The Boston Red Sox recently signed starting pitcher David Price to a seven-year, $217 million contract. That works out to $31 million per year. Not to be outdone, the Arizona Diamondbacks then signed pitcher Zack Greinke to a six-year, $206.5 million contract. Using straight division, Greinke’s contract calls for an average of $34.4 million per year, but the deal includes $60 million in deferred money that will be paid out in the five years following the end of the contract, so Greinke won’t be making $34.4 million next year. No matter how you look at it, though, these are big money deals.

There are many comparisons you can make with this. For starters, each time David Price heads out to pitch next season he will be making around one million dollars. David Price has averaged 217 innings pitched over the last six seasons. If he pitches 220 innings next year, he’ll make around $140,000 per inning. At 15 pitches per inning, that’s more than $9,000 per pitch. David Price will make as much money for throwing six pitches next season as the average public school teacher makes in a year.

In the world of Major League Baseball there are good arguments to be made that Price and Greinke will be worth the cost of their contracts. The most likely scenario for a long-term, big-money contract is that the player provides surplus value in the first few years of the deal but ends up overpaid in the last part of the deal. Baseball is flush with money right now for a number of reasons, including strong attendance numbers, but the big drivers behind the current economic strength of the game are cable television contracts and Major League Baseball Advanced Media (MLBAM). Baseball has done a very good job of establishing an online presence through MLBAM, which allows fans to follow their teams on assorted electronic devices beyond TV and radio.

Also, the way people consume entertainment these days is a big factor. More and more people have an on-demand mentality when it comes to their entertainment choices. No longer do we have to be in front of the TV at nine o’clock on Wednesday night to watch Modern Family. We can just record it and watch it later. If we miss the first few seasons of a popular show, we can binge-watch past seasons and catch up. We can record a week of Jeopardy! shows, then watch five in a row on a Saturday afternoon.

Sports are different. Most people want to watch sports live and this gives baseball (and other sports) a huge advantage. Sports fans have to be in front of the TV—or watching on a smartphone, a tablet, or a computer—while the sport is happening. We want to talk about it with friends, tweet about it on Twitter, and complain about the refs on Facebook. This strong desire to watch sports live makes sport programming a highly desirable commodity for networks and results in the big money TV contracts that baseball teams are signing.

So when you read about David Price or Zack Greinke signing a contract that will pay them $30 million or more per year, you have to understand that teams have enough money to pay them. They wouldn’t dish it out if they couldn’t afford it. These contracts aren’t unreasonable in the context of the game. As much as Price and Greinke are making, the owners of their teams are making more. Getting paid $30 million per year is not so ridiculous in the context of Major League Baseball in 2015. This is the going rate for a top pitcher these days.

As a matter of fact, Major League Baseball players are earning a much lower percentage of league revenues than they did a dozen years ago. Back in 2002, MLB player salaries were 56% of league revenues, but it’s been dropping steadily ever since. Their share dropped below 40% in 2014. That’s a significant decrease. Imagine how much pitchers like Price and Greinke would be making if the players’ share of league revenue hadn’t declined so much in that time period. Where is that money going now? In the pockets of the owners, of course. Baseball is flush with money these days and player contracts reflect that, but they could actually be making much more than they are now. Instead, the owners are making it.

In the world where most of us reside financially, it seems ridiculous to have a professional athlete make that much money, especially when compared to a teacher, a construction worker, a police officer, or any other job where people put in a good day’s work to make enough money to pay their rent and feed their family. This is where it can be frustrating for fans. Most of the people sitting in the stands or watching the games on the electronic device of their choice will never come close to making the annual salary of a major league rookie (around $500,000).

And it’s not just sports. There are plenty of other high-income fields with ridiculous salaries. According to Forbes.com, movie star Robert Downey Jr. will make $80 million in 2015. Jackie Chan will make $50 million. Vin Diesel will make $47 million. On the small screen, Jim Parsons, who plays Sheldon Cooper on The Big Bang Theory, makes $29 million per year. His TV roommate, Leonard, played by Johnny Galecki, makes $27 million. Even smarmy Howard Wolowitz (Simon Helberg) and his awkward buddy Raj (Kunal Nayyar) will each make $20 million.

Howard Stern earned $95 million between June 2014 and June 2015, with $80 million of that coming from Sirius XM satellite radio. Ellen DeGeneres made $75 million in that time span. Thanks to his long-running talk show and the release of his 13^th book, Dr. Phil McGraw made $70 million. Kim Kardashian nearly doubled the amount she made from the previous year thanks to her role-playing app Kim Kardashian: Hollywood. She made $52.5 million from June 2014 to June 2015.

The simple fact is, athletes and entertainers are making million and millions of dollars because we spend our money to watch them. It’s very easy to say that a famous athlete or actor shouldn’t make 500 times as much as a schoolteacher, but we all make choices in how we spend our money and those choices dictate how much the athletes we love to watch will earn. We go to the games, we watch the movies, we subscribe to cable or Netflix so we can watch our favorite shows. Every time we choose to spend our money on entertainment, we’re contributing to the high salaries these people are making.

I have friends who are continually shocked by the big contracts that baseball players sign. They think it’s ridiculous. When I get into a conversation with these people about this topic, I always think about this quote by Bill James from the book, The Mind of Bill James: How a Complete Outsider Changed Baseball (2006):

“One of the unwritten laws of economics is that it is impossible, truly impossible, to prevent the values of society from manifesting themselves in dollars and cents. This is, ultimately, the reason why we pay athletes so much money: that it is very important to us to be represented by winning teams. The standard example is cancer research; letters pop up all the time saying that it is absurd for baseball players to make twenty times as much money as cancer researchers. But the hard, unavoidable fact is that we are, as a nation, far more interested in having good baseball teams than we are in finding a cure for cancer.

That pool of money which we pour into athletics makes it inevitable that athletes are going to be better paid than cancer researchers. Dollars and cents are an incarnation of our values. Economic realities represent not what we should believe, not what we like to say we believe, not what we might choose to believe in a more perfect world, but what our beliefs really are. However much we complain about it, nobody can stop that truth from manifesting itself.”

I live in Washington state, one of only seven states that does not have a state income tax. During the Great Depression in the early 1930s, Washington came very close to instituting a state income tax. Times were very hard back then and people were struggling just to put food on the table. Voters first voted to change the constitution to allow an income tax, then voted to approve the tax, with 70% in favor. An income tax was more popular among the voters than bringing back the sale of beer.

Local business owners could see where this was headed, so they challenged the tax in court. In 1933, this challenge reached the Supreme Court in Olympia and was voted down 5-4. Since then, a state income tax has come up for a vote seven times and voters have rejected it every time.

A measure was on the 2010 ballot that would have created an income tax on earnings over $200,000. This tax would affect fewer than 70,000 people out of the state’s 6.7 million residents and would provide money for education and health care. It was rejected by 65 percent of the voters. A dozen years before, voters had approved funding for the construction of CenturyLink Field, home of the Seahawks, even though the Seahawks’ Paul Allen is the NFL’s richest owner, worth $17.5 billion. I’m sure if you ask residents of Washington which is more important, education and health care or professional sports, they would say education and health care. But how they chose to spend their money says otherwise.

Income inequality has been and will be a big topic in the news over the next year. Not to get into the politics of the issue, but the statistics are clear. There is a growing disparity between what the majority of people in this country earn and what the richest people in this country earn.

In the most simple terms possible, the rich are getting richer. We often hear about the growing disparity between what the top 1% earns compared to the other 99%. It’s true; the gap has grown significantly over the last 30 years. Looking at the difference between the top 1% and the other 99% doesn’t tell the full story, though.

This IRS report showed the top 1% had an adjusted gross income (AGI) of $434,600 or more in 2012. The MLB minimum salary in 2015 was $507,500, which means every player in the major leagues is in the top 1%. It’s the level above the top 1% where the disparity is even greater and the gap is growing more quickly. The top .01% of tax returns in 2012 had an AGI of $12 million or more. Of the roughly 750 players in Major League Baseball in 2015, 121 made at least $10 million, which is about 16%. We could estimate that 10-15% of MLB players are in the top .01% of income earners.

The top .001% of tax returns had an AGI of $62 million. No player is in that range yet, but Bryce Harper will be a free agent heading into his age-26 season in 2019. With Zack Greinke having just signed a contract worth $34.4 million per year, will Bryce Harper be baseball’s first $50 million per year player in three years? If he stays healthy, we all know he will sign a record-setting contract. When he does, it’s very likely that our friends who don’t grasp the economics of Major League Baseball will lament the fact that a baseball player is making so much money. Then they’ll go to the theater and spend $15 to watch a movie starring an actor making $60 million and think nothing of it.

On this year’s Hall of Fame ballot, there are 15 newcomers who the BBWAA has never gotten a chance to vote for. Only four of these guys, Ken Griffey Jr., Trevor Hoffman, Billy Wagner, and Jim Edmonds, have a reasonable chance of garnering the 5% of votes required to survive until next year’s ballot. But of course, ever year, there is that one voter who for whatever reason thinks that Aaron Sele or Armando Benitez was a Hall of Famer. Yes, the dreaded pity vote.

Now, there are some standards for a pity vote. It’s not just about falling off the ballot after one year. Despite not managing to get the necessary 5% last year, Carlos Delgado did not get 21 pity votes.. He was too reasonable a candidate with a significant amount of support. Hideo Nomo in 2014 was also not a pity candidate, despite only getting 6 votes, good for 1.1% of the picks. That’s more support than any third party had in the 2012 presidential election. We’re talking about guys that get 2 votes, maximum. Any more than that and it’s a trend, and we’re too edgy to vote for any mainstream candidates. So who are the deep-cut candidates of the 2016 Hall of Fame election?

There is Mark Grudzielanek, who is probably the guy least likely to get a vote. He was not particularly memorable nor did he stick around very long with any one team. If you feel like trolling the system, then just pick David Eckstein who was the exact same player with more gritty-gamer-clutch-Harold Reynolds-scrappy-played-the-game-the-right-way narrative working for him. Of course, Eckstein may get too much support. Would it shock you to see Eckstein get 3 votes, either from the old fogey crowd or from some edgy troll voting ironically?

Including Eckstein, there are a lot of 2002 Angels’ championship team on this ballot, which is funny because there are no legitimate Hall of Fame candidates from that roster. Troy Glaus was legitimately a star for a few seasons, so I could see an Angels beat writer or someone tossing him a vote. Same could be said for Garret Anderson, except he was much less good than Glaus.

Speaking of Anderson, let’s play a fun game! Here are two mystery players from 2002:

Player A hit .344/.354/.516.

Player B hit .306/.332/.539.

You probably guessed that one of them is Garret Anderson, and you would be right? You may have even guessed that he was Player B.

You probably did not guess that Player A was Mike Hampton.

Hampton is mostly remembered as a disappointment because of his poor, injury-muddled play after signing the largest contract in baseball history. He was probably a better player than either Garret Anderson or David Eckstein, but I doubt he’ll get a vote. I also doubt that Mike Sweeney will get a vote, mostly because I cannot recall anything interesting about him. Maybe he’ll get thrown a bone by some masochistic Royals writer longing for the good ol’ days of 2001, lamenting the current success of the franchise.

Randy Winn played like a Hall of Famer for like 2 months after being traded by the Mariners to the Giants in 2005. He wasn’t really special aside from that stretch. Luis Castillo and Mike Lowell combined to win 5 World Series rings, including one each with the 2003 Marlins. Good players. Lowell did win World Series MVP honors in 2007 with the Red Sox, so maybe he gets one vote for that. Other than that, I doubt any of these guys will manage to get pity. Brad Ausmus is probably the worst player on the ballot. He was the guy you were trying to upgrade from, not the one you actually wanted to start. Unless he made quick friends with someone in the Detroit press, he’s not getting a vote.

No, the best candidate would be Jason Kendall. He has at least some of the intangible goodness that Eckstein has wrapped up in a player who was actually pretty good. Kendall was a prototypical lead-off hitter who played catcher. A weird combo, but an interesting one. Kendall led off 50 times in 5 different seasons. No other catcher since deadball has done that even once. Kendall was actually a good lead-off hitter too. Had the Pirates utilized good players elsewhere in the lineup, he would have been batted in many times by them. Kendall may have had a real Hall of Fame case had he continued what he was doing for like a decade more instead of falling off a cliff. Alas, it was not to be.

So, if you happen to have both a Hall of Fame ballot and a desire to rebel against the conformity of the system and vote for someone unique, Jason Kendall is probably your man. Or maybe Troy Glaus, who was probably about as good, but less much interesting.

Or just vote for ten guys who actually, you know, deserve to be in the Hall. That’d be good too.

Every year, we hear about batters taking a new approach at the plate that they expect to generate better outcomes. But, as has often been shown, a lot of player tendencies are hard-wired. Players generally don’t change that much. What happens when they do?

In June, I looked at hitters who were pulling the ball a lot less or a lot more than they had in 2014. The conclusion was that it didn’t really make much of a difference, in aggregate, on offensive performance, although some players did markedly better and some did markedly worse. Now that the full season’s in the books, I decided to take another look at the comparison to see how a change at the plate affects hitting.

To look at this, I selected hitters with 350 or more plate appearances in both 2014 and 2015, corresponding roughly to at least half-time play. There were 173 such players. Using that sample set, I evaluated three observations you hear a lot about modern hitters:

• They pull too much, allowing infielders to get extra outs by shifting. If they’d hit to the opposite field, they’d do better.
• They try to hit everything into the seats, resulting in too many infield flies and lazy fly balls to the outfield instead of hitting sharp grounders that can become singles.
• They’re too passive, getting behind the count by watching pitches.

I looked for changes in pull tendency, ground vs. air batted balls, and aggressiveness at the plate, measured by net pull percentage (i.e., percentage of balls pulled minus percentage hit to the opposite field), ground ball/fly ball ratio, and swing percentage as proxies. To gauge the impact of the changes, I looked at change in wRC+, since it is a park- and season-normalized comprehensive measure of hitting.

It’s important, I think, to make a distinction between a change in outcomes to a change in approach. Take pulling the ball. If a batter pulls the ball less from one year to the next, it could be because he’s consciously trying to spray the ball over the field more in order to become less predictable and therefore harder to defend. Mike Moustakas comes to mind. But a batter may pull less because of the effects of age and/or injury, making his bat slower and unable to turn on inside fastballs. Since we can’t divine approach from full-season statistics, we’ll have to satisfy ourselves with outcomes. Among the 173 players in the sample, Victor Martinez had the largest decline in hitting the ball hard, and his wRC+ decline of 90 points was similarly the largest in the group. That doesn’t mean that he went into the season deciding to hit the ball softer, and that his strategy backfired. Rather, it was a reflection of Martinez’s health. A change in outcomes isn’t necessarily reflective of a change in approach.

I ranked the 173 players by their change in pull tendency, ground vs. air batted balls, and aggressiveness at the plate, and divided them into quintiles based on plate appearances. As an example, for pull tendency, the quintiles were players who went the opposite way a lot more (net pull percentage down 7.5% to 25.9%), those who went the opposite way somewhat more (net pull percentage down 3.6% to 7.4%), those who hit about the same (net pull percentage down 3.5% to up 0.1%), those who pulled somewhat more (net pull percentage up 0.2% to 5.0%),and those who pulled a lot more (net pull percentage up 5.0% to 17.8%). I also selected examples of players whose wRC+ was considerably better or worse in 2015 for each quintile. Generally, these were the players at the top or bottom of the rankings, though I did ignore obviously injured underperformers like Martinez and Jayson Werth.

In the tables I’m going to display, there are a lot of negative numbers for change in wRC+. The reason is that among the 173 players with 350 or more plate appearances in 2014 and 2015, the average wRC+ declined by 5.2 points (from 109.6 to 104.4), or 4.3 points (110.9 to 106.6) weighted by plate appearances. While that may be a topic for future research, it’s not a shock, given aging curves, regression, and the emergence of young talent in the majors.

Players who pulled a lot more or went the other way a lot more in 2015 than in 2014 did better than their peers. (Again, the average player’s wRC+ declined by 5.2 points, or 4.3 weighted by plate appearances). Those who went the opposite way a lot more improved relatively, and those who pulled a lot more improved both relatively and absolutely. If there’s a benefit to hitting to the opposite field for pull-happy sluggers who make too many outs by hitting the balls to shifted infielders, we’d see the change in wRC+ decline as the net pull percentage increases. That’s not what happened. Bryce Harper, Chris Davis, and Shin-Soo Choo, among others, benefited from pulling more, not less.

Players’ ground ball tendencies, similar to their pull tendencies, resulted in positive variance at both extremes. Players who hit the ball on the ground a lot more improved relative to their peers, and those who hit it in the air a lot more improved relatively and absolutely. Harper’s an outlier again—he pulled a lot more, hit the ball in the air a lot more, and produced a lot more runs. It’s amusing to see Red Sox teammates Xander Bogaerts and Hanley Ramirez as prime examples of what can go right or wrong if you hit a lot more ground balls.

This project turned out to be murkier than I would’ve liked. Did batters who pulled a lot less, or those who it the ball on the ground a lot more, do better in 2015 than they did in 2014? Yes, but so did those who pulled a lot more and hit the ball in the air a lot more. And those are only aggregate figures; in every quintile, there are examples of batters who were a lot better or a lot worse. And we can’t completely tease out the change in approach from the change in a batter’s health or age or the way he’s pitched. About the only thing that seems to be safe to say is that swinging more is a dubious strategy. If a player goes into spring training talking about getting more aggressive at the plate and taking a lot more hacks, we might hope that his batting coach can talk him out of it.

Pirates pitchers hit more batters than any team in the majors this year, 75. They also led in 2014. And 2013. That’s unusual. The only teams to have lead the majors in hit batters for three or more seasons since 1901 are the 1921-23 Phillies, 1930-32 Cardinals, 1938-40 Senators, 2002-04 Rays, and the 2013-15 Pirates.

The Pirates also got hit more than any team in the majors this year, with 89 hit batters. On one hand, that makes sense, given baseball’s Book of Exodus stance: A hit batter for a hit batter. On the other hand, and more significantly, it’s been a rare occurrence. Since 1931, only 14 teams have led their league in both pitcher and batter hit by pitches (1943 Giants, 1947 Dodgers, 1955 Dodgers, 1963 Reds, 1966 White Sox, 1968 Astros, 1980 White Sox, 1982 Angels, 1983 Expos, 1996 Astros, 2009 Phillies, 2012 White Sox, and 2013 and 2015 Pirates). Only 8% of teams in that time span have led their league in both hitting batters and getting hit. Pure random chance would put that figure above 9%. It just doesn’t happen very frequently.

I should interject that I fall in the anti-hit batters camp. I don’t like seeing anybody getting hit by pitches. Sometimes they shake it off. Sometimes they miss time. Sometimes it’s horrifying. But when you consider that there were 1,602 batters hit last year, 844 on fastballs, and the average fastball velocity is 92.1 mph—well, they’ve all got to hurt. As I’ve discussed in previous posts, some hit batters are clearly accidents, often occurring when a pitcher, ahead in the count, comes inside on a pitch and misses. But some undoubtedly are a form of message-sending, with the message coming as a hard object thrown at a speed that would constitute assault were it not on a baseball diamond. (A notable case occurred when Cole Hamels hit Bryce Harper in 2012, then justified it on the grounds of “that old-school prestigious way of baseball.”) Intentionally throwing at hitters to exact some sort of vengeance, sorry, is dumb. But how often does it happen?

The Pirates provide a good test case, since by leading the league in hit batters on both offense and defense, they provide a decently large sample size. Here’s how large: Pirates batters were hit 89 times, tying them for 11^th among the 1,926 team-seasons since 1931. Their pitchers hit 75 batters, tying them for 43^rd. If you saw a lot of Pirates games, you saw a lot of batters getting hit.

And you heard a lot of excuses. The Pirates encourage pitching inside, drawing the ire of other clubs. But Pirates backers also point to the large number of Pirates batters who get hit, and the need for the pitchers to “protect” Pirates batters. You hit my Andrew McCutchen, I hit your Joey Votto. That sort of thing.

How often does that happen? Is protection–really, retaliation–a significant factor in batters getting hit? To try to answer, I classified every hit batter in Pirates games last season—164 in total—into three different categories:

• First Blood: Named in honor of the great American thespian Sylvester Stallone, the standard by which actors have been judged. (The New York Times memorably described Arnold Scharzenegger as “the thinking kid’s Sylvestor Stallone.”) First Blood (the initial work in Stallone’s Rambo oeuvre) occurs when a batter is the first one hit in a game or series.
• Retaliation: As a follow-up to First Blood, Retaliation occurs when a batter is hit by the pitcher whose teammate was last hit.
• Piling On: This occurs when a team, having already had a batter hit, suffers another, with no intervening Retaliation.

(I realize that I’m ignoring hit batters as retaliation for things like inside pitches, hard slides, and being Bryce Harper. Those don’t show up in game summaries, and besides, that’s more two-eyes-for-an-eye and therefore less acceptable.)

The timeframe is important here. Hit batters occur in the context of a game, but the casus belli can stretch out longer. Al Nipper hit Darry Strawberry with a pitch in spring training of 1987, allegedly in retaliation for Strawberry taking a slow trot around the bases after hitting a home run off Nipper in the prior year’s World Series. So I looked at hit batters in three settings:

• The game being played
• The series between the teams, to see whether retaliation carries over from one day to the next
• The season series, to capture longstanding grudges.

For example, on July 12, the day before the All-Star break, the Pirates’ Arquimedes Caminero hit the Cardinals’ Mark Reynolds with a pitch in the tenth inning. The next time the two teams played was on August 11. The Cardinals’ Carlos Martinez hit Pirate Aramis Ramirez in the first inning. That’s First Blood for the game and series, but Retaliation for the season series, since the prior hit batter, albeit a month earlier, was a Cardinal. Two days later, Pirates catcher Francisco Cervelli was hit by a pitch from Lance Lynn in the first inning. That was First Blood for the game, but Piling On for both the series and season series, as it followed his teammate getting hit. The next time the teams played, on September 4, Pirates reliever Jared Hughes hit Reynolds with a pitch in the ninth inning. That counts as First Blood for the game and the series, Retaliation with respect to the season series. The following day, the Pirates’ Starling Marte was hit by Jaime Garcia in the second inning. That was First Blood for the day, Retaliation for both the series and the season series. In the bottom of the second, Charlie Morton hit Jon Jay. That’s Retaliation in the context of game, series, and season series.

(Another aside: I am opposed to the use of plunked as a synonym for hit by pitch. Plunk is what happens when you’re rearranging books on your bookshelf and a paperback falls from a high shelf and hits you in the shoulder, or when you’re walking in the woods and an acorn hits your head. A 92.1 mph fastball is not a plunk.)

You may be thinking: This is pretty stupid, categorizing hit batters, what’s the point? The point is that if the Pirates pitchers are hitting opposing batters for some sort of tribal/protection/vengeance thing, we should see a lot of Retaliation. If that’s nonsense, it’s not the case.

Say a team plays 19 opponents, as the Pirates did (every National League team, plus the American League Central). Let’s also assume that the team’s pitchers hit 75 batters, as the Pirates did, and the team’s batters were hit 89 times, again as the Pirates were. If hit batters are random, we’d expect the team to be throw 19 x 75 / (75 + 89) = 8.7 First Blood pitches and get hit by 19 – 8.7 = 10.3 such pitches in season series. Thereafter, the odds of a hit batter being Retaliation or Piling On would be 50/50, subject to the distributional difference between 75 and 89. So the team would log 33.2 Retaliation and Piling on hit batters, and get hit by 39.3 of each type of pitch. Again, this assumes that hit batters occur completely randomly.

Here are the actual totals:

This kind of refutes the self-defense argument, doesn’t it? A Pirates batter was hit by a pitch before an opponent was in 61 games, accounting for nearly 70% of the team’s hit batters. But Pirates pitchers drew first blood in 56% of their games as well. Overall, retaliation accounted for only 20% of batters hit by Pirates pitchers in games. Over the course of a series, when my hit batter today can result in your hit batter tomorrow, retaliation explains only 32% of Pirates opponents hit. Even with the most liberal definition of retaliation, when it can be spread over the weeks or months of a season series, it still accounts for just 43%, less than half of batters hit by Pirates pitchers. Not that it was different on the other side: Pirates hit in retaliation accounted for only 15% of hit batters in games, 33% in series, and 39% in season series. The majority of hit batters occurred without seeming provocation.

Let’s compare the results of the Pirates games to those of the random distribution presented above. For Pirates pitchers, a random distribution would be 9 First Blood, 33 Retaliation, and 33 Piling On. Actual figures: 9, 32, 34. For Pirates batters, a random distribution would be 10 First Blood, 39 Retaliation, and 39 Piling On. Actual figures: 11, 35, 43. Those distributions (1) are pretty close to random and (2) feature less retaliation than a random distribution would suggest.

So what does it mean? Well, retaliation definitely does occur. We saw it the National League wild card game, when Pittsburgh reliever Tony Watson pretty clearly hit Cubs pitcher Jake Arrieta on purpose, in response to Cervelli and Josh Harrison getting hit by Arrieta, resulting in the silly spectacle of the benches clearing. But the example of the Pirates’ regular season, when there were a lot of hit batters, shows that retaliation isn’t as common as either code-of-honor defenders like Hamels nor hand-wringers like I might think. The numbers instead suggest that hit batters are, in fact, pretty random. Which would seem to make intentionally hitting batters a really uninformed idea as well as a bad one.

When I started this piece the Red Sox were going hard for David Price, but they hadn’t signed him yet, and it still wasn’t anywhere close to being a guaranteed deal. Now Price has signed with the Red Sox and Greinke is headed to Arizona (who saw that coming), so this piece is no longer realistic (as though it ever was). I still think it is interesting to think about however, so here you go.

Situation: Price signs elsewhere and the Red Sox are forced to pursue Greinke. As some have hypothesized, Greinke is inclined to stay in the National League so he can continue to hit. To sign him, the Red Sox will have to overpay by a significant margin. Either that or let him hit?

Okay, first a clarification: Greinke would not be the new DH (could you imagine replacing Ortiz on his retirement tour with Greinke). No, he would be given the opportunity to bat, say, in twenty-five of his starts next year (in the contract it would then be determined, the number of games Greinke would get to hit the following years, based on how he hit in the previous year). A few of those starts will be inter-league games, possibly a couple of them would be to give Ortiz a day off, but mostly Ortiz would hit for another player on the field. You might say that wins are money and that since this would cost you wins you should just cough up the money to get Greinke to come to Boston. But what if this would hardly cost you any wins at all? What if the team could be just as good when Greinke hit?

The first thing to do is to find out how good Zack Greinke has been at hitting. In hit National League career he has a wRC+ of 67, though over the last three years he has seemed to improve, hitting to a wRC+ of 87. To give a comparison, Madison Bumgarner, known as a very good hitting pitcher who has even pinch-hit on occasion, has a career 49 wRC+ and a 73 wRC+ over the last three years. It does seem like Greinke has improved, hitting-wise, lately, but he is a pitcher, and you can’t expect too much out of him, so we will take his median wRC+ over the last three years, 74, as a reasonable true talent. So this was a starting point to compare this to other players.

The first name that seems interesting is Ryan Hanigan. Unlike some other Red Sox players who haven’t hit that well of late, no one really expects him to improve. Over the last three seasons he has a wRC+ of 75. This is basically equal to Greinke’s prescribed true talent, so it seems as though we could break even. Against righties however, Hanigan had a wRC+ of 69 over the three-year span, and it was even worse last year at 62. So, it seems that against righties, Greinke, whose wRC+ hardly drops in his three-year sample size, might even be the better hitter. Additionally, Greinke is actually the better baserunner as well. Over the last three years, Greinke is the best baserunning pitcher in baseball, with a BsR score of 0.5, slightly above average. He joins only four other pitchers as above-average baserunners over that time period. Hanigan on the other hand is a below-average baserunner, with a BsR of -4.0 over the last three years. This is just another reason for Greinke to hit instead of Hanigan.

If Hanigan really was the backup catcher, then, assuming Greinke was the better hitter against righties, the Red Sox would already be close to working out a good way for to hit Greinke. Hanigan would become Greinke’s personal catcher, and Greinke would hit instead of Hanigan against righties. Hanigan though is only the backup catcher until Vazquez is healthy. While he has had a setback in playing winter ball, he is expected back early next year. So Greinke hitting for Hanigan may only be an option for around a month.

Vazquez, Castillo and Bradley are all other options to hit for against righties. Bradley and Castillo have had 65 and 69 wRC+’s against righties, respectively. These would seem like great options to pinch hit for, except for the fact that they are supposed to be good candidates to improve. Depending how they do early in the year, both could be able to be hit for by Greinke, though it wouldn’t be great for their confidence. Vazquez actually hit slightly better against righties in his very limited tenure in Boston, though that could reverse itself, since he is right-handed. So it seems as though the Red Sox can piece together 10-15 games where, because of personnel or days off, it makes enough sense to have Greinke hit against righties. They still need 10-15 more starts however.

This brings us to facing lefties, and Pablo Sandoval. Last year was a bad year for Sandoval, but even before that he was bad against lefties. Over the last three years he has had a wRC+ of 61 against lefties. Last year it was even more horrendous, however, as he had a score of 21. Pair this with his -15.1 Def rating last year, and it seems obvious he should not be playing third base with a righty on the mound. The Red Sox may sit Sandoval against lefties anyway, but this could be an opportunity to hit Greinke and get better defense. If the Sox were planning on having Greinke hit, they would do well to try to find a cheap, good-fielding third baseman. If the Red Sox could find someone like Gordon Beckham, who is an inexpensive, above-average defender at third base, that would be a big upgrade on defense. He had a positive 5.5 Def rating playing mostly third last year, and cost the Braves only $1.25 million plus incentives. There are probably countless others, though, that could fill this role.

Sandoval had a wRC+ of 99 against righties last year, so it doesn’t seem like he would be hit for against righties, but if his defense or hitting doesn’t improve, he could be a candidate to be hit for once in a while, even against righties. This is especially the case, given the importance of third base defense when Greinke is pitching. Looking at Greinke’s batted ball spray chart, you see a lot of ground balls. Focusing on those ground balls, you can see third base got a decent amount of attempts, especially ranging left and right, which is Sandoval’s weakness. So, at the rate Sandoval played last year, though he is expected to improve at least slightly, Greinke could hit for him all the time, with a good defender at third.

One other thing that should be mentioned is what will happen once Greinke leaves the game. When bullpen pitchers come in, they would then occupy Greinke’s batting spot. This is not as big an issue as it may appear, because bullpen pitchers will usually get pinch-hit for, but it would force Farrell to manage more of a National League game. It is unfortunate that the DH cannot be moved around in the batting order like every other position, but the Red Sox would just have to make use of their fairly deep bench.

Additionally, since 2010 the National League has only scored around six fewer runs per year than the American league from the seventh inning onward. This is the time in the game when the starter is generally out of the game, so National League teams can pinch-hit for their relievers. Since Greinke would only bat in 1/6th of the games, this averages out to be a run per year, or about 1/10th of a win. It could be even less than that since the Red Sox have a quality bench. So the disadvantage of having bullpen pitchers with lineup spots seems to be incredibly minuscule, even almost unnoticeable.

On average, around a third of pitchers are lefty. If the Red Sox try to line up Greinke against lefties, you can probably assume that it will happen around a dozen times. If Greinke gets six starts in April, he will probably face a righty in about four of those games. Greinke will bat for Hanigan on those occasions and for Sandoval against lefties, leaving nine more batting days for Greinke. The Red Sox could probably find nine more days to both take the defensive upgrade and have Greinke bat, rest a slumping player, or simply give starters a day off here and there. These might be slight disadvantages for the team, but could possibly be neutralized with the possible upgrades when Greinke bats for Hanigan and Sandoval.

Overall, if Greinke continued to be the great pitcher he is, a great offense would not be as important to the Red Sox on his pitching days. While on the whole it is probably a slight disadvantage to have Greinke bat, it seems to be very small, and not worth shelling out a few more tens of millions of dollars. The biggest question mark in this is Greinke’s true batting talent. While he has hit well in his career, he has totaled less than 400 plate appearances over his entire career. Anything could happen in this small sample size, so it is hard to know. This probably will never happen, but it is interesting to think about. For now though the Red Sox have Price, and the Diamondbacks just shelled out $206 million for Greinke, so the Red Sox are just as well not even thinking about him hitting in Boston.

We might as well wait until 2020, when Bumgarner will hit the open market, until we think about this again.

The Astros were baseball’s biggest surprise of the 2015 season. Few will dispute that. This was, however, preceded by some of the worst seasons in Houston history. They posted three consecutive 100+ loss seasons from 2011-2013 followed by a somewhat bounceback 2014 campaign, posting a 70-92 record. Although they were not quite back to the winning tradition that ‘Stros fans enjoyed during the late 1990’s and early 2000’s, young potential began to show, headed by silver slugger Jose Altuve. The combination of young talent with free agent and trade market moves led to an unexpected 86-76 season and the first playoff birth since 2005 (where they eventually got swept by the White Sox in the Fall Classic). Part of this success was due to a new-found, solid bullpen and front five led by Cy Young winner Dallas Keuchel. However, the more exciting part of their success — at least for the average fan — was the explosive offense.

Houston’s 2015 opening day lineup included four new players to the organization: Luis Valbuena, Jed Lowrie, Colby Rasmus and Evan Gattis, all of which had 15+ home run seasons in the past. These lineup changes were complemented by a new hitting coach in Dave Hudgens, who preaches that being aggressive in the zone leads to a higher OBP, harder hit balls, and more runs scored. This proved to be a highly successful match, as the Astros posted impressive power numbers. They were second in the league in ISO, SLG, and home runs (all behind the Blue Jays), according to fangraphs.com. Their team wRC+ of 105 was 4th best in the league and was the best wRC+ since back in 2000 – the first year of Minute Maid Park. The most recent yearly changes have been the most impressive numbers, however.

From 2014 to 2015, they had the biggest increase in all three aforementioned categories of any team in baseball, adding 67 home runs, .046 ISO, and .054 SLG. They also increased their Z-swing% by 3.5% to 70.2%, the highest in the league and right in line with Hudgens’ approach. Surprisingly, they did this while decreasing their K% (albeit only by 0.9%). This leads to the question of how big of an impact Hudgens had on the organization and its multitude of young power hitters.

There were 11 Astros who had double-digit home runs, all who are younger than 30 years old. Five of those players broke the 20-home-run mark (Gattis – 27, Rasmus – 25, Valbuena – 25, Chris Carter – 24, Carlos Correa – 22). This is not including 29-year-old Carlos Gomez who was acquired in the latter half of the season, who only hit 12 home runs throughout his injury-plagued 2015 season. With so much raw power and youth in the organization, an active hitting coach is crucial to develop successful hitting approaches and general consistency at the plate. Hudgens seems to have been very successful in extracting the most out of his hitters in his first year.

Many of these hitters took strides to becoming more balanced at the plate. For example, slugger George Springer who posted a miserable 33.0% K% in his 2014 rookie campaign came down to a more reasonable 24.2% in 2015 while posting an above-average ISO of .183. The biggest surprise in this is that that is his lowest strikeout rate of any full year in his baseball career, including rookie and high-A ball. Another highly noticeable change is the power numbers of All-Star second baseman Jose Altuve. Known for being more of a contact hitter, the 5’6″ Venezuelan hit 15 home runs (the first double-digit home run season for Altuve) and improved his ISO from a below-average .112 in 2014 to a career high of .146. Teammates Luis Valbuena and Colby Rasmus also posted career highs in ISO at .214 and .236, respectively.

The good news for Astros fans is that this offense appears sustainable. The BABIP numbers of these Astros hitters slightly decreased for the most part. The glaring exception is George Springer, who had a BABIP of .342 compared to his rookie year’s .294 (but with his strikeout rate decreasing 8.8% and OBP increasing by .031, only time will tell if he can continue his impressive numbers at the plate once pitchers adjust and approach him differently). The Houston front office has built an offense around around younger hitters with a lot of raw power. This is not to mention their speed, as they ranked 3rd in stolen bases last year. So although the AL West has shown to be unpredictable in recent years, the way the Astros have built their team may very well provide some sustainability for them moving forward.

Side note – don’t expect the Astros to remain quiet in the off-season just because of their youth-heavy core. They have already begun shopping Jake Marisnick after retaining Colby Rasmus with a 15.8MM qualifying offer.

In my last article on these here internet pages, I attempted to create the best conceivably possible player by taking the most valuable seasons in baseball history and putting them all together into one awesome player. The results were fairly ridiculous. Can we get equally ridiculous results from the greatest age-seasons from pitchers? I’m going to make a couple of tweeks to my methodology from last time to tailor it more towards pitchers, who, at the extremes, seem to have more peculiar career arcs.

• No pre-1900 seasons

I included this rule for position players because I’m not too familiar with the era. I’m including it for pitchers because they weren’t doing anything like what modern day pitchers, or even pitchers in the 1920s were doing. I mean, in 1889, John Clarkson of the Boston Beaneaters pitched 620 innings with a 2.73 ERA. His FIP-WAR was 10.9 while his RA9-WAR was 19.7. That is 4.7 WAR better than Babe Ruth’s best season.

• No seasons with less than 50 IP

This doesn’t really apply all that much, unless you want me to include Joe Nuxhall’s two-thirds of an inning in 1944 when he was 15. He allowed 5 runs on 2 hits and 5 walks.

• No duplicates, take player’s best season

This wouldn’t be as much fun if it were just young Dwight Gooden and old Randy Johnson

As for which version of WAR I’m going to use, FIP-based WAR seems to be less prone to wild fluctuations, particularly with old-timey players. The gradual increase in strikeouts over the past century-plus seems to have balanced out the gradual decline in innings, so that the ridiculous seasons of today are similar in value to the ridiculous seasons of yesteryear. With all that said, let’s get to it and create a Ridiculous Moon Wizard Pitcher.

Read the rest of this entry »

Weighted On-Base Percentage (wOBA) is typically considered to be the best measure of offensive ability and effect on runs scored among other rate statistics such as batting average, slugging percentage, and on-base percentage. 89.8% of a team’s runs scored correlates to wOBA between 2005–2015. I decided to look at a team’s performance, measured by how many runs they scored in a season, against the amount of runs wOBA predicted* they would have scored.  (wOBA Expected Runs was calculated based on a linear regression model with runs modeled as wOBA. The adjusted r-squared value of R~wOBA is .898)

Generally, the results are what you would expect. Teams deviate from their wOBA Expected Runs, but the 50% of the teams (between the 25th and 75th percentile of the observations) range between -17.49 and 16.9 runs from their wOBA Expected Runs.

The outliers even fall within the uncorrelated portion of the relationship between runs scored and wOBA. As stated above, wOBA explains 89.8% of runs between 2005 and 2015. At the far right of the graph is the 2008 Minnesota Twins, who scored 829 runs against their 756 wOBA Expected Runs. The difference, 73 runs, is less than the 10% of runs that is theoretically not explained by wOBA. At the far left of the graph is the 2005 Arizona Diamondbacks who scored 696 runs against their expected amount of 756. Again, this 60-run differential falls within the 10% gap we would expect.

The mean difference of runs scored from the wOBA Expected Runs Scored is minuscule (.003 runs) and the standard deviation from that mean is 24.9 runs. This all strengthens wOBA’s position as the best offensive run predictor.

What does this all have to do with Don Mattingly and the Dodgers? The graphs below show each team’s runs scored below or above their wOBA Expected Runs Scored. You’ll see that teams fall within the standard deviation of runs scored less wOBA Expected Runs (-25.93–24.87), with some exceptions. The exceptions that fall outside of that range generally do not display a tendency for extreme over- or under-performance of their wOBA Expected Runs in consecutive seasons; however one team does stand out.

The 2013–2015 Dodgers consistently under-performed their wOBA Expected Runs, with the following differences in the respective seasons from 2013–2015: -51, -33, and -58 runs. To put this in context, only 8 of 330 of teams, or roughly 2%, that took the field between 2005–2015 under-performed their wOBA Expected Runs by more than two standard deviations (-49.8). The 2013 and 2015 Los Angeles Dodgers were two of those teams. No other franchise appears on the list twice, much less twice within three seasons.

In Mattingly’s first two seasons with the Dodgers (2011 and 2012) the results were standard, with a -6 and +12 runs to wOBA Expected Runs differential, but when the Dodgers came under new ownership and started spending to bring in new players things changed. The team got better but their performance in relation to what they were doing got worse.

A glance at the graphs above will show that teams have under-performed their expectations, but never this badly for a three-year stretch. There is luck and there are trends, and the Dodgers are a trend of under-performance. Does this mean Don Mattingly is a bad manager? Maybe. Does it mean that Mattingly was a bad fit for this Dodgers team as constructed? Probably.

It could all be on the hitters; it could all be bad luck, but those seem unlikely. The 2013–2015 Dodgers are the worst offensive under-achievers in the last decade. The results suggest that Mattingly was unable to shuffle a cast of talented and enigmatic hitters into the right order to produce the best sequencing of results. Alternatively, the other narrative is that Mattingly was handed a group of talented and enigmatic hitters that couldn’t execute situational hitting and hit inconsistently. Either way, the Dodgers cost themselves a lot of wins through one, or a combination of the two narratives. The team lost 5, 3, and 5 wins each year, compared to if they met their wOBA Expected Runs, as calculated using the Runs per Win for 2013–2015.

This doesn’t necessarily bode poorly for Mattingly in Miami. The Marlins don’t have the benefit of a deep and talented bench. They are a fairly straight-forward offensive team that should allow Mattingly to write-up consistent lineups so long as the team remains healthy. This is not to say the Marlins will out-perform the Dodgers. It is to say that the Marlins may perform closer to how we would expect them to perform.

However, if the problem did not lie with Mattingly, but instead the Dodgers’ roster, than things do bode poorly for the Dodgers. It will be interesting to see if Dave Roberts can unlock something Mattingly could not; or whether the players are to blame; or whether Los Angeles must wait for Gabe Kapler, baseball’s philosopher-king, to set the runs free.

Yes. Probably. If you’re in a hurry, you can now go do whatever you should be doing instead of reading about no-longer-prospecty baseball players. But if you’re not in a hurry, know this: there’s a chance he can survive, if only a small chance.

Kyle Drabek is rowing against a mighty tide that seeks to dash what’s left of his career against the jagged rocks. The former Phillies first-round pick (don’t fret, Ruben-haters — the really good guys in this draft were already gone) had a mediocre minor league career followed by a wretched major league one. Over 177 injury-plagued innings, Drabek has been a TTO arsonist: 6.1 K/9, 5.7 BB/9, and 1.2 HR/9. His career ERA/FIP is 5.27/5.42. When hitters die and go to heaven, they face him every night. And yet the Arizona Diamondbacks recently signed him to a minor league deal. What might they be thinking?

Drabek has been through Tommy John surgery twice, in 2007 and again in 2012. Here’s a list of repeat TJ offenders — you can sort on “Back to playing” to see who, well, made it back to playing. It’s largely a grim list, but there are some pitchers who came back to perform decently. As you can see from perusing the list, and this post, the vast majority of those are relievers.

Drabek’s major league performance so far suggests little more should be expected of him. In the expansion era there have been 73 starting pitchers who “achieved” a FIP of 5+ in at least 150 innings before age 28. Here they are — Drabek checks in at #27.  The name that jumps out most prominently on this list is Joe Nathan:

Through age 27         IP        ERA        FIP         K/9          BB/9          HR/9

Nathan                       187       4.61       5.72          5.6            5.2               1.4

Drabek                       177       5.27        5.42         6.1             5.7               1.2

Entering his age-28 season, Nathan was a failed starter with one shoulder arthroscope to his credit. That year the Giants converted him into reliever, and after season’s end converted him into A.J. Pierzynski. Nathan went on to rack up the eighth-most saves in MLB history, which is a pretty fair achievement even if you aren’t into saves.

How did he do it? Unfortunately, pitch-by-pitch data isn’t available back to the years (1999-2000) when Nathan did most of his damage as a starter. But a look at Nathan’s pitch values nevertheless suggests some clues. One big clue in particular: his slider was devastating. By fleeing to the bullpen, Nathan probably was able to add a little heat to the slider, and perhaps able to throw it more often. Hitters would only see him once as a reliever, but this may not have been a huge factor, since hitters were beating Nathan like a drum as soon as the cute guest-PA-announcer-kid finished shouting “play ball!” Get to him a third time, though, and it was like walking to the plate with a plutonium-corked bat.

One can imagine that being in the bullpen enabled Nathan to add some velo and subtract the amount of times he threw his weaker pitches. Salomon Torres presents a similar profile: a failed starter in the 1990s, Torres disappeared off the baseball earth for a few years before resurfacing with the Pirates as an effective reliever in 2002. Torres’ out pitches were the slider and splitter; he featured both as a reliever evolving toward the latter as he aged.

Justin Miller also made the transition from awful starter to solid reliever. Like the others, he did not wholly abandon a pitch when moving to the pen, but he placed greater emphasis on his — you guessed it — excellent slider, at the expense of his not-so-excellent fastball. Miller didn’t add much velocity in becoming a reliever; it seems to be the change in pitch selection that helped him turn the corner.

These career paths might be helpful signs for Drabek, but in at least two senses they aren’t: unlike the other guys mentioned above, Drabek lacks a carrying pitch. Nathan had an excellent slider, as did Miller and (at times) Torres, even when the rest of their pitches were failing them. Drabek’s pitches are all below average, so he appears to lack a safe base from which to make his bullpen transition (although to be fair, all of Drabek’s pitching stats suffer from the pain and embarrassment of small sample size). By the numbers, the curve is the least bad of his offerings; perhaps focusing on becoming a fastball-curve guy would benefit his development.

Focusing on the curve brings us to Drabek’s second problem: TJ survivors appear to struggle with breaking pitches. Throwing more curves at this stage of his career may be the last thing Drabek can (or is willing) to do. It’s not impossible: Jason Isringhausen leaned heavily on the curve as he remade himself into an elite closer. But there aren’t a lot of examples here.

Perhaps Drabek can develop his changeup, his second-least-bad pitch. It appears that, following his surgery, he tried to emphasize his cutter, a pitch that hasn’t been kind to him yet, but an approach that did help The Beard to become fearworthy. Perhaps a superior pitching coach could help Drabek, but here’s who the Snakes just hired.

Despite these difficulties, the Diamondbacks nevertheless have an incentive to pick through the Drabekian rubble to see if they can salvage any value. Even with their spiffy new TV deal the D’Backs will always be no better than second-tier in terms of resources and attendance, especially problematic with the Dodgers juggernaut in the same division. Finding cheap pitching hand-me-downs will enable the organization to invest elsewhere (as it is already doing with the lineup).

Given both Drabek’s limited major league success and his limited major league appearances, deciding how to reconstruct him may be even more difficult than such projects usually are. Drabek doesn’t have huge platoon splits, and while for now that means both southbats and northbats will feast on his pitches, over the longer haul it may mean that he could be useful as a swing man or multi-inning reliever.

The Diamondbacks have had success in re-imaging double-TJ survivor Daniel Hudson as a reliever, but he had already had much more success as a starter than any of the other pitchers mentioned in this post (except Tommy John himself). Indeed, the Snakes may move Hudson back to the rotation next year. But perhaps the work with Hudson has given the organization some clues for how to deal with a much more challenging project.

I’m rooting for Drabek, but I’m taking the under.

In the middle of June, I wrote an article looking at batted-ball data. Specifically, I grouped players into tiers based on their hard-hit percentage and looked at the statistics accumulated by the players in each group, then identified the outliers. This is a look back at that article to see if we can learn anything.

To start with, the following charts show a comparison of the correlation of other metrics to the different strengths of batted balls hit. I did this in the middle of June and will compare that chart to one I created using statistics for the entire season. In June, I used a cut-off of 150 plate appearances through June 14. This was right around the 60 game mark of the season. There were 236 players. At the end of the season, I used 350 plate appearances as the cut-off, which consisted of 249 players.

Noticeable here is the strengthening of the correlation for the power statistics with hard-hit percentage as more data came in. The three stats dealing the most with power—ISO, HR/FB, and slugging percentage—all saw an increase in their correlation with hard-hit percentage. This is true down the column until you get to batting average and BABIP, which showed a weaker correlation over a full season than over the first two and a half months. While ISO, HR/FB, and SLG all correlate with hard-hit percentage at .70 or above, batting average and BABIP are down around 0.10, and LD% is at .06.

In the June article, I separated the players into groups based on their hard-hit percentage. As you would expect, the players who hit the ball hard a higher percentage of the time were more productive hitters. Here is the breakdown again, first the chart through June 14, then the full-season chart.

Remember, these aren’t necessarily the same players within tiers in both tables. Some players could have moved from one tier to another as the season went on and more players qualified overall for the full season. The way to look at this is to go down the columns to see how the average statistics for each group change as hard-hit percentage goes down. It’s easy to see that the groups of players in the higher ranges of hard-hit percentage are more productive than the groups of players in lower ranges of hard-hit percentage. The players in the upper tier, with a hard-hit percentage of 35% and above, hit more fly balls, had more of those fly balls go over the fence, had a higher batting average, slugging percentage, and isolated slugging. Roughly 85% of these hitters had a wRC+ at 100 or better. The least productive tier was the group of players with a hard-hit percentage at 24% or below. A small number of these players were able to be league average or better hitters.

The numbers from June are similar to the numbers for the full-season. As hard-hit percentage goes up, offensive production goes up and the percentage of players who are above-average hitters (by wRC+) goes up. A similar trend emerges for ISO, fly-ball percentage, HR/FB%, and slugging percentage.

The interesting players to me are the ones in the minority among their group of hitters. Through June 14, there were seven players in the top tier who had a hard-hit percentage greater than 35%, but with a sub 100 wRC+. These players consistently hit the ball hard but were still below-average hitters. Considering how often they hit the ball hard, I expected these players to improve and more closely match the rest of the group from this point forward. Theoretically, these are the guys with upside based on their hard-hit percentage. At least, this was my hypothesis. How did these players do over the rest of the season?

The seven players who hit the ball hard a high percentage of the time but who had a wRC+ below 100 through June 14 are shown below. The following chart shows the performance of these seven hitters before and after June 14.

*note—to determine the wRC+ of the group, I just did a weighted average based on each player’s plate appearances. The other numbers are precise totals for the group.

These players did improve as a group, with their composite batting line going from .237/.292/.387 to .252/.305/.455. They improved even though their BABIP dropped from .289 to .286. The big increase was in their power. They hit more fly balls and had more fly balls go for home runs. Their ISO increased from .151 to .203 and their wRC+ went from 86 to 106.

Two of these players had fewer than 60 plate appearances after June 14, so they aren’t very helpful to us. Of the remaining five players, two stayed close to the level they had established by June 14 and the other three showed strong improvement. Here is a closer look at these players:

Jorge Soler was essentially the same hitter before and after June 14, right down to an identical 96 wRC+. His BABIP dropped from a sky-high .383 to a still very good .339, but he also struck out less often and his hard-hit percentage dropped from 39.5% to 32.3%. His hard-hit percentages in both portions of the season suggest he should have hit better than he did, but his low fly-ball percentage limited his power. Over the course of the whole season, Soler had a hard-hit percentage of 35.9%. That puts him in the top tier. The players in this tier of hitters had an average fly-ball percentage of 38%. Soler’s fly-ball percentage was 29.8%, which corresponds with the players on the lowest tier of hard-hit percentage, those players below 24%. Basically, Soler hit the ball hard as often as guys like Adrian Gonzalez, Bryan Braun, and Yoenis Cespedes, but hit the ball in the air as often as Gregor Blanco and Alcides Escobar. While he hits the ball hard with regularity, he doesn’t hit enough fly balls to take advantage of his hard-hit percentage.

Like Soler, Jay Bruce’s overall production did not improve. His wRC+ dropped slightly, from 96 to 90 even though he maintained a high hard-hit percentage. The shape of his production changed, though. He hit for much more power, with an ISO that was .040 higher after June 14 than before, but a corresponding drop in walk rate torpedoed his on-base percentage. The overall effect was going from hitting .212/.324/.394 through June 14 to .234/.277/.457 after June 14. Jay Bruce is a mystery. He had a top-tier hard-hit percentage and hit the ball in the air frequently enough, but his production didn’t compare to the other players with similar profiles.

Mark Trumbo was one of three players in this group who did improve a significant amount. Trumbo hit .242/.276/.445 through June 14 and .276/.333/.451 after. His wRC+ increased from 93 to 119 even though his hard-hit percentage dropped from 35.2% to 31.7%. The biggest change for Trumbo was an increase in BABIP from .280 to .337 and an increase in walk rate from 4.5% to 8.0%.

Both Will Middlebrooks and Matt Adams did not have enough plate appearances after June 14 to tell us much of anything.

Steve Pearce improved his wRC+ from 79 through June 14 to 106 from June 15 on even though his hard-hit percentage cratered from 35.6% to 25.4%. His BABIP was nearly the same. His walk rate and strikeout rate changed very little. He didn’t improve his on-base percentage by much. The big difference was an increase in slugging percentage from .365 to .471 with a corresponding increase in ISO from .153 to .248. He did this by greatly increasing the number of balls he hit in the air. His fly-ball rate through June 14 was 39%. After, it was 53%. That seems like a drastic change to me, so I wonder if Pearce made the decision to go all out for power by hitting fly balls as often as he could.

The final guy on this list was the greatest success story of this group, Matt Kemp. Kemp was terrible in the first part of the season. When I initially wrote about batted-ball data on June 14, Kemp was hitting .249/.289/.340 even though his hard-hit percentage of 35.8% was in the upper tier of hitters. From June 15 on, Kemp hit .270/.328/.519 with a hard-hit percentage of 45.5%. He hit fly balls at a higher rate (31% to 39%) and more of those fly balls left the yard (3.4% HR/FB% to 20.6% HR/FB%). Kemp’s ISO improved from .091 to .242 and his wRC+ went from 78 to 133.

This is a small group of players, so it is not an in-depth study. Also, two of this group of seven players didn’t have enough plate appearances to be meaningful. Of the remaining five players, three did significantly improve, while the other two continued their subpar ways.

The other group of hitters that interested me was the group of nine that had a wRC+ greater than 100 despite a hard-hit percentage below 24% through June 14. These players were somehow able to be above-average hitters despite carrying such a low hard-hit percentage.

The following chart shows these nine players (out of a group of 44) who had hard-hit percentages below 24% but with a greater than 100 wRC+. The top chart shows what they did through June 14 and the bottom chart shows what they did from June 15 on. My hypothesis was that these players would hit worse because their low hard-hit percentage would not let them sustain their above 100 wRC+.

As a group, these nine hitters went from hitting .313/.366/.404 through June 14 to .271/.315/.386 after June 14. They saw their combined wRC+ drop from 117 to 91. Only three of these nine hitters continued to have a wRC+ over 100 from June 15 on. The glaring change in BABIP from .353 to .303 for the group is likely a main culprit in their diminished production. They also walked less often and struck out more often.

Nori Aoki was the leader in wRC+ among this group of hitters on June 14^th. Had he been able to sustain that for a full season, it would have been a career year. Unfortunately, he suffered a broken leg when he was hit by a pitch from Carlos Frias about a week later and wasn’t the same hitter when he came back. He also dealt with concussion issues and didn’t play after September 3. He was much worse after June 14 but injuries were obviously a big factor.

Jacoby Ellsbury was already on the DL with a knee injury at the time I wrote the original article. He missed close to seven weeks in May, June, and July and really struggled upon his return. His hard-hit percentage was just slightly lower than it had been before but his BABIP plummeted from .379 to .261 and his walk rate dropped significantly also (11.2% to 4.8%). Like Aoki, injuries were probably a big factor in Ellsbury’s diminished production.

Jose Iglesias also dealt with an injury, like Aoki and Ellsbury, but his was in September and cause him to miss the last month of the season. He had already declined from a 125 wRC+ through June 14 to an 80 wRC+ from that point forward. His BABIP dropped from .367 to .302 despite an increase in hard-hit percentage from 13.7% to 17.9%. Even with that increase, a 17.9% hard hit percentage is ridiculously low. With a hard-hit percentage that low, I wouldn’t expect Iglesias to be anywhere close to a league-average hitter going forward.

Billy Burns had the lowest hard-hit percentage (13.6%) of any qualified hitter over the entire season and the highest soft-hit percentage (30.5%). He rode a .366 BABIP to a well above average 120 wRC+ through June 14. From that point forward, his wRC+ was 97, with a BABIP of .328. Over the whole season, Burns had a 102 wRC+ despite such a low hard-hit percentage. Like Iglesias, I wouldn’t expect Burns to be league average as a hitter next year either.

Salvador Perez and Jace Peterson both increased their hard-hit percentage but still saw a drop in their wRC+ by a significant amount. Perez had fewer fly balls leave the yard (15.2% HR/FB% to 10.6% HR/FB%) and his already mediocre .292 BABIP dropped to a less-than mediocre .257. Peterson had a 106 wRC+ and .339 BABIP on June 14, with a hard-hit percentage of 23.8%. From that point forward, his hard-hit percentage was an improved 27.6%, but his BABIP was .266 and he had a 63 wRC+.

Yunel Escobar and Ian Kinsler were the only two players among this group of nine who saw an increase in wRC+ after June 14. They also greatly increased their hard-hit percentage. Yunel’s hard-hit percentage went from 23.9% to 30.4%. Kinsler’s increased from 22.1% to 28.6%. Both of these hitters were below their career rate of hard-hit balls as of June 14 and hit closer to their career marks from that point forward, which was likely a factor in their improved production.

Dee Gordon joined Escobar and Kinsler in maintaining a wRC+ over 100, but he did see a drop from 118 to 109. His BABIP through June 14 was a ridiculous .418. From that point forward, it was a silly .357. His hard-hit percentage barely changed at all (17.7% to 17.5%). Gordon has had a very low hard-hit percentage every year of his career. His production is very dependent on a high BABIP. In the three seasons when he’s had a BABIP of .345 or higher, his wRC+ was 94, 101, and 113. In the two seasons when he had a BABIP below .300, his wRC+ was 58 and 73.

Overall, just two of these hitters had an improved wRC+ after June 14 and both of those hitters also increased their hard-hit percentage. A third hitter, Dee Gordon, had a worse wRC+ after June 14 but was still an above-average hitter (109 wRC+). The other six hitters in this group were significantly worse after June 14.

This is a look at individual outliers and there are factors beyond hard-hit percentage that come into play, but I do think hard-hit percentage can help us when analyzing a player’s production during the season.