The Indians have an awesome starting rotation. They’re fifth in the MLB (first in the superior-hitting American League) with a 3.95 SIERA, seventh in ERA with a 3.96. They obviously have a solid top three in Carlos Carrasco, Corey Kluber, and Danny Salazar. Beyond them, the emergence of Trevor Bauer has grabbed headlines. But what about that last spot in the rotation? It is being held down, and held down steadily, by one Josh Tomlin. And he isn’t dragging down the staff’s ERA like most number 4s and 5s. In fact, he’s actually improved the ERA of the staff with a solid 3.81 ERA. However, he’s only averaged 6.39 K’s per nine innings, far below the league average for starting pitchers this year (7.72). He certainly doesn’t have overwhelming stuff. How has he been able to succeed?

Tomlin has impeccable command. He’s walking 1.15 guys per nine innings, in line with his career (1.45). He’s third in the MLB in K/BB ratio (first in AL). He’s 13th in first-pitch-strike percentage. He dots the corner with his main secondary offerings, a curve and a cutter, throwing them down and away to righties and down and in to lefties. He’s done this throughout his career:

And he’s continued to do so this year:

He owns that low and outside corner! Spotting his pitches on the corners has likely helped Tomlin to induce a solid Z-Swing percentage of 62.7% (according to FanGraphs plate-discipline data), which is 10th-lowest in the MLB this year. This means that Tomlin has been good at getting called strikes. He pairs this skill nicely with a 33.6% O-Swing percentage, which is the 11th-highest in the MLB this year. This means that Tomlin has been good at getting hitters to swing at pitches outside of the zone (pitches they usually can’t drive). This has been a skill for Tomlin throughout his career (33.2% O-Swing during his career).

In addition, he has a career BABIP of .274 (league average is around .295 every year). He has improved on that mark this year, allowing a .268 BABIP. This isn’t entirely surprising, given the high O-Swing percentage: If you swing at pitches outside of the strike zone, it’s much harder to make solid contact. Also of note is the fact that Tomlin’s Z-Swing percentage has really improved for him this year (66.3% career versus 62.7% this year).

What’s the driving force behind the improvement in these two plate-discipline stats? Tomlin’s cutter and curve offer a good explanation. According to PITCHf/x data on FanGraphs, Tomlin’s cutter has the 15th-best “rise” among qualified pitchers this year. It also has the eighth-most horizontal movement, darting away from righties and in to lefties. What’s more, the cutter has induced a 42.7% O-Swing percentage across his entire career. That number has held strong this year at a 44.5% clip. He’s decided to uptick the usage on the pitch this year to a career high, while throwing his four-seamer at a career-low rate.

The curve is the driving force behind the low Z-Swing percentage: This year, the pitch has a crazy low percentage of 44.7%. While that is lower than his career percentage on the pitch,  the curve is generating excellent vertical drop this year (15th-best in the MLB), and I wouldn’t be surprised to see him maintain a low percentage.

Tomlin isn’t flashy. He doesn’t pile up strikeouts. He doesn’t throw very hard. But, he spots the ball tremendously well and appears to have good contact management skills. Two pieces to the puzzle are his low Z-Swing percentage (fueled by the curve) and high O-Swing percentage (fueled by the cutter and its uptick in usage).

Data courtesy of FanGraphs and Brooks Baseball. Thanks for reading!

You probably know that Zach Britton is good at baseball, and that he’s having a great year. He was good enough last year that an article was written titled “How Zach Britton Blew His Saves”, and he’s been even more effective this year. Britton set a record last Wednesday night for consecutive saves by a left-handed relief pitcher to start a season, and has a number of other impressive stats:

• he hasn’t allowed a hit since July 15 (a span of 8 appearances), a run since June 21 (18 appearances), or an earned run since April 30 (36 appearances)
• he has allowed hits in just 18 of 47 appearances, and allowed multiple baserunners (via hit or walk) in just 10 of appearances

The ESPN Cy Young Predictor (CYP) shows Britton to be leading the current AL Cy Young race. He could be the first reliever to earn first-place Cy Young votes since Craig Kimbrel and Fernando Rodney received (single) first place votes in 2012. But is it really plausible to think that he could win?

Relievers and Recent Cy Young Voting

Let’s compare Britton’s stats with the four other relievers to receive first-place Cy Young votes since Eric Gagne’s 2003 victory, the last reliever season to actually win the Cy Young:

A lot of dominant seasons. A few notes:

• Rivera’s 2005 season benefited from a transition time where many writers still prized W-L and voted for Bartolo Colon; Colon’s selection over Johan Santana looks silly in hindsight
• Rodney’s 2012 and Britton’s 2016 season look really similar, except that Britton has been perfect in save situations (more on this soon)

Why Gagne Won

Gagne’s narrative of dominance that year, including his famous entrance and nickname “game over”, was corroborated by a combination of save records (55 saves and 0 blown saves, in the midst of a still-standing record 84-save-conversion streak), minuscule WHIP (.692), and an eye-popping 137 Ks (15.0 per 9 innings). Britton has the perfect save conversion rate and low WHIP that Gagne had, but faces additional obstacles in winning and constructing the name narrative.

The first is that Britton’s K rate, while great, is much lower. The second is that reliever seasons have become discounted recently, a sort of narrative goalpost shift in the sabermetric era. The perfect save conversion was repeated by Jose Valverde and Brad Lidge in 2011 and 2008, respectively, and I think no longer carries the same impression on voters. Gagne won convincingly even though there was no shortage of excellent starters that year (Mark Prior and Mike Schmidt both had WAR figures much higher than Gagne’s), because he was the story in NL pitching that year. Relievers tend to do worse on metrics like WAR compared to starters, and this makes constructing the same justification for voters to cast high votes to relievers much harder today. WAR was in its infancy in 2003, and I think if the 2003 vote were recast today, the result would be quite different.

This leads us to some sabermetric numbers:

A lot can be said here, but a few things I wanted to mention:

• I think Gagne’s high WPA is based on his outstanding performance in high-leverage situations (a look at his splits shows that he gave up two extra-base hits against 63 strikeouts in 154 high-leverage plate appearances in 2003)
• bWAR loves Rivera; he had three other seasons of 4 or more WAR, including his workhorse 1996 season with 107.2 IP and 5 WAR
• Gagne and Kimbrel’s FIP are actually lower than their ERA, I think because of their K rates
• Rivera, Rodney, and Britton had their ERA (and ERA+) figures benefit from allowing multiple unearned runs

 Lastly, let’s look at stranding runners:

All five stranded baserunners at an excellent rate, especially Kimbrel’s astounding 92.8% LOB. They were also extremely effective at preventing inherited runners from scoring, with a combined 55 of 60 inherited runners stranded. This takes us to:

Britton’s Luck

Britton has enjoyed both good and bad luck this year, and I’ll just mention two factors: defense and bequeathed runners. The good luck is in having a good infield defense behind him, which is obviously important for a sinkerball pitcher. Davis, Schoop, Hardy, and Machado are enjoying FanGraphs Fielding ratings of 1.1, 0.4, 1.9, and 4.1, respectively, and for what it’s worth, the Orioles are second in the AL in fielding percentage as well.

The (slight) bad luck is in his two bequeathed runners, both of whom scored. The first was on April 30, where Britton left with a runner on 1st and 2 out and Vance Worley allowed the runner to score, tagging Britton with one of his three ER this year. The other was on June 21, where Britton left with a runner at 2nd and 2 out, and Ordrisamer Despaigne allowed the runner to score. Britton was charged with 3 unearned runs but 0 earned runs, as Flaherty was playing 3rd instead of Machado that day and made an error early in the inning; this is one of only two errors committed behind Britton this year.

The Search for Perfection

If Britton ends up something like 55/55 in save situations (or blows one save) with his current rate stats, I think he’ll get at least a few first-place votes. But I think it is nearly impossible to be a reliever with a typical closer load and actually win the award in the WAR era, and perhaps tools like the Cy Young Predictor might be adjusted to reflect this.

This discussion also raises the question in my mind of whether we will ever see a reliever put up a perfect season of at least 60 innings with 0 runs allowed. It is really hard to throw that many shutout innings. Hershiser and Drysdale had streaks of nearly 60 scoreless innings, but all of the pitchers on the top 10 list of scoreless streaks were primarily starters. Reliever Brad Ziegler began his career with 29 scoreless appearances, but that’s only halfway to 60. Maybe it is like the chance of another .400 hitter.

We will see how Britton’s season turns out, and how the voters evaluate it. In the meantime, we will probably be seeing a lot more of this:

In “Hardball Retrospective: Evaluating Scouting and Development Outcomes for the Modern-Era Franchises”, I placed every ballplayer in the modern era (from 1901-present) on their original team. I calculated revised standings for every season based entirely on the performance of each team’s “original” players. I discuss every team’s “original” players and seasons at length along with organizational performance with respect to the Amateur Draft (or First-Year Player Draft), amateur free agent signings and other methods of player acquisition.  Season standings, WAR and Win Shares totals for the “original” teams are compared against the “actual” team results to assess each franchise’s scouting, development and general management skills.

Expanding on my research for the book, the following series of articles will reveal the teams with the biggest single-season difference in the WAR and Win Shares for the “Original” vs. “Actual” rosters for every Major League organization. “Hardball Retrospective” is available in digital format on Amazon, Barnes and Noble, GooglePlay, iTunes and KoboBooks. The paperback edition is available on Amazon, Barnes and Noble and CreateSpace. Supplemental Statistics, Charts and Graphs along with a discussion forum are offered at TuataraSoftware.com.

Don Daglow (Intellivision World Series Major League Baseball, Earl Weaver Baseball, Tony LaRussa Baseball) contributed the foreword for Hardball Retrospective. The foreword and preview of my book are accessible here.

Terminology

OWAR – Wins Above Replacement for players on “original” teams

OWS – Win Shares for players on “original” teams

OPW% – Pythagorean Won-Loss record for the “original” teams

AWAR – Wins Above Replacement for players on “actual” teams

AWS – Win Shares for players on “actual” teams

APW% – Pythagorean Won-Loss record for the “actual” teams

Assessment

The 1997 Boston Red Sox 

OWAR: 63.7     OWS: 317     OPW%: .583     (94-68)

AWAR: 41.4      AWS: 234     APW%: .481     (78-84)

WARdiff: 22.3                        WSdiff: 83  

The “Original” 1997 Red Sox cruised to the pennant by a ten-game margin over the Yankees. Jeff Bagwell delivered a 30/30 season (43 HR / 31 SB), drove in a career-high 135 baserunners, rapped 40 doubles and coaxed 127 walks. Brady Anderson followed his 50-home run campaign in ’96 with 39 two-base knocks and 18 dingers. A trio of “Original” and “Actual” Sox infielders provided additional firepower in Boston’s stacked lineup. Nomar Garciaparra (.306/30/98) merited the 1997 AL Rookie of the Year Award as he registered 209 base hits, 122 runs scored, 44 doubles, 11 triples and 22 stolen bases. Mo “Hit Dog” Vaughn slammed 35 circuit clouts and supplied a .315 BA. John Valentin (.306/18/77) led the League with 47 two-baggers.

1B Jeff Bagwell and 3B Wade Boggs placed fourth at their respective positions in the “The New Bill James Historical Baseball Abstract” top 100 player rankings. “Original” Red Sox teammates specified in the “NBJHBA” top 100 rankings include Roger Clemens (11th-P), Mo Vaughn (51st-1B), Brady Anderson (63rd-CF) and Ellis Burks (77th-CF).

  Original 1997 Red Sox                                                             Actual 1997 Red Sox

Roger Clemens (21-7, 2.05) collected the 1997 AL Cy Young Award while posting a personal-best with 292 whiffs. Curt Schilling (17-11, 2.97) overpowered the opposition with a career-high 319 strikeouts. Paul Quantrill furnished a 1.94 ERA in 77 relief appearances. Tom “Flash” Gordon notched 11 saves for the “Actuals”.

  Original 1997 Red Sox                            Actual 1997 Red Sox

Notable Transactions

Roger Clemens

November 5, 1996: Granted Free Agency.

December 13, 1996: Signed as a Free Agent with the Toronto Blue Jays.

Jeff Bagwell

August 30, 1990: Traded by the Boston Red Sox to the Houston Astros for Larry Andersen.

Brady Anderson 

July 29, 1988: Traded by the Boston Red Sox with Curt Schilling to the Baltimore Orioles for Mike Boddicker. 

Curt Schilling 

July 29, 1988: Traded by Boston Red Sox with Brady Anderson to the Baltimore Orioles in exchange for Mike Boddicker.

January 10, 1991: Traded by Baltimore Orioles with Pete Harnisch and Steve Finley to the Houston Astros in exchange for Glenn Davis.

April 2, 1992: Traded by Houston Astros to Philadelphia Phillies in exchange for Jason Grimsley.

December 20, 1995: Granted free agency.

December 21, 1995: Signed by Philadelphia Phillies.

Honorable Mention

The 1927 Boston Red Sox 

OWAR: 32.6     OWS: 230     OPW%: .463     (71-83)

AWAR: 13.7       AWS: 153      APW%: .331    (51-103)

WARdiff: 18.9                        WSdiff: 77

The “Original” 1927 Red Sox tied for last place with the Indians yet managed to finish 20 games better than the “Actual” squad. Babe Ruth (.356/60/165) established the single-season home run record and paced the Junior Circuit with 158 runs scored, 137 walks, a .486 OBP and a .772 SLG. Tris Speaker sported a .327 BA and laced 43 two-base hits in his penultimate season.

On Deck

What Might Have Been – The “Original” 1904 Superbas

References and Resources

Baseball America – Executive Database

Baseball-Reference

James, Bill. The New Bill James Historical Baseball Abstract. New York, NY.: The Free Press, 2001. Print.

James, Bill, with Jim Henzler. Win Shares. Morton Grove, Ill.: STATS, 2002. Print.

Retrosheet – Transactions Database

The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at “www.retrosheet.org”.

Seamheads – Baseball Gauge

Sean Lahman Baseball Archive

RotoGraphs, in addition to several Community writers, have been posting about an “x” category of metrics for quite some time. They include things like Andrew Dominijanni’s xISO, Andrew Perpetua’s xBABIP, and more. The clear purpose of developing those statistical indicators was to measure and predict fantasy-baseball success, something we all aspire to in our hopefully low-priced leagues (although you probably found that using x-stats is a lot like overstudying for a test because the amount of effort you put into preparing yields diminishing returns, and you “over-Xed” the players).

One of the most prominent of the x-stats trotted out at the beginning of every season is xHR/FB, developed by Mike Podhorzer, and always accompanied by an amusing “leaders and laggards” piece. His version of xHR/FB is quite good, with a .649 R-squared value. In his regression analysis, Mr. Podhorzer utilizes somewhat exclusive metrics (hopefully public at some point), such as average absolute angle. Overall, it’s a pretty good predictor, and it becomes doubly understandable to the layman when it gets multiplied by fly balls to produce an expected home-run value.

The only real issue I have with HR/FB (and its prediction) is that it is HR/FB. While it is more stable for hitters than for pitchers, it still isn’t quite as stable as a stat I’d like to use for fantasy baseball. For my 1000 player-season sample from 2009-2015, HR/FB had a year-to-year R-squared value of .49. It isn’t terribly difficult to figure out why. There are numerous reasons, including weather changes, team changes, opponent changes, player development, and more. Moreover, it doesn’t take a very good picture of a hitter’s overall profile because it only looks at how many home runs a player hits per fly ball. A player might have a high HR/FB, but he may not hit enough fly balls for the metric to accurately describe his power (i.e. whether he actually hit a lot of home runs). On the other hand, it’s important to note that a high HR/FB generally goes with a higher FB%.

Perhaps a better metric for evaluating a player in the greater context of his hitting profile is HR/BBE. Home runs per batted-ball event is just HR/(AB+SF+SH-SO). It has a slightly higher year-to-year R-squared of .56 (from my sample), in large part because it takes into account more variables than does HR/FB. Under the umbrella of BBE fall not only fly balls, but line drives (and there can be line-drive home runs), and ground balls. In case you’re wondering why I included sacrifice hits, it’s because they tell a little bit about what kind of hitter a player is. Most modern managers are far more likely to ask a Ben Revere to lay down a sacrifice bunt than they are a Kris Bryant.

And so I thought it might be useful to run a linear regression analysis to develop an xHR/BBE (and from there, xHR). I’m a statistical autodidact, so I tried to keep things simple. Additionally, I thought it would be best if I utilized accessible variables like FB% so that a moderately literate sabermetrician could use it. After testing myriad variables, I came up with four that I’d use — average FBLDEV (Statcast), wFB/C, SLAVG, and FB%.

• AVG FBLDEV – Average fly ball/line-drive exit velocity. The idea is that the higher this value is, the harder the player is hitting the ball, and so he will hit more home runs.
• wFB/C – A rather obscure metric buried in the FanGraphs glossary, wFB/C is weighted fastball run values per 100 pitches. I use it because most home runs come off some form of a fastball, and home-run-hitter types are typically good fastball hitters.
• SLAVG – “Slap” average, a metric of my own invention (although someone else has probably thought of it – I just haven’t seen it before), is singles divided by at-bats. It’s a bit like ISO in that it tells you about a player’s power distribution (or lack thereof). I figure that this is inversely correlated with power because the more singles a player hits, the fewer home runs he’s likely to hit.
• FB% – Fly ball percentage obviously figures pretty heavily into a power hitter’s profile. It’s awfully difficult to hit a lot of home runs without hitting a plethora of fly balls.

It seems like a decent list of predictors in that they are understandable and accessible to the average fan, in addition to having a good relation to home-run hitters. I used all players that had at least 100 batted-ball events in 2015 and 2016 (Statcast only has data going back to 2015), which turns out to be close to 500 player-seasons. So let’s throw them into the Microsoft Excel Regression grinder and see what it spits out:

Note: To be clear, the end goal is not necessarily xHR/BBE, but rather xHR. xHR/BBE is just the best path to xHR because HR/BBE is a rate stat, meaning that it will have a better year-to-year correlation than home runs because that’s a counting stat. So if a player gets injured and only plays half a season, his HR/BBE would probably be similar to his career values, but his home-run numbers would not be.

The primary thing to recognize here is the R-squared value: a pretty good .78272. To the uninitiated, this simply means that the model explains 78% of the HR variance. If you’re interested (and you really ought to be), here are the coefficients for the variables and the overall formula:

xHR= (.114557524*FB% – .183885205*SLAVG + .006658976*wFB/C + .004075449*FBLDEV -.343193723) * BBE

With this information, it isn’t terribly difficult to look up a few pieces of data on FanGraphs and Statcast to see how many home runs a player “should” have hit. In case you’re wondering about its predictive value relative to that of HR/BBE, xHR/BBE has an R-square value that’s six points higher (.61). Nevertheless, it’s important to note that, based on the graph, the model struggles to predict home-run numbers for the players on the extremes – the Jose Bautistas of the world. Because the linear regression tends to underestimate rather than overestimate at the top, it’s likely that a quadratic regression would fit better. It’s something to look into, but this’ll do for now. Moreover, while there are some really crazy outliers, like Jose Bautista being predicted to hit 12 fewer home runs (Steamer does have him on pace for only 26 this year!), the model does work reasonably well for more average players.

Keep in mind that numerous improvements will be made. If anyone wants access to data or has a question, then just let me know. If not, then enjoy the tool and use it for fantasy, even though it’s getting a bit late for that. Maybe next year.

Over the weekend, the Atlanta Braves swapped their bad infielder embroiled in a domestic violence incident, Hector Olivera, for nice-guy outfielder Matt Kemp. The deal was largely panned within the industry, and many felt the Padres benefited most by ridding themselves of Kemp while he still had value. Olivera’s involvement in the deal was a purely financial exchange, as he was immediately designated for assignment, and he may never play in the majors again amid the stink of mediocrity and domestic violence. But the complex financials of the deal effectively mean that to land Kemp, the Braves’ bank account will be light just $30M or so over the next three years. Forgetting for a moment the enormous misstep the Braves made in acquiring Olivera in the first place, this Kemp acquisition is unbelievably impressive considering the price other teams are paying for defensively-challenged power-hitting outfielders.

Take Jay Bruce. One of the hottest names on the hot stove this July, he got moved on Monday for Dilson Herrera and Max Wotell. The interesting thing here is that Bruce is due $13M and signed only through next season, and the Mets had to give up real talent to acquire him. Herrera, the headliner going back to the Reds for Bruce, is a 22-year-old second baseman with a .790 OPS in AAA. But the kicker here is that Bruce isn’t good. He’s been worth six wins below average over the last three years.

Consider:

• Matt Kemp 2015/16: .263/.301/.460, 46 HR and an OPS+ of 109
• Jay Bruce 2015/16: .240/.301/.481, 51 HR and an OPS+ of 108

Undoubtedly, Bruce has been the better player this year. His OPS+ is 20 points higher than Kemp’s, meaning he’s been about 20% better than Kemp. But let’s consider what that means for a moment. Purely in terms of slugging, it’s about 25 total bases over the course of 400 at bats. That’s an extra base every four games, or twice a week. I realize that baseball is made up of all those little differences — and that those differences are what separate the contenders and the pretenders — but we’re talking about a whole lot of luck when we’re talking about two extra bases a week.

So why does “the industry” value one of these guys so much more highly than the other? Perception. The Reds have spent the greater part of the last year building up Jay Bruce as a potential difference-maker for a playoff team desperate for power. They’ve subtly leaked rumors of his availability to the press. They’ve reminded everyone that he’s clocked 233 homers in his career, and they had to smile as Yoenis Cespedes proved last year that flawed players can bring teams over the hump.

But is Kemp really all that different from Bruce? Was Kemp available for 3/$30M to everyone? Do you realize what 3/$30M means in today’s baseball? Last offseason, Joakim Soria signed for 3/$25M while Gerardo Parra got 3/$27.5M. That type of money goes to 7th-inning relievers and 4th outfielders. Kemp doesn’t even have to be good to be worth that type of money; merely average.

But Sean, the Defense!

Eh. They’re both pretty bad at defense. Whether one guy is worth -20 runs while the other is worth -15 really doesn’t matter to me. Maybe it should, but it really doesn’t. That type of difference is similar to the white noise to which one can ascribe that one extra base per week.

So really, it comes down to a simple proposition. It’s not as glamorous as trying to pick between Nolan Arenado, Manny Machado, or any other young superstar.  You’ve got two guys. Both are power hitters and play bad defense. One might be better than the other this season, but he was way worse last year. That one costs a solid prospect, and is signed for one year at $13M. The other costs zero prospects, and is effectively signed through 2019 at ~$10M per.

Who do you take?

In this post, I take a look at the 2016 Chicago Cubs though their first 100 games. I’ll start out by focusing on the Cubs’ run differential (Runs Scored – Runs Allowed). After a historic start, they reached their pinnacle after the 67th game of the year against the Pirates. At this point, the Cubs were 47-20 and had outscored opponents by 171 runs! Since then, the ball club is 13-20 and their current run differential is at +153.

Still, the Cubs’ +153 mark is 42 runs better than the next-closest team (Washington Nationals). The Cubs and Nationals are the only clubs to have a run differential that is greater than +100. The second-place Cardinals rank third in the league at +95 right now. While the Cubs dominate the top end of the spectrum, the Reds and Braves are running away with the worst run differentials in the league. The Reds have a -143 mark, largely due to the thrashings they have taken at the hands of the Cubs so far in 2016. The Braves have the second-to-worst differential at -134 runs.

Projected Runs to Wins

In another place, I introduced the “Pythagorean Theorem’s of Baseball” which basically tries to determine the number of games a team will win based on their number of runs scored and number of runs allowed. Here are the formulas for six of the most common win-percentage projection formulas:

I added up the Cubs’ total runs scored and total runs allowed after each game this year and compared their actual number of wins to the projected number of wins based on each formula. These charts visualize the differences between those numbers.

This matrix summarizes how accurate each of the projection formulas has been in predicting the Cubs’ winning percentage and total number of wins so far in 2016. The most accurate formulas was the James_1.83 followed by the James_2 and Soolman. Four of the six formulas were very good predictors, but the Cook and Kross formulas overforecasted the number of wins that they expected the Cubs to have. Notice that at one point this year, each of those formulas projected the Cubs to have over 15 more wins than they actually had. The R^2 value (coefficient of determination) is indicative of how well the projected win percentage matched up to the actual win percentage after each game this season.

All in all, the Cubs have should have at least six more wins this year based on these formulas. Scoring as many runs as they have (4th most in the MLB) and allowing as few runs as they have (T-1st in the MLB) should result in an even better record than 60-40. We knew it was unlikely that they would keep up their record-setting start in the run-differential category, but it will be interesting to see how these numbers match up as the season progresses.

Well, here we are: Over 100 games into the season and Bryce Harper has yet to break out of his slump. When Bryce came to the Majors back in 2012 he was one of the most hyped prospects since Alex Rodriguez broke into the bigs as a 19-year-old shortstop. The pressure, I’m sure, was immense, and through his first three seasons Harper had put up good numbers, but had yet to establish himself as the superstar we all thought he’d be. Something clicked in 2015 though, as he posted an amazing 9.5 WAR, 197 wRC+, and 0.461 wOBA, all best in the MLB by a fair margin. We all thought he’d done it, he had exceeded expectations and was ready to join Mike Trout as one of the most exciting, talented, and productive players in the game. His 1.5 WAR, 180 wRC+, and 0.443 wOBA through April of 2016 merely affirmed this sentiment.

Here we are. 2.8 WAR, 115 wRC+, and 0.346 wOBA. To be fair, these are by no means terrible numbers. He is still creating runs at a decently better rate than the average MLB player, with much of the credit going towards his MLB-leading 18.2 BB% and his 0.214 ISO. His defense has also been very good this year, helping to raise his WAR to 41st in the MLB. No, I am not saying Harper is a bad player, I’m just saying he is worse than the Bryce Harper we saw in 2015. We were all ready to call him a superstar (heck, we even voted him into a starting spot at this year’s All-Star Game), but now he’s taken this step back and we have no choice now but to start questioning his superstar status. Let’s take a look both at what might be causing this slump, and what Bryce could do to bust out of it (if anything at all).

The stat that jumps out at me most is his BABIP. The MLB average is exactly 0.300 this year, and Bryce has a career mark of 0.317. Bryce isn’t too far into his career, and while it’s possible that his 0.369 BABIP last season was an anomaly, it’s certainly safe to say that Bryce is definitively above average in this area. This season his BABIP has dipped down to 0.234, good enough for second to last in the MLB, ahead of only Todd Frazier (0.203). BABIP has a great degree of luck involved, in that some hitters with higher BABIPs might just get lucky (e.g. hit a little bloop into shallow right field that drops for a hit), or might be playing poor defenses (e.g. Jason Heyward would have caught that little bloop, but Jose Bautista was in right field and missed it by a foot). I believe, though, that going from 0.369 in 2015 to 0.234 in 2016 is enough of a differential to at least form the hypothesis that Bryce is struggling beyond just facing better defenses and getting less breaks.

One of the keys to figuring out this drop in production is figuring out what has changed from last year. Obviously his BABIP has declined, but why? For the  most part, pitchers are throwing him the same types of pitches at the same rates, and are throwing pitches in/out of the zone at the same rates as well. He has almost the exact same swing% on pitches outside the zone, but there’s about a 5% decrease in his swing% on pitches in the zone; nothing monumental, but something we ought take note of. The greatest changes that may be observed are in his batted ball numbers, shown here:

We can almost construct a narrative from these numbers: He’s hitting balls soft significantly more often, and he’s also hitting less line drives. Soft ground balls and fly balls are easier to convert into outs, and his infield fly ball% increase implies that he is hitting fly balls with less power. This explains why his home run rate is down. Where he was previously hitting hard line drives and grounders, and turning fly balls into home runs, he is now hitting softer, more easily-fielded grounders and popups, resulting in a steep decline in BABIP.

But this isn’t a cause, it’s a symptom. Again, we are forced to ask why it is that Bryce isn’t hitting balls as hard, and why he’s hitting less line drives? Bryce has been known for having great plate discipline, something that generally hasn’t changed over the last two years. At the surface, we see that he still has a very high walk rate, lays off pitches outside of the zone, and is one of the more patient hitters in baseball. However, one stat that caught my eye was his contact% on pitches outside the zone (and even inside the zone). His O-contact% went from 60.9% to 67.4%, and even his Z-contact% increased from 84.4% to 87.7%. This can be visualized here:

For the 2015 season

And for the 2016 season

There are two ways to look at this: The types of pitches Bryce is seeing, and the counts he’s getting himself into. All of this revolves around where pitchers are throwing pitches, where he’s swinging, and where he’s making contact. As you can clearly see, Bryce has been making a tangibly higher amount of contact this season. Logically, it makes sense to say that he is taking more pitches in the zone, and making weak contact where he used to just swing and miss. But that can’t be the whole story, can it? In attempting to find differences between this season and last, I merely found that regardless of what the count was, Harper was always making more contact; it didn’t matter if he was ahead, behind, or even. He was also making more contact regardless of what pitches were being thrown.

Let’s start with the types of pitches Bryce sees. We’ll split it up into fastballs (which includes 4-seamers, 2-seamers, and cutters), and secondary pitches (curveballs, sliders, and changeups). With secondary pitches, pitchers have begun to come into the zone a bit more than they used to. These charts show where pitchers are throwing Bryce non-fastballs:

2015

2016

It is by no means a huge difference, but it’s still there. Obviously, pitchers are still mostly throwing him non-heaters down and away, they’re just getting them in the zone more frequently. How does Bryce respond to this change? Well, he’s been laying off the low pitch a bit more, and instead has attempted to hit the inside pitch. These are his swing percentages on secondary pitches:

2015

2016

This also means that those non-fastballs are being called as strikes more frequently (assuming that umpires are generally going to call pitches in the zone as strikes). As we can see in his contact% charts, this season Bryce has been making contact at an extremely high rate on those high and inside pitches, and softer pitches have been absolutely no exception. In fact, he’s been making contact with the high and inside non-heaters more than he is with high and inside fastballs. What are the implications of this? Let’s look at his slugging% against secondary pitches:

2015

2016

Slugging% is by no means a perfect measure of a hitter’s ability. Yet, in this case, it gives us a decent idea of which locations a hitter is making solid contact. In his 2015 campaign he was able to get his arms extended and drive curveballs with great power. This season he is attempting to pull the ball more, and it’s resulting in weaker contact. While he is able to drive the inside breaking ball at a pretty decent rate, I suspect that he’s opening up his stance, which can occasionally result in a hard-hit ball, but will often result in a weak fly ball to the opposite field, or a weak grounder to the pull side. The fact that he’s swinging so much more frequently at inside pitches would also be reason to guess that as he’s swinging at breaking balls out over the plate he is still attempting to pull them, as opposed to going with the pitch. Further evidence of this comes from looking at how he hits breaking balls from lefties (curving away from him), versus how he hits them from righties (curving towards him).

2015

He even seems to do better against lefties. Against both of them, however, he clearly is able to see the pitch that will eventually break across the middle/outer half of the plate, and drive it with power. Let’s head over to 2016:

While his production has decreased against both righties and lefties, it is clear that the disparity is much larger when it comes to lefties. This is because Bryce is able to get away with trying to pull the ball against righties, as the ball is curving towards him. This makes pulling the ball a much more natural motion. Against lefties, the only breaking balls he is hitting are the ones that start inside and break right to the inside part of the plate, and the pitches that break to be right down the middle. It is the non-fastballs that are low and on the outer part of the plate that he is unable to drive, especially the ones being thrown by lefties. He’s opening up more, which also explains why his pull% hasn’t gone up (in fact it’s gone down). When he’s open, it’s hard to drive the outside pitch even if you make contact with it intending to hit it to the opposite field. Instead, he’s making that weak contact that results in outs.

Looking solely at secondary pitches, the narrative becomes: Bryce is taking the pitches that are out over the plate, and is instead swinging at pitches that are high and inside. He has a tendency to attempt to open up to the ball, and while he can sometimes get away with it against righties, lefties have been able to essentially shut him down. He is also making much more contact with all of these pitches, meaning that he’s putting more balls in play, yes, but they are weak balls that are easy to field, and are thus resulting in outs. With this mindset, even trying to hit the ball to the opposite field becomes more difficult, and all of this culminates in a lower BABIP.

Next, let’s look at how he’s handling fastballs. One thing that quickly becomes evident is the fact that Harper has been swinging at fastballs a lot less this year, especially ones up in the zone.

2015

2016

His swing% on fastballs in other areas of the zone is roughly the same; it’s really just those high and down-the-middle fastballs that he’s suddenly laying off of more. And yet, just as with non-fastballs, Harper still has been managing to make more contact this year, especially on pitches high and inside, as well as pitches low and out of the zone. How has that translated in terms of his slugging%?

2015

2016

What immediately jumps out at you is the large hole in the top part of the zone this year where Bryce is generating virtually no production. His production on low fastballs is closer to on par with last season, but up in the zone (the same area where he isn’t swinging nearly as often) he can’t get anything going. Why is this? With fastballs it’s a little more simple than with breaking balls in some aspects: For whatever reason he’s laying off fastballs in the zone, and he’s making weak contact with fastballs both high and inside, and down and away (which is where pitchers throw him fastballs most frequently). He’s giving pitchers more opportunities to throw fastballs out of the zone too. The big question mark comes at why he can’t do anything with those high fastballs specifically?

The answer isn’t too straightforward, but I do think that a large part of it is what types of pitches Bryce swings at in which counts. See, there is a very large differential in Bryce’s swing% in counts with no strikes between last year and this year, whereas in two-strike counts his swing% is about the same. He is taking more pitches when he has no strikes against him, especially the high fastball:

2015

2016

He seems to be swinging at less pitches overall, and his focus has shifted from the top of the zone to the inside part of the zone. It should be noted, too, that he is swinging significantly less at breaking pitches with no strikes as well, which highlights something that’s a little less tangible. With fastballs the narrative becomes this: Bryce is taking more fastballs early in the count, which means he isn’t capitalizing on those fastballs. Once he has two strikes on him, it would reason to guess that he would have more trouble making square contact, right? Well, not quite…

Against fastballs in two-strike counts Bryce is actually hitting decently, but he’s still missing the ones across the middle of the plate. One thing I noticed is that, in two-strike counts, he’s getting thrown more breaking pitches than before, and less fastballs. In 2015, 258 out of 719 two-strike pitches were breaking balls (36%). In 2016, the mark has been 189 out of 448 (42%). With two-strike pitches in 2015, 383 out of 719 were fastballs (53%), whereas 2016 has only seen 220 out of 448 (49%). Bryce has become more aware of the outside pitches, both fastballs and breaking balls, and this has something to do with it.

With two strikes, Bryce is swinging at around the same rate in 2016 as he was in 2015. The pitches he is hitting successfully are: High and inside fastballs, away fastballs, away breaking pitches from righties, all breaking pitches in the middle of the plate, and high and inside breaking pitches from lefties. Ok, that’s pretty tedious. Let’s show all of that visually, looking just at 2016:

First, fastballs with two strikes

Again, he’s gearing up for away pitches, and he’s swinging at almost anything, so he has success against away fastballs. We know that he’s been very keen on high and inside pitches of all kinds and in all counts this year, and that is also the easiest pitch to see. He has a reactionary eye for that pitch, and is able to catch up and drive it. High fastballs out over the plate can be somewhat easy to react to but he a) isn’t as keen on hitting them, b) isn’t seeing them that often in two-strike counts anyways, and c) isn’t expecting them. Thus, he’s most likely popping them up, which explains his high increased infield fly ball%. This is supported by the fact that his ground-ball rates on high fastballs with two strikes is quite low:

Next, let’s look at slugging% against breaking pitches from righties with two strikes

Again, it appears that because the ball is curving towards him it’s going to be easier to drive. He is then able to pull the breaking pitches that are up and out over the plate, and is able to drive the low and outside pitches with authority. His lack of success on up and away pitches is a little perplexing, but could be attributed to anything from bad luck, to him possibly not seeing that exact pitch as well, to the fact that the sample size here is pretty small and he hasn’t seen a ton of pitches in that area.

Finally, let’s check out breaking pitches from lefties

Nothing monumental in this aspect, especially as it’s not too different from how he hits breaking pitches against lefties in all counts. Regardless, it still fits our narrative as the up and inside pitches are right in his wheelhouse, and the pitches that breaking out over the plate are easier to hit than any other breaking pitch coming from a lefty.

Whew. That is a lot of heat maps to take in. Let’s review a bit: Bryce has a tendency to take more pitches early in the count, something he hasn’t done before. He’s also opening up, which makes him susceptible to breaking pitches and causing him to make weaker contact. The fact that he’s making more contact on pitches outside of the zone doesn’t help much either. He’s taking more fastballs as well, and once he has two strikes on him he’s seeing less of them, and is most likely expecting them less. He then begins to swing much more frequently, which actually reaps pretty good rewards, though there are some holes in his swing against certain pitches. He can’t get the high fastball, and struggles with breaking pitches against lefties. The result of all of this? Lower BABIP, lower wRC+, lower wOBA, you name it.

Obviously there are factors involved with this that go far beyond what heat maps and stats can show us. Baseball is an incredibly mental game, and once you realize you’re in a slump it can sometimes just drive you deeper into that slump. Statistics also can almost never tell the whole story, and as I mentioned earlier the sample size here is small enough that none of this is much of a predictor for future behavior. There’s a good chance that, on many of the situations mentioned above, Bryce has just gotten unlucky (or heck, maybe even lucky) and thus the heat map doesn’t reveal much. Overall though, when looking at everything in a holistic manner it allows us to construct an idea as to why Bryce is failing where he previously succeeded. We can never know everything for sure, but we know more than we did.

I’ve been hearing for months now that Bryce will be just fine, slumps happen to everyone, he will soon return to form, etc., and I’m not here to disagree with that. Although, I will ask (and I ought add that I am a big supporter of Bryce’s): What if he doesn’t break out of it? Odds are his 2015 will be one of the best seasons of his career, and 2016 (if it continues like this) will be one of his worst, and he will find himself somewhere in between for the rest of his career. It’s just that the deeper he drives himself into this rut the more compelled I am to find the source of problem as best I can, from a purely analytical standpoint.

Love him or hate him, the more that Bryce (and the many young superstars like him) thrives, the more baseball thrives.

(Note: All statistics and heat maps taken from Bryce’s page on FanGraphs.com)

What ails you now, brain?

Well, I still feel icky watching the Cubs after their trade for Aroldis Chapman.

Even after watching the last few games? Chapman’s been basically as good as advertised.

Actually even more so. Looking at pictures of the team celebrating with Chapman bother me and I wonder about whether the Cubs have mortgaged their souls. There’s one of my favorite young players Addison Russell, high-fiving unrepentant “I’m only sorry because of the gun” wife-choker Aroldis Chapman.

Look, you have to look at this from a baseball perspective. This is a borderline defensible deal. On the one hand, the Cubs gave up a LOT for Chapman, but they also had less relative value of those pieces. The Cubs want to win now, and the Yankees can afford to stock up on pieces to win later. The price of high-leverage lights-out relievers is high. I might think the deal looks imbalanced, but the Cubs stockpiled prospects for this very reason.

OK, but you can’t talk about this in terms of “a baseball perspective”! Clearly the reasons this deal makes you queasy have nothing to do with just baseball. Also in terms of BASEBALL reasons, doesn’t this feel like you’re defending Billy Beane’s terrible Donaldson trade? Or the Astros’ terrible Ken Giles trade?

OK, but when it’s the bottom of the 9th in the playoffs with two men on, are you going to want Aroldis Chapman’s 105-mph fastball against your team or for your team? This is more like the Michael Bourn-Brad Lidge deal. Giving up a lot in the future for one additional piece right now.

Yeah but that also means that when the Cubs go cheering in celebration at that big win, they will be running into the arms of a man who probably choked his girlfriend and then fired a gun multiple times into his garage. Are you OK with that?

Well, you still listen to James Brown, don’t you? You still love “Ignition (Remix)” (surely far more stomach-churning in context). You still watch Woody Allen movies. You still enjoy Degas’ paintings. Can’t you separate the act from the person? Look at that helpless swing from Jose Abreu in the face of a 91-mph slider following a 105-mph fastball and tell me it’s not art!

Yes, but that doesn’t mean that you need to make choices to pursue people who have done awful things. It’s one thing if the world accrues some sort of benefit from this work. Here, only the Cubs do! I can appreciate his fastball on the Yankees, thanks. And on top of that, Aroldis Chapman’s fastball is extraordinary but he’s not somehow irreplaceable. Hector Rondon has been as good this season.

OK, but last time I checked, Mr. “I Think Criminal Defendants Shouldn’t Have Stigma Forever,” you think we should let people who have served their time reenter society, find employment, vote, and be citizens without having the stigma of “ALLEGEDLY” in front of their names for the rest of their lives. We don’t know what happened that night. Chapman was not indicted, and he served a suspension in his job. Why can’t he just be another player now? Why must his collateral consequences last forever?

Well, obviously some categories of crimes we deem worse than others, and you proclaim that crimes that reinforce the patriarchy and misogyny are worse crimes. And do we really think Chapman’s changed? His general comments on the incident are not those of a repentant person and are pretty much a non-apology apology.

OK, but Matt Bush drunkenly ran over a guy’s head with a motorcycle and he plays baseball. Jose Reyes is out there playing baseball. And if what you care about is misogyny, I’m sure that MLB is full of misogynist guys if you ask. Everyone loved Kirby Puckett! Bobby Cox was a lovable grump! And those guys all hit their wives.

That’s hardly a defense. This gets back to what I said earlier: do we need to affirmatively seek out guys with that history? And on top of that, the Cubs paid a lot for the guy! Way more than the Yankees traded back in the offseason. It implies that the Cubs do not care about his past at all. Does this mean that hitting your girlfriend depresses your employability right after it happens, but not eight months after it happens?

Yes basically! Time and penalties separate us from our past indiscretions as a society. It’s not that time somehow heals the wound, but it’s a return to normalcy.

But I don’t want players who commit domestic violence to be normalcy!

Yeah, but when it comes to a collision of your conscience and baseball, why does your conscience only worry about this aspect of Chapman? Do you expect all businesses to have these high-minded ideals? If you do, where are people who do something you think is terrible supposed to do? Go work in the landfills and live under a bridge? If anything, the economics make it easier to let prior bad acts become history. Jhonny Peralta went from PED user to good SS for the Cardinals. Baseball execs are analytical thinkers in a zero-sum world. Your gain is someone else’s loss. SOMEONE will be employing Aroldis Chapman; your moral stance does not change that.

But the Cubs were supposed to be different! They’re my team! A lovable fun team of goofballs who wear fun costumes and play fun-loving pranks on each other and definitely don’t beat their wives.

OK, one, that’s wrong. Remember Starlin Castro? You think those sexual assault allegations just went away? And he was such a lovable scamp! Sammy Sosa had accusations of spousal abuse. Mark Grace has many a DUI to his name. And second, the Cubs are not heroes. They are, as you often say, millionaire jocks in their early 20s playing a child’s game for your entertainment. Do you expect them to reflect your values?

I guess we all have to accept that our heroes are mercenaries wearing cute outfits and our beloved sports teams are just billion dollar businesses.

There, now sit back and enjoy the baseball.

BUT THAT’S EXACTLY THE THING. Baseball is supposed to be an escape. It’s pure and beautiful and keeps us from thinking about our impending deaths. I want to enjoy it guiltlessly. Why can’t it also have a conscience?

Because baseball is not apart from the world; indeed it almost always reflects the world around it. Baseball is messy and full of flawed humans and you need to accept that.

Why must we accept all those flaws, though? That’s where I think you’re wrong! We celebrate Roberto Clemente and Hank Aaron and players with hearts. We celebrate Branch Rickey for selecting Jackie Robinson because we think his conscience was right.

But he only did it because it “made good baseball sense.” Which this deal makes too. Baseball is inherently immoral. We recognize Clemente, but Kennesaw Mountain Landis and Pete Rose and Ty Cobb are all celebrated too.

OK, but your answer cannot be “not as bad as Ty Cobb” every time.

Fine but modern baseball is not much better. Should I list the terrible working conditions for minor league players? Should I get into these baseball “academies” in poor countries? Terrible stadium deals that rob the public?

Agh! I guess I’ll just feel a little gross about my Cubs this year and a little queasy about any potential playoff glory being tainted by the 50% chance that Aroldis Chapman will be the focus of the big celebration, but only slightly less gross than I should feel about baseball itself?

Yeah that’s about right.

At least I can feel good about hot dogs and apple pie right?

Yeah, about that…

Since even before the Pirates began using a shift against left-handed hitters regularly in 2013, this tactic has slowly become more and more prevalent.  In fact, it has become so prevalent that it is now a fixture in Major League Baseball.  As the shift has gotten more popular, many variations of it have been invented for different instances.  In some extreme shifts, the second baseman is placed in short right field, while the shortstop is positioned slightly to the right of second base.  Another shift places the second baseman, shortstop, and first baseman in between first and second, creating an almost impenetrable wall of three fielders on one side of the infield.  And, in some cases with certain hitters, all four infielders are placed to the right of second base.

All of these shifts have been proven to be immensely effective.  In fact, when the Pirates first began implementing it regularly when nobody else was using it that much, it gave them a jaw-dropping advantage over other teams.  Since then, every defense in the league has used it routinely — but mostly only against left-handed hitters.  There are many pull-happy right-handed hitters who have benefited immensely from not having shifts implemented against them regularly.  There is no reason why shifts should not be placed against right-handed hitters.  Of course, there are some right-handed hitters who go the other way as or more often than they pull the ball.  But there are some right-handed hitters, some of whom are very good, who could be considerably hampered by a shift.  Let’s take a look at some examples:

Robinson Chirinos:

Although Robinson Chirinos is not an impact player for the Rangers, he is a player who could have a significant amount of hits taken away from him because of the shift.  In fact, Chirinos could be one of the players who is most impacted by a shift.  He pulls the ball a shocking 62.1 percent of the time, and goes to center 24.1 percent of the time.  That means that he only goes the other way 13.8 percent of the time.  That percentage is so minimal that there should be a shift against him 100% of the time.  This shift would take away much of his production.  Actually, I invented a calculation that determines exactly how much of his production the hypothetical shift takes away.  I call this calculation “Fixed Average”, and it is very simple:  Fixed Average (FA) equals hits (H) minus by hits that would have been outs with the shift (SHIFT OUTS) divided by at bats (AB).  Or FA = (H – SHIFT OUTS)/ AB.  In this calculation, “hits that would have been outs with the shift” are grounders in between short and third that got through, or grounders up the middle that got through (the second baseman would have been playing up the middle with the shift).  However, some of the SHIFT OUTS  would still get through even with the shift.  So in that case it can be assumed that 1/4 of those hits (in between short and third and up the middle grounders) would have been hits.  And if the number of hits that would have been taken away is not divisible by four, then the calculation assumes that less than 1/4 of the discussed hits would have been stopped.

Robinson Chirinos’ regular average is .205.  Using the aforementioned Fixed Average, his average is .170.  That difference should be more than enough to convince teams to shift against right-handed hitters.

Maikel Franco:

Right now, Maikel Franco is the premier outlet of production for the Phillies.  He has hit 18 home runs so far this year, by far the most by a Phillies player.  Of course, his home runs wouldn’t be impacted by a shift, but he does have a .257 average, which would be impacted by a shift.  That average is respectable, but he pulls the ball 44.9 percent of the time and hits it to center 35.1 percent of the time.  He only hits it the other way 19.9 percent of the time.  So with a shift hampering his production, how would Franco do?

Using Fixed Average, that .257 average drops to .214.  Watch out Franco.  If a shift comes your way, you suddenly become less productive than your teammate Ryan Howard.

Brian Dozier:

Brian Dozier is a hard-hitting Twins’ second-bagger who has been a mainstay in the rapidly changing Twins organization for four years.  He has put together good power numbers while maintaining a less than desirable, but still respectable, batting average.  He has a very good amount of patience at the plate, keeping his OBP steady with his walks, but that would all change if a shift were implemented on him.  Out of all the players on this list, none pull the ball and hit it to center more than Brian Dozier.  And none hit it the other way less than him.  He pulls the ball 52.9 percent of the time and goes up the middle 34.2 percent of the time.  That means he goes the other way less than 13 percent of the time.

Right now, Brian Dozier’s average is .249.  Using Fixed Average, his average with the shift becomes .214.

Albert Pujols:

It is sad to see what a pull hitter Albert Pujols has become.  Although he was never one to go the other way with consistency, Albert always went the other way enough so that a shift would not be implemented on him.  However, since Albert joined the Angels, he has started to pull the ball with alarming regularity in order to prolong his quickly fading career.  Because of his new approach, Albert has been hitting the ball hard and often despite his climbing age.  That could change, though, if he were faced with a continuous shift.  That’s not to say he hasn’t ever encountered a shift.  He has been sporadically shifted on by opponents for the past few years.  But it’s been too little to significantly diminish his hitting.  In the absence of a continuous shift, Albert has kept on pulling.  He pulls the ball almost half the time he’s up, going to left field at a 49.2 percent clip.  He goes to center 32.2 percent of the time and hits it the other way a paltry 18.6 percent of the time.  That may not sound as significant as the other players on this list, but he still owns one of the most lopsided pull percentages in baseball.

Albert’s regular average is .249.  Utilizing Fixed Average, that average drops to a paltry .208.  Suddenly, the number-four man in the Angels’ batting order becomes an expensive waste.

Evan Longoria:

To have Evan Longoria on this list is perplexing.  He is commonly referred to as the “laser show,” because he sprays line drives all over the field.  However, it seems that the “laser show” only hits lasers to one part of the field.  Indeed, he’s been pulling for a while, although not as much as he is now.  This year, he has started to pull much more than he has in the past.  It’s been working.  His batting average, mired at or below .270 for the past few years, has suddenly jumped to .290.  It’s not as if he’s getting younger, either.  He’s almost 31 years old, just a year removed from his prime.  Therefore, it’s a weird time for him to be getting better.  There is only one dramatic change in his statistics that would explain exactly what caused his production to change.  His other-way percentage has dropped eight percentage points from last year, from 26 percent to 18 percent.

As pointed out before, Longo’s average this year is .290.  His Fixed Average is .255.  Therefore, his production would drop to even lower than it was before this year if a shift were implemented against him.

Edwin Encarnacion:

Feared stalwart of the Blue Jays batting order, Edwin Encarnacion has consistently produced 30-40 home runs a year.  Also, unlike teammate Jose Bautista, he has been known to keep a respectable average while blasting baseballs into the stands.  But there is a reason why his wRC+ hasn’t dipped below 135 since 2012.  Since that year, his other-way percentage has never climbed above 20 percent.  This year, it is at an all-time low, as he struggles to maintain production as his age and career progress.  His production would grind to a halt much quicker, and his value would drop much faster, if teams would put a shift on him.

Encarnacion’s season average is at a respectable .264, but his Fixed Average is .239.  That is a difference between a formidable All-Star and a three-true-outcome type of hitter.

Adam Duvall:

Adam Duvall burst onto the scene this year, giving the depressed Reds fans something to cheer about.  His majestic homers earned him an invite to the Home Run Derby, and his wRC+ has remained steadily above 110.  These stats are especially amazing considering his former stats in the major leagues were not good at all.  This has left people wondering, though, what the cause is for Duvall’s sudden jump.  Why has he suddenly vaulted himself into the upper echelons of baseball players?  What has he changed?  The answer is, of course, because he has started to pull the ball with consistency.  In his first few years in the bigs, Duvall went the other way 27 percent of the time with bad results.  Now, he only goes the other way approximately 18 percent of the time, and he’s experienced very good results.

Duvall’s average so far this season is just hanging onto “not horrible” at .246.  With Fixed Average, it is well into the “bad” bracket at .213.

Kris Bryant:

I saved the best (and the most surprising) for last.  Ever since he arrived at the major leagues, Kris Bryant has been pulling more and more.  His pull percentage has risen to 47.5 percent, and his other-way percentage has dropped to 18 percent.  Although he joins a list which includes the likes of Evan Longoria and Albert Pujols, Bryant would by far be the most affected by the shift.  He would be most affected because of how good he’s become.  Presently, he has a WAR above 5 and a wRC+ of approximately 150.  Many people have predicted him to win the MVP, and if he continues producing at this rate, he has a fair shot at this prestigious award.

Bryant’s average is .284, and his power is off the charts.  However, his Fixed Average for the year is .245.  Nobody with an average of .245 or below (except for pitchers) has ever won an MVP award.  Of course, his stats would still be considered respectable with a .245 average, because of his 25 home runs.  He’d also probably begin to go other way if faced with a shift regularly, so that we could assume his average wouldn’t drop to .245.  But overall, his stats would most likely not be as good as they are now.

I may have left out some right-handed hitters known for pulling, but these were the players with the most drastic pull stats.  There are many right-handed hitters who go the other way just as much as they pull, but overall the evidence is pointing towards implementing a shift against select right-handed hitters.  It would drastically change their production and the way the MLB works.  It all depends, though, on if teams are willing to use it.  It would help them immensely, but as with the shift against left-handed hitters, it will take time for teams to adopt the strategy.  But soon, as they begin to see results, it will slowly become more and more prevalent to the point where it is used almost as often as the shift against left-handed hitters.  The Fixed Average calculation is based on some assumptions utilizing each player’s play-by-play data; it is my best attempt at forecasting what would happen to each player’s production if they were to face regular shifts.  All the statistical information in this article was acquired from the games prior to July 24th.

Note: this post is not by “guesto”, but rather by Carl Aridas.

***

If you have a net worth of USD $10 million, assuming nothing else, you are doing well.  As most readers of this site are either Americans or at least have a ready comprehension of the value of the American dollars, the American dollar is a readily understood value of money.  However, if the net worth of person B is Yen 10 million and person C has a net worth of HKD 10 million, what does that mean in comparison to you with a financial net worth of USD 10 million, and how can the three net worth values be compared via one more widely accepted value?

The quick answer, used by foreign exchange markets every trading day, is to use an exchange rate.  This allows Americans to equate HKD and Yen into their more familiar USD, people in Hong Kong to translate the Yen and USD amounts to HKD, and Japanese citizens to equate USD and HKD into Yen equivalents.

In baseball — yes, I recognize this is a baseball site — WAR is our exchange rate, and oWar and dWAR help translate different parts of the game into a common currency for us.  However, what if we want to equate dWAR by position into more a more traditional yardstick for some baseball fans who might prefer to see a triple-slash line rather than a dWAR value?  In researching the relative value of defense and the contract equivalent for Jason Heyward, I did just that and in so doing developed a simple methodology described below for users who prefer to use a triple-slash line.

In 2014 and 2015, Justin Heyward was worth a combined 4.8 dWAR.  With access to only games in the NY marketplace, this seemed high, and Heyward hadn’t passed my eye test for being a great defensive right fielder.  Starting with very traditional defensive metrics, I composed the following table of NL right fielders, using only their time in right field and ignoring all other positions, with the exception of dWAR:

Using just these defensive statistics avoids errors due to opinions of how hard a ball was hit, and also combined both range and positioning, either or both of which can be used to record putouts.  Once done, I repeated the exercise for the prior season:

And combining the two resulted in the following chart:

A quick comparison shows that Heyward is certainly the most durable right fielder in the senior circuit, and had the most putouts, and had near the most assists and led in dWAR over the two years in our study.  However, one must make an adjustment for the differences in innings played, which the next table attempts to do:

A quick review of the per-inning defensive metrics reveals that Heyward does indeed catch more fly balls than any other NL right fielder.  In addition, as assists are so minuscule to be almost useless (Heyward would have one more assist in 1,000 innings than Curtis Granderson), and errors even less frequent, the only source of extra defensive value assigned to right fielders is their position/range resulting in actual outs.  The next chart determines the extra number of outs over 1,267 innings of defensive value, which is the average number of innings Heyward played between 2014-15:

The last column above is the key – the number of extra outs per season of the fielder’s defense.  As a side note, note that Giancarlo Stanton is also an extremely strong defender, and Jeff Francoeur still had defensive value in 2014-15.  Conversely, someone needs to teach Jorge Soler what a glove is for, and at this point in their careers both Yasiel Puig and Matt Kemp will be leading the charge to bring the DH to the National League.

Below are the rather pedestrian offensive values of Jayson Heyward in 2015:

Less than 15 homers, only 50 extra-base hits, and only 60 RBI to go along with 79 runs scored had me convinced that the Cubs had made a rather severe overpay.  Even his .359/.439/.797 slash line failed to convince me otherwise.

However, adding the extra 43 “extra outs” computed previously as an additional 43 singles (I know readers already think that some if not most of these extra outs had to be extra bases in the gaps, but I decided to be conservative in my estimates) to Heyward’s slash line results in the following:

A triple-slash line is familiar to all readers, and I assume all readers recognize that is a great triple-slash line, just as USD $10 million is a lot of money.  A .429 OBP in 2015 would be fifth in baseball, ahead of Trout, McCutchen and Rizzo and behind only Harper, Votto, Cabrera and Goldschmidt.  His OPS would be sixth in baseball, behind Harper, Goldschmidt, Votto, Trout, and Cabrera but still ahead of Donaldson, Cruz, Encarnacion, Davis and Ortiz.

This analysis, of converting defensive value to traditional statistics, can be leveraged and used elsewhere.  Certainly not limited to right fielders, this same methodology can be followed to other positions, although in the infield, both assists and putouts would need to be quantified compared to just putouts as done here.  Also, since these basic defensive statistics have been kept for decades, the same analysis could be repeated using historical players.