence of superheroes is a bad thing, so we’re left with a major dissonance. Yandy Diaz’s situation in Cleveland was a lot like the beginning of The Incredibles.

In an age of celluloid superheroes, Diaz looks like a real-life version. The “most jacked player in baseball” according to stack.com (the mere existence of this website makes me uncomfortable) has put up minor league numbers of someone with super vision, not super strength. Indeed, his career-low in on-base percentage at any minor league stop with at least 20 plate appearances is .399. In 2018, he split time between Triple-A Columbus and Cleveland, where his OBPs were .409 and .375, respectively.

Unfortunately, like the existence of superheroes, Diaz’s power remains in our collective imaginations. Despite his mammoth yolkedness, his professional career high in home runs in any full season is nine. Even Delino Deshields hit 12 in the minors once, and he is a small, fast player, and he plays like it. You can usually tell what kind of player someone is by their body type, but not so with Diaz.

As you may guess, there have been zero ground-ball home runs in the Statcast Era. Indeed, cold hard data and common sense align on this topic. This is the great barrier separating our reality from SuperYandy, his radioactive spider so to speak. Diaz’s professional ground-ball rates have ranged from the low-50s to the mid-60s. To put that in context, the following chart shows the ten qualified MLB players with the highest GB%, along with Yandy’s 2018 season:

The most valuable player here is Lorenzo Cain, and by a wide margin. As you can see, Cain posted one of the highest BABIPs and walk rates of the bunch, and he finished 24% above average offensively. Combine that with his stellar baserunning and center-field defense, and Cain was one of the most valuable players in the majors in 2018. However, the chart makes it clear that hitting grounders is generally not great for hitters’ production. Without a strong BABIP and BB%, it’s nearly impossible to be above average while hitting that many grounders.

Luckily for Diaz, he seems to be skilled at achieving high marks in both of those categories. We’ve already talked about his SuperVision, and the Steamer projection system expects Diaz to put up a .368 OBP while walking over 12% of the time in 2019. Meanwhile, Yandy’s BABIP is directly tied to his potential to become baseball’s Mr. Incredible.

BABIP has always been an attention-grabbing stat. When it first jumped into the analytical scene, it was dismissed as randomness. The thought was that hitters can’t control where the ball goes, or the quality and positioning of defenders, so we should expect batting average on balls in play to fluctuate with luck, and to an extent, it does. But more recent thought suggests that players do have some control over their BABIP. Cain is much faster than Trey Mancini, so even though they have identical ground-ball rates, we can expect Cain to beat out more of those grounders. Indeed, Cain had 27 infield hits in 2018, while Mancini finished with only 11.

So what other controllable factors can lead to higher BABIP? For one, batters can influence how hard they hit the ball, and they can influence how high they hit the ball; indeed, we find that each of these factors affects batting average on balls in play. From 2015-17, balls struck at 100 mph led to base hits 49.8% of the time, and that percentage only increases with harder hit balls. (It should be noted that that includes home runs, which are not included in BABIP). In addition, each type of batted ball is associated with BABIP performance, as outlined in the following chart:

Diaz has always specialized in that ‘non-flies’ category: during his limited MLB career, just 20.8% of his batted balls have been fly-balls, which is the sixth-lowest during that time-frame. However, not all non-flies are created equally; we’ve already discussed the association between hitting the ball hard and reaching base successfully. Among the 480 players with 50 or more batted balls in 2018, Diaz finished 24th in average exit velocity, just behind the AL and NL MVPs, Mookie Betts and Christian Yelich.

This is the kind of hitter Diaz is as of this winter. He’s a non-fly-ball hitter who consistently makes great contact with an above-average eye and low strikeout numbers. In the field, Diaz had a strong reputation in the minors. Baseball America even named him the strongest defensive third baseman in the Carolina League in 2014. Additionally, throughout his minor league career, he played every position except shortstop, catcher, and pitcher.

Put all of this together and you have yourself a high-floor, multi-positional major league baseball player, which makes his time with the Indians franchise seem peculiar. Diaz began his American baseball career in 2014, and he cruised through the minor leagues as a consistently great hitter. By just 2015, he got his first taste of Triple-A ball, and 25 games into 2016, he was permanently at that level. And then… the Indians never really gave him a shot. For Columbus in 2016, as a 24-year-old, he hit .325/.399/.461, good for a 149 wRC+. No call-up. In 2017, he was even better: .350/.454/.460, 163 wRC+. Finally, the Indians called him up after over 800 extremely successful Triple-A plate appearances, and he fared okay in his cup of coffee. In 2018, he spent most of his time in Triple-A, again, despite his 132 wRC+ in his 120 MLB plate appearances.

For some reason, despite his overwhelming success as a professional baseball player, Cleveland barely gave him a chance to succeed. He’s potentially Mr. Incredible, an extremely strong player with great potential being held back. For one, it seems like Cleveland, and Terry Francona, viewed Diaz’s defense as “a work in progress,” despite countless public reports to the contrary. Maybe that’s the case, but even if we assume Diaz’s fielding isn’t actually as good as those reports make it out to be, I still find it hard to believe that Diaz would not have been a better first baseman than Yonder Alonso in 2018. We must consider that it is possible that the front office knows something about him that would make him less appealing.

To Tampa Bay, Diaz is not just a high-floor Ben Zobrist type, but he also has tantalizing upside. There’s no way of knowing this for sure, but I am willing to guess that the strongest three players in the major leagues are, in some order, Yandy Diaz, Aaron Judge, and Giancarlo Stanton. We don’t know if Cleveland tried to convert Diaz into someone with Judgian power, as John Sterling would say, but we can assume the Indians at least thought about it. Maybe they tried to change his swing and he was resistant. Who knows? There’s little doubt that this is the Rays’ plan though. They’re hoping that Diaz can change his swing a la J.D. Martinez and become SuperYandy, a slugger without the strikeouts. Even if that doesn’t work out, they still end up with a valuable player, and if it does, Diaz could end up as one of the most valuable players in baseball. It will take time before we know if he was one of the best players traded this offseason, but rest assured, he’s already one of the most interesting.

Something appears to have happened to Madison Bumgarner. Specifically, his four-seam fastball has gone missing. Depending on which data source you use, it figuratively and literally disappeared. Regardless of data source used, Bumgarner’s fastball isn’t performing.

Two leading data sources disagree on what has happened to Bumgarner’s fastball. Because of this, I chose to look at both sources independently: Pitch Info (through Brooks Baseball) and Statcast (through Baseball Savant). This analysis spans four seasons, 2015 through 2018, encompassing Bumgarner’s two best and two worst complete seasons.

According to Pitch Info, Bumgarner threw four-seamers in 2018 at a career-low frequency — 34.5% of the time in 2018, down from 48.2% in 2016 and 49.6% in 2015. It has been losing effectiveness since its peak in 2014. Using Pitch Info’s runs above average metric, we see Bumgarner’s four-seamer peaked in quality at 1.25 runs above average per 100 pitches in 2014 and has dropped each year since then: 0.97 in 2015, 0.39 in 2016, -0.35 in 2017, and -1.14 in 2018, a career low.

As seen in the Pitch Info Whiff Percentage charts above, Bumgarner’s four-seam fastball had its lowest whiff rate of our period of study in 2018 (seen on the left), likely leading to it’s ineffectiveness. Similarly, Bumgarner’s four-seam is measured to have had more vertical sink, independent of gravity, than it had throughout this period (seen on the right). Depending on the pitch, more movement generally increases whiff rates. A four-seam fastball moving more like a two-seamer, however, would lose swing-throughs: sinkers (two-seamers) generate more contact in the form of ground balls.

Bumgarner produced his highest ground-ball rate with his fastball since 2013 while also generating the fewest whiffs with his fastball of his career. Couple the results with the change (increased vertical movement), and it appears his fastball began to behave like a two-seam fastball.

This seems to be clear already. According to Statcast, Bumgarner threw his four-seam fastball only once in 2018, as compared to 38.6% of the time in 2016 and 41.1% of the time in 2015. He replaced them mainly with two-seam fastballs, but also with some curveballs and changeups.

When comparing Statcast to Pitch Info, I wondered if Statcast could have been misclassifying four-seam fastballs as two-seamers. Through looking at the above plots, however, it’s clear a cluster of pitches was missing in 2018. The above graphs are of every pitch Bumgarner threw, by horizontal (x-axis) and vertical (y-axis) movement, colored by Statcast pitch classifications. Even when ignoring pitch type labels, a pitch type is seen to be missing. Specifically, Bumgarner’s high-rising, fairly straight pitch was no longer thrown. On a side note, notice how inconsistent 2017’s movements were: likely because Bumgarner had to recover form a major shoulder injury and struggled.

With Statcast data, we can evaluate what happened with greater depth than through other methods. Below is a table of statistical changes in both Bumgarner’s two-seam and four-seam fastballs.

Velocity is measured in miles per hour, spin in revolutions per minute, extension is feet from the rubber, and horizontal and vertical movements are in inches from release point. Ignore 2017, as it was a very inconsistent year (as seen with the movement chart above). Both two-seam and four-seam fastballs in 2015 and 2016 had significant vertical rise due to spin. In 2018, however, Bumgarner couldn’t or wasn’t spinning his fastballs as much, resulting in less rise and more downward movement. This could be why Statcast is misclassifying his fastballs.

Why has Bumgarner lost spin on his fastballs? The data suggests two reasons why, both of which could be correlated. He’s lost velocity, and release speed correlates with spin rate. Similarly, Bumgarner has less extension on his fastballs than in 2016. His 2018 extension is similar to his 2015 extension, but because he’s lost velocity, the loss of extension could be penalizing. This loss of extension could explain the loss of spin if it’s related to grip or release.

Extension loss to home plate reduces the perceived velocity the batter anticipates, making it easier for the batter to time the pitch. Both loss of velocity and extension would, when combined, greatly benefit the batter at the expense of Bumgarner’s fastball.

What could have caused the loss of velocity and extension? Bumgarner is 29 years old, so there is a chance he’s entered his decline. The likely culprit, however, is injury: Bumgarner fell of a dirt bike in April 2017, injuring his left shoulder, and he broke his left hand on a line-drive comebacker in spring training in 2018, requiring surgery. Being left-handed, both injuries could have significantly affected his 2018.

One year away from free agency, Bumgarner likely hopes he can recover lost velocity and spin on his fastball. Whether it was an organizational change, a declining skill set, or driven by injury, his 2018 fastball difference was one to forget. His shoulder should be better healed, one year further removed from his accident, and hopefully his throwing hand does the same.

This and other postings like it can be found on my personal blog, First Pitch Swinging.

Every year, nearly every team in baseball receives significant contributions from unexpected sources. The 2018 campaign was no exception, with a number of players putting up productive seasons while primarily coming off the bench. For the purposes of this article, we’ll define a bench player as any player with (roughly) 100-plus plate appearances over the course of the season that did not appear as a team’s primary starter at any one position. Additionally, I sorted out players that were traded (or acquired) midseason (Manny Machado for example) or called up to start full time but did not record enough time to count as the team’s primary starter at their position (per Baseball Reference). Players with 500-plus PA were excluded from consideration on account of extensive playing time (apologies to Chris Taylor, Matt Kemp, Jurickson Profar, and Ben Zobrist), and one player was selected at each position, along with honorable mentions. Without further ado, let’s look at the best of the bench in 2018:

Catcher: Elias Diaz, Pirates

Honorable Mentions: Tyler Flowers (ATL), Luke Maile (TOR)

Diaz certainly served as a key bright spot during an up-and-down season for the Pirates, filling in admirably for the oft-injured Francisco Cervelli. The young Venezuelan had somewhat of a breakout campaign in 2018, posting a 114 wRC+ while contributing positive defensive value behind the plate. Overall, Diaz put up a solid 2.0 WAR in 277 PA on the season. After a weak offensive showing in 2017, Diaz appears to have made notable strides in plate discipline this season, improving his walk rate from 5.5% to 7.6% while dropping his strikeout rate from 19.0% to 14.4%. This decline in strikeout rate represents one of the 10 largest such drops in the league between 2017 and 2018 among players with at least 200 PA in each season. Combined with Cervelli’s excellent output, Diaz helped guide the Bucs to a league-leading 5.3 WAR from catchers:

While Flowers and Maile each put up solid seasons in their own right, Diaz ranked among the top 10 bench players in all of baseball by WAR this season and established himself as one of the better backup catchers in the game. Read the rest of this entry »

At some point in the coming days or weeks or months, Bryce Harper, with an assist from Scott Boras, will make a choice as to which team he will sign a contract to play baseball with in 2019, and possibly beyond. A lot of factors will go into what his choice of team will be. It is almost certain that one of those factors will not be the city and state (i.e., local) income taxes he would be paying were he to choose this team or that.

Maybe I have that wrong. Maybe the local income tax burden will be high on a list of factors Harper considers. Maybe he’ll meticulously pore over a table showing each team’s possible effect on his overall tax bill. More likely, though, beyond the idea that a team he’s considering plays in a no-income-tax state or a super-high-income-tax state, I can’t imagine him or Boras actually stressing out over it.

That said, it is worth noting that the difference in local income taxes to be paid by Harper next year would vary widely depending on which team he chooses. And when I say “widely”, I’m talking a difference of millions. Mo’ money, mo’ taxes. Nice problem to have, amirite?

What follows is my attempt to quantify just what this difference might be, by team. Before diving in, two points.

The first point is to dispel any lingering notion that, if Bryce Harper were to choose the Texas Rangers or Seattle Mariners or Miami Marlins—come on now, stop laughing and pay attention, this is kind of important—or any other team in a no-income tax state, he would not have to pay any state income tax at all. That’s not true. In every place that levies income tax in which his team plays games, a ballplayer on a big league roster is responsible for paying them. Regardless of whether he plays 81 games at home as, for example, a member of the Astros in Houston, located in a state with no income tax, when the Astros play their 19 road games in California (top income tax rate: 13.3%), he would owe the Golden State tax on (19÷162 =) 11.7% of whatever his total salary for the year is. Same goes for all the other games in all the other taxing places his team plays in. So no matter what team Bryce Harper plays for, he’ll be paying a boatload in state income taxes to a bunch of states.

The other point is that, regardless of which team Harper ends up playing for, he’s going to pay the same in federal taxes no matter what, which makes sense. Why would his federal tax burden be any different playing in New York versus paying in Tampa Bay? Of course it wouldn’t be. Although you might be surprised to learn that even though one team plays in Canada, which obviously has a different federal income tax scheme than the US does, the tax brackets of the two countries are surprisingly similar, with Canada being even a touch lower at the top end than the US is. So, for this exercise, let’s assume that regardless of what team Harper ends up playing with, his federal tax burden to his team’s country will be the same. As such, our focus is not federal income tax; it’s only local income tax.

OK, now: to get at what the difference in local tax burden would be based given each of the thirty teams Harper could possibly play for, we had to determine how many games each team would be playing in each state in 2019. There are seventeen different states, one province and one District of Columbia (let’s call them all “states” for this piece) that are home to big league teams. Three of these states (FL, TX, WA) collect no income tax at all. Five others (CA, NY, DC, MN, Ontario) impose very high state income tax rates of at least 9% at the top end. The remaining eleven range from about 3% (PA) to 6% (GA). In addition, ten teams play in cities that levy their own income taxes, ranging from 1% (KC, STL) to a top end of 4.25% (NYC). It’s a veritable hodge-podge of Thanks For Playing Here, Now Pay Up.

To put actual numbers on this, let’s assume that Bryce Harper signs on to play for a base salary of $35 million next year. That seems as good a guess as any at this point. Personally, I think he’s probably going to sign a one-year deal for $35 million, tops. Given his inconsistent performance of the past three years, as well as testing positive for injury history, I don’t think he’ll be getting the terrain-adjusting 10/400 deal he and his agent have been craving. I think recency will make teams think twice before committing to him for so much money and so many years, so I can see Bryce wanting a shot at putting up an MVP level season in 2019 so he can get his 10/400, or even better, next winter. I won’t belabor this point anymore, since it belongs in another article anyway. Let’s just say in 2019, one way or the other, Bryce is going to sign for $35 million.

That’s not the income he’s going to be paying tax on—there will be write-offs and exemptions and deductions and the like that his first-rate tax attorneys will find, so let’s say all of that leads to an adjusted gross income for tax purposes of $30 million. That’s the number we’ll use as the basis of Bryce Harper’s state and city tax burden for next year.

Lastly, these tax estimates are based on the actual tax rates each of these states and cities levy on income earners in their jurisdictions, including the application of graduated rates where appropriate (mostly in high tax states, and in New York City). Even so, with only a few exceptions, the vast, vast majority of Bryce Harper’s income will be taxed in all these states and cities at the highest rate available.

Here’s the result, rounded off to the nearest $10,000 to make it easier to take in. Remember, these are not taxes he pays only to the city or state his team calls home—they’re taxes paid to all the jurisdictions he plays in during the season:

Holy Toledo, is this ever a huge difference. Choosing a California National League or a New York City team, just by itself and independent of anything else, will take an additional $2 million out of Bryce Harper’s pocket than choosing the Houston Astros. Are you scared yet, Yankees/Red Sox/Indians/Angels/A’s fans?

Now, to be clear, it’s not as though we should cry for Bryce Harper because of his heavy tax burden. Bryce Harper has been a multimillionaire ever since he was 17 years old. He is a very rich young man who is on his way to becoming a very wealthy young man. (If you’re unclear on the difference between being “rich” and being “wealthy”, here’s a very entertaining and very NSFW tutorial.) So let’s not feel as though we need to light any novena candles on behalf of Bryce Harper.

By the same token, even for a man as rich as Bryce Harper, $2 million is not nothing. It’s decidedly something. And remember, that’s $2 million based on one year of Bryce’s salary alone. Over the course of the kind of ten-plus year contract he’s looking for, that could well add up to over $20 million in wages lost just to local taxes, for no other reason than he might choose playing for the Dodgers over playing for the Astros. Or over playing for the Rangers or Mariners or Marlins.

You can laugh about that last one now, because math class is over.

A significant challenge in baseball research is identifying when a player has made a transformational adjustment that results in a step-change in playing level (i.e. J.D. Martinez in 2013) vs. a player who has a great, yet unrepeatable year. Mookie Betts and Alex Bregman both had excellent years in 2018 and a call for regression would be expected. However, this research note presents data which suggests that Mookie Betts did indeed make a transformational mechanical change and will likely perform at high levels going forward while Alex Bregman’s improvement does not share the same solid underpinnings.

I recently examined the relationship between backspin and performance in this post. One of the key takeaways from that research was that no player in the highest backspin quartile (since the data started in 2015), has consistently put up “superstar” numbers. In fact, Mookie Betts was in the high backspin group and had the second highest wRC+ of 122 over the 2015-2017 time period – not “bad” but far from a super-star level. With Betts’ phenomenal 2018, I was curious if he was the only high backspin hitter to “break out” or if he made a significant change to his swing mechanics to hit the ball more “square.”

After reading that he and J.D. Martinez were working together on mechanics, I was curious if his backspin profile changed from prior years. Not only did it change, Betts had the largest reduction in backspin of all Qualified Hitters in 2018! Here is a list of the top and bottom ten backspin changers over last year:

Alex Bregman, on the other hand, had the sixth largest increase in backspin of all Qualified Players. Take a look at a comparison of Exit Velocity (EV), Launch Angle (LA) and Distance for the two players on well-hit fly balls (EV>=90, LA>=15).

Both Betts and Bregman had an EV increase of approximately one MPH. The change in the launch angle profile between the two hitters is significant – Betts added five degrees of launch angle compared to Bregman’s two-degree reduction. Betts should have had a distance gain; however, the fact that he didn’t is actually a positive based on the data. Thus, while Betts is showing a 13 ft. distance decrease over last year, Bregman had a 14 ft. increase. Most of Bregman’s distance increase is from backspin – a very unhealthy source based on the data.

While beyond the scope of this research note, the mechanical drivers responsible for changes in spin are Vertical Bat Angle, the amount of Explicit Swing Loft (also referred to as “Attack Angle), and the ball contact point (above or below the ball equator). Backspin increases with lower levels of Vertical Bat Angle and Explicit Swing Loft (Attack Angle) while “square” contact increases with larger values. More to follow on this in a future post. Because of the link between swing path quality and backspin, using distance as a performance metric in isolation is highly problematic – and can lead one to the opposite conclusion in projecting performance. In other words, it matters where the distance change is coming from.

In addition to the amount of backspin, other metrics such as the Standard Deviation of Launch Angle and a player’s IFFB% also have a strong relationship to the quality of a player’s swing path. Using a quartile ranking system for each of the three metrics, four players were in the top and bottom quartiles for all metrics in both 2017 and 2018. The difference in performance of the two groups is quite telling:

Wow! Considering only swing path quality metrics, the performance between the two groups is worlds apart.

To get a sense of the magnitude of the change for Mookie Betts in 2018, he was in the fourth quartile for all three metrics above in 2017. He moved from the fourth to the second quartile in backspin, fourth to first in Standard Deviation of Launch Angle, and fourth to second in IFFB%. Alex Bregman, on the other hand, moved into the fourth quartile for all three swing path quality metrics in 2018.

I have followed Bregman’s swing for some time and have made some timely performance predictions (in both directions) based on video. The backspin and swing path quality data, on the other hand, point to longer term issues that may not surface immediately. After all,  backspin improves the performance of balls hit but is inversely related to player performance given sufficient frequency (i.e. PAs). Thus, getting the precise timing of a performance shift based on the above data is difficult. However, without a swing path change for Bregman, the odds suggest that significant regression is not a matter of “if” but “when”.