Earlier in the month I had an idea. It all stemmed from the idea of quantifying the un-quantifiable. I was going to record grit.

A lot of times we hear about how gritty a player is, but it’s tossed around with no real proof. Sure Nick Punto dives into first a lot, but is that really more gritty than stupid? Is a guy like David Eckstein really the grittiest of all gritty players, or can it be a guy we don’t really notice?

To figure all of this out I, along with some help, wrote a formula. The formula is imperfect, because of a lack of reliable sources for things like headfirst slides and broken-up double plays, but it tries and does its job. The formula is as follows:

(((InfH+1stS3+(.5*CS+SB2+1.5*SB3+3*SBH))(2*P/PA+.5*Foul/S%))/(HR+1)+(.1*PA/Seasons)+PitchingAppearances

Where InfH stands for Infield Hits and 1stS3 means first to third on a single, we have found a way to see a players GRIT (Game Rating In Testosterone.) All this stat is designed to show is who works harder to score a run for their team, it doesn’t show you who is better or worse, but it does show who tries.

Using this formula my small team of experts has found David Eckstein to have a career GRIT of 172.16, which is very impressive over a 10-year career, but it’s no Juan Pierre, who has amassed a career GRIT of, wait for it, 1582.

We also found the difference between Martin Prado and Justin Upton, who was the subject of criticism from Diamondbacks GM Kevin Towers who said he wasn’t gritty enough prior to trading him for Prado. We found out that Kevin Towers may have been wrong.

Using their numbers the formula says that Prado has put together a GRIT of 57.93 in his career, where Upton has a GRIT of 68.65, despite playing in one less season. So, Kevin Towers, you may need to rethink your strategy.

Also invented was TeamGRIT, a stat that uses numerous numbers to calculate how hard a team works for each run.

A disclaimer here before I list the GRITs: I am not trying to say that some teams work harder than others, nor am I saying that a high GRIT is more or less valuable than a low GRIT, all these numbers illustrate is that some teams are more comfortable with power numbers to win games, while others are more inclined to small ball.

The formula used is

(((InfH+1.5*BuntHits)+1stS3+2ndDH(.5*CS+SB2+1.5*SB3+3*SBH)(Pitches/PA+.5*Fouls/Strike%)+(GIDPinduced+OFAssists))/(HR+.5*HRA))+(.1*PA/GamesPlayed)

The following are the AL leaders prior to games played on August 7th 2013

Royals – 90.57 (9th in wins)

Indians – 74.77 (6th in wins)

Red Sox – 73.92 (1st in wins)

A’s – 70.57 (5th in wins)

Blue Jays – 61.73 (10th in wins)

Rangers – 56.52 (4th in wins)

Astros – 55.70 (15th in wins)

White Sox – 51.62 (14th in wins)

Rays – 51.10 (2nd in wins)

Angels – 48.98 (12th in wins)

Twins – 46.97 (13th in wins)

Yankees – 45.59 (8th in wins)

Orioles – 40.49 (7th in wins)

Tigers – 30.30 (3rd in wins)

Mariners – 25.90 (11th in wins)

The most interesting numbers to me are those of the Royals and the Tigers. On opposite ends of the spectrum, one is a team that absolutely crushes the ball, everything that comes their way, the Tigers hit it, and they’re fine with it. They don’t feel the need to manufacture runs the way that the Royals do. The Royals seem to grind more to score their runs. More than any other team in the league by a large margin. They, like the Astros at 55 GRITs, are doing everything in their power to score more runs. It doesn’t always work, but there’s something to be said about a team that works to get extra runs and extra outs. If anything, they’re less comfortable with a lead than the Tigers. That isn’t to say the Tigers get lazy, just that they tend to not have to try so much.

In the NL there appears to be a negative correlation between GRIT and wins; I assure you, this is just a coincidence.

NL leaders prior to games played on August 7th 2013

Pirates – 80.83 (2nd in wins)

Rockies – 77.08 (8th in wins)

Marlins – 76.31 (15th in wins)

Brewers – 73.57 (14th in wins)

Mets – 67.33 (11th in wins)

Giants – 64.21 (12th in wins)

Padres – 62.53 (9th in wins)

Phillies – 57.06 (10th in wins)

Dodgers – 51.83 (4th in wins)

Cardinals – 47.67 (3rd in wins)

Nationals – 45.03 (7th in wins)

Cubs – 44.79 (13th in wins)

Diamondbacks – 42.38 (6th in wins)

Reds – 39.99 (5th in wins)

Braves – 31.12 (1st in wins)

The only thing these numbers definitively tell us is that there is a lot more GRIT in the American League, which is a deviation from the stereotype of hard-hitting AL clubs. The longball is less important in the American League, whereas manufacturing runs is a lot more emphasized. In the National League one team stands out from the pack: The Pirates.

They have a GRIT of 80.83 while also being in 2nd place, they are the only team in the top 5 of wins who is also in the top 5 of GRIT. The Pirates also hit a fair amount of home runs, but that’s not enough for them. They aren’t comfortable with just a lead. They want more of a lead. They try their damnedest to score more runs than anyone else by any means necessary. Is this because they spent so many years as a losing team? Possibly, but that’s just a theory.

As I said before, these numbers are not proof that any team is better than another, nor are they proof than any player is better than another, just that some teams and players are GRITtier than others.

So there you have it, your introduction to GRIT.

Note: I have no idea if I’m the first to do this, but quite frankly I don’t care.

I feel as though this will be the article where my disclaimer is put to full use, as this seems to be a comparison that is an easy one to make, but no one (at least from what I can tell) is making it. Andy Pettitte and Mark Buehrle have very similar career ERA’s (3.88 and 3.85, respectively); they were both late-round draft picks, as I covered earlier, and…well, that’s basically where the similarities end.

Buehrle is obviously famous for his durability, having never gone on the DL, and while Pettitte has had some durability issues recently, he’s been pretty durable for his career, with 10 seasons of 200 innings in his first 14 years in the majors. Obviously, Pettitte has considerably more innings pitched (3255.1 to 2829.1), as he’s existed for five more years.

One key difference between the two is peripherals. Pettitte’s career K% is a solid¹ 17.4%, whereas Buehrle’s is, well, a less solid 13.8%. While Buehrle also has better career control than Pettitte (5.5% to 7.3% BB%), Pettitte is a little more groundball inclined (48.6% to 45.4% GB%).

Put it all together, and Pettitte has a career xFIP² of 3.70, whereas Buehrle’s sits at 4.21, a 51-point difference that would suggest that these two men are not very similar. Their respective WAR values (4.1 WAR/200 IP for Pettitte, 3.3 for Buehrle) also works to support this conclusion. However, this is FanGraphs WAR, based off of FIP; looking at their Baseball-Reference WAR–i.e. runs-allowed WAR–it would appear that Buehrle is better than Pettitte (3.8 to 3.6)³.

While we’re on the subject, let’s see some other pitchers in that general vicinity of career rWAR/200 innings, that I may or may not have picked selectively to further my argument⁴.

Nolan Ryan–3.0

Ted Lyons–3.2

Gaylord Perry–3.4

Steve Carlton–3.5

Phil Niekro–3.6

John Clarkson–3.7

Bert Blyleven–3.8

Fergie Jenkins–3.8

Are several of these pitchers people from the days of yore whom you’ve never heard of? Yes. Are they all Hall of Famers? Also yes.

So why is Pettitte considered to to have a strong case for the Hall of Fame, while Buehrle is borderline at best? It all comes back to that key pitcher stat: wins. Because, as the article cites, Pettitte is part of an elite group: only 46 pitchers have 250 career wins, and 32 of them are in the Hall⁵. Buehrle, meanwhile, is toiling away with a meager 182 wins, only 157th all-time.

Obviously, wins are a completely meaningless statistic, and Pettitte having that many career wins is almost entirely circumstantial. The above article mentions that Pettitte played on playoff teams for 14 of his first 17 seasons, compared to only two for Buehrle’s first 13 seasons, and, of course, Pettitte has played most of his career with one of the best closers of all time, whereas Buehrle played much of his career with a guy who partakes in, uh, unusual fowl ingestion techniques.

There’s also the fact that Pettitte played most of his career in New York, the attention pimp⁶ of cities; while Chicago is one of the larger cities in the U.S., its media shrivels up and dies in comparison to the Big Apple’s. How much this contributed to Pettitte’s alleged divaism–and confirmed indecisiveness–will never be known; what we do know is that Buehrle is humble about himself and his achievements, probably more so than Pettitte.

In many ways, the situation with Pettitte and Buehrle mirrors that of NFL linebackers Ray Lewis and London Fletcher; both Lewis and Fletcher have very similar career stats, but the former is a surefire Hall of Famer, while the latter has more of an outside shot. Some have theorized that the reason for Lewis’s increased fame are twofold: first, that he came from a high-profile school (Miami) as a high-round draft pick (26th in the first round), as opposed to a low-profile school (John Carroll) as an undrafted free agent; obviously, since both Pettitte and Buehrle are both very low-round draft picks (22nd and 38th, respectively) from very low-profile schools (San Jacinto and Jefferson, respectively), this is obviously irrelevant.

And the second reason for Lewis being more popular than Fletcher? Well, this. In short, what Mr. Easterbrook’s theory states is that Lewis–and possibly, by connection, all similarly-inclined athletes–act the way they act in order to promote their own fame, and build up a case for the Hall of Fame. This could easily be applied to to Pettitte and Buehrle; the former is considerably more self-promoting, while the latter is much more willing to give his teammates credit.

So, while this may have been a largely pointless article, the main message remains clear–two pitchers are very similar in most respects, instead of their reputation, and that reputation may have a lasting effect on their immortality. Why are men judged by their reputations instead of their accomplishments? Now there’s a question worth answering.⁷

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¹Remember, this was mainly accrued during the steroid era, when that level was (roughly) average.

²Please note that xFIP only goes back to 2002, and Buehrle’s and Pettitte’s careers (and their career ERAs cited above) go back to 2000 and 1995, respectively.

³If aggregate WAR values are more your thing: Buehrle has nearly 20 fewer career wins than Pettitte by fWAR (47.3 to 67.0) but is less than five wins worse than him by rWAR (54.0 to 58.5).

⁴Twain was right.

⁵Of the 14 that are not, 8 are still eligible or have not yet become eligible: Pettitte, Greg Maddux, Roger Clemens, Tom Glavine, Randy Johnson, Mike Mussina, Jamie Moyer, and Jack Morris.

⁶I.e. one that makes attention whores out of the famous.

⁷Believe me when I say I did not intend that to sound as deep as it did.

Strikeout rates have climbed since 2006, while league wOBA has dropped.  Responses to ballooning strikeout rates have been mixed. One response is to trade one of your best hitters, while another is to lead the MLB in home runs. Some clubs are more averse to strikeouts than others.

It’s no secret that Diamondbacks GM Kevin Towers hates strikeouts. Since taking over in 2010, Towers has discarded every Diamondbacks player who struck out 100 times or more from the 2010 club that set the major-league record for strikeouts in a season by striking out 24.7% of the time. His 2013 squad’s 18.5% strikeout rate is 10th-lowest in the majors. However, the decreased strikeout rate has not resulted in increased offense. The 2010 D-Backs scored 4.40 runs per game, posting a .325 wOBA and 93 wRC+, a shade better than that of the more contact-driven 2013 Diamondbacks who currently average 4.17 runs per game with a .313 wOBA and 92 wRC+. While the 2010 team had the 4th-best walk rate at 9.5%, the 2013 Diamondbacks are just 13th at 8.1%. Though the 2010 Diamondbacks struck out more, they also walked more, and made more quality contact, as shown by a .312 BABIP% and .166 ISO which were 2nd and 4th in the majors, respectively. The 2013 team has a .301 BABIP% and .135 ISO, good for 10th and 23rd in the majors. A look at the plate discipline numbers shows that the 2013 Diamondbacks swing at more pitches out of the strike zone and make more contact on those swings than the 2010 team.

If a hitter can cut his strikeout rate while maintaining his walk rate and power production, that is special. However, there is usually a tradeoff between power/walks and contact. After all, not everyone can be vintage Albert Pujols. To dig deeper into the balance between power and contact, I separated MLB hitters by strikeout percentage into five groups, with 30 hitters per group. I limited the study to qualified hitters, to eliminate the presence of pitchers and small sample size hitters. Not surprisingly, the first group was the clear leader in home run rate.

I included WAR even though it includes defensive and baserunning values because I thought that the contact-heavy hitters in group 5 might make up for their offensive deficiencies by being better defenders or baserunners. However, the total WAR for each group tracked offensive production for the most part. The first four groups are very close together with regards to wOBA. As I expected, the most strikeout-heavy group owned the highest walk and home run rates. Group 2 made up for its lower home run rate with a higher BABIP%. The rates of doubles were very close in all groups, ranging from 4.5% in group 5 to 5.2% in group 3. Group 5 had the lowest homerun and walk rates. Despite group 5’s ability to put the ball in play, the contact generated was of a lesser quality due to higher contact rates on pitches out of the zone. With the exception of Edwin Encarnacion, Adrian Beltre, and Buster Posey, none of the hitters in group 5 had more than 20 weighted runs above average (wRAA). The group average was 0.9 wRAA. Though group 5 had the lowest WAR of any group by a wide margin, they had the 3rd most plate appearances.

As the above table shows, there is not a significant negative connection between higher strikeout rates and offensive production. In fact, the most contact-heavy hitters are far less productive offensively than their more strikeout-prone counterparts. Of course, the plate approach of Chris Davis would not work for Marco Scutaro and vice versa. The idea of an ideal groundball rate for individual hitters has been posited. I would suggest that there is also an ideal strikeout rate for individual hitters. The following is a list of five hitters who I believe would benefit from a more or less contact-friendly approach.

Matt Holliday has trimmed his strikeout rate from 19.2% in 2012 to 14.4% this year. However, he has also trimmed his wRC+ from 141 to 137. His BABIP% is down from .337 to .312, but this is likely due to a less formidable batted ball profile, as his xBABIP% has dropped from .328 to .304. His Line Drive/Infield Fly ratio is down from 89/11 to 58/16. Furthermore, his home runs on contact has dropped from 5.7% to 4.8% and his overall homerun rate has dropped from 4.9% to 3.5%. His flyball distance has decreased from 305.15 to 294.66. A look at the PITCHf/x data shows that Holliday is swinging more and making more contact on those swings. His Swing% has jumped from 47.2 to 49.9 and his Contact% has gone from 78.5 to 81.8. His O-contact% has gone from 65.0 to 66.1 and his Z-contact from 86.1 to 89.0. While Holliday is striking out less while walking at the same rate, his swings have been noticeably less aggressive, and his overall offensive production is down.

Mike Moustakas has reduced his strikeouts even more than Matt Holliday, going from 20.2% in 2012 to 13.6% in 2012 while essentially maintaining his walk rate. However, his offensive production is down significantly, from 90 wRC+ to 79 wRC+. His home run rate has dropped from 3.3% to 2.6%, and his home runs on contact is a paltry 3.3% compared to 4.5% in 2012. His fly ball distance has dropped to 279.2 to 274.6. Moustakas’ increased contact rate has come largely from swings on balls outside of the zone, as he has seen as increase in O-Contact% from 63.7 to 74.3. During GM Dayton Moore’s tenure, the Royals have had an emphasis on putting the ball into play. Their 16.4 K% since 2007 is the lowest in the league over that time frame. However, they have only a 92 wRC+ over that span, good for 21st in the league and their BB% of 7.0 is dead last. While the Royals’ emphasis on contact appears to have helped Eric Hosmer, its application to Moustakas has had a negative impact on his production.

Adrian Gonzalez has undergone a significant change since being traded from the Padres. While playing in the spacious Petco Park Gonzalez posted home run rates between 3.8-5.9% and walk rates of 8.2-17.5%. His wRC+ numbers ranged from 123 to 156. His home run rate dipped to 3.8% in his first year at Fenway, his lowest since his first full season, but a still solid walk rate of 10.3% and a .380 BABIP% led him to an excellent 154 wRC+. Since then, his ability to draw walks and hit for power have plummeted. From 2012 to the present, Gonzalez has a 2.9 HR% and a 6.7 BB%. While Gonzalez has posted his three best contact rates since 2011, his O-Contact% has been between 70.1 and 75.9, well above his career rate of 67.1. Though Gonzalez has slightly improved his power production from 2012, his 126 wRC+ remains a far cry from his peak years. In Gonzalez’ best years, he had strikeout rates in the 17-20% range. He can still be a productive player, but the make-contact approach has taken away much of his power and walks.

Asdrubal Cabrera is posting career high strikeout and fly-ball rates in 2013. Unfortunately for him, this approach has not led to an increased power output, as his home runs on contact, average fly ball distance, and ISO are virtually unchanged from 2012. The 22.0% strikeout rate has conspired to cut his wRC+ from 113 to 91. In an effort to hit for more power, Cabrera’s contact rate has gone from 84.0% to 78.6%, a career-low figure, and his walk rate has dropped from 8.4% to 5.8%, also a career low. Though Cabrera’s BABIP%  has dropped from .303 to .286, his xBABIP% is up from .319 to .334, suggesting that he can be productive when he puts the ball in play. Not yet 28, it is time for the Indians shortstop to go back to the plate approach that made him a productive hitter in 2009-12, controlling the strike zone with a more level swing. In picture form, here is a swing from 2011 when Cabrera had a K% of 17.8 and a 119 wRC+.

 Yoenis Cespedes has improved his home runs on contact from 5.9% in 2012 to 6.4% in 2013. However, because of the jump in his strikeout rate from 18.9% to 23.9% his overall home-run rate remains at 4.3% and his ISO is basically the same. His wRC+ is only 96, compared to 136 in his debut season. Cespedes is hitting more fly balls at 47.7% compared to 39.9%, and their average distance is the same, but those fly balls have come at the expense of line drives and ground balls, which has caused his xBABIP% to sink from .305 to .279 and his actual BABIP% to go from .326 to .255. Because Cespedes is relatively new to the league, I wanted to see if pitchers are attacking him differently. However, Cespedes has been pitched to in largely the same fashion as 2012, but with slightly more fastballs and less changeups. Cespedes has been less able to hit those fastballs, as he is only 0.37 runs above average per 100 fastballs, compared to 1.71 last year. Cespedes has been seeing slightly more pitches out of the zone, as his Zone% has decreased from 46.2% to 45.1%, but his O-Zone Swing% is mostly the same. For the most part, Cespedes has been getting beat in the strike zone, as his Z-Contact% down from 84.2% to 81.0%. Because Cespedes’ raw power and athleticism are so impressive, there is a temptation to be overaggressive at the plate. He will likely always be an aggressive hitter, but if he can cut his strikeout rate to his 2012 level, it will be worth the decrease in home runs on contact.

Unlike many people, I do not think that strikeouts are inherently bad. For some hitters, the increased strikeouts are the cost of home runs and walks. Other hitters would be well served to put more balls in play while suffering a loss of power. However, start implementing a one-size fits all approach of strikeout avoidance and you’ll end up like the Royals.

Note: I have no idea if I’m the first to do this, but quite frankly I don’t care.

As you’ve probably grown sick of hearing¹, Brewers center fielder Carlos Gomez is undeterred by his team’s general shittiness and is having a terrific season–his 5.7 WAR² is a very close third in the NL, and one of the players he’s behind may be out for a while. While he’s always been an excellent defender (50.8 career UZR prior to this season), his bat has never been particularly good (his career-best wRC+ prior to this season was 105, last year).

A massive improvement on offense has been the driving force behind his MVP-type numbers, as his wRC+ of 133 this year sits at 16th in the NL; this can be attributed to an increase in power (.235 ISO, compared to .150 for his career) and an uptick in BABIP (.350, compared to .311 for his career). Many of the articles listed in the first footnote cite these as reasons behind his improvement. One element of his game that has not improved, however, and is getting startlingly little coverage from the media, is his plate discipline; his walk and strikeout rates sit at 6% and 25.1%, respectively, meaning his BB/K of 0.24 is 6th-worst in the NL.

Now, should Gomez end up leading the league³ in WAR with that kind of plate discipline, how revolutionary would that be? I decided to find out. I looked up every NL WAR leader going back to 1910 (when strikeouts for batters⁴ were first recorded) and recorded their strikeouts and walks, then calculated each batter’s K/BB⁵ and ranked them from lowest to highest; the top 10 are listed below.

The average K/BB was 0.85, meaning Gomez’s⁶ is nearly 400% worse.

Now, any fan of baseball–sabermetrically inclined or otherwise–knows that this year (and in recent years), plate discipline has been at an all-time low. Knowing this, I decided to measure each player differently. I gathered up all the league-average K/BB’s for every year going back to 1910, then divided each WAR leader’s K/BB by the league-average K/BB for the respective year, and created K/BB-, in the style of ERA-. I then ranked each batter’s K/BB- from highest to lowest (i.e. worst to best); the top 10 are listed below.

The average K/BB- was 58, meaning Gomez’s was almost 200% worse.

The closest match to Gomez’s season (at least in terms of plate discipline) was Pete Reiser in 1941. That year, his K/BB was a very solid (by our standards) 1.54, but the league-average was below 1, meaning he was actually pretty bad by league-adjusted standards.⁷

Even when we adjust for the era, Gomez’s plate discipline is historically bad. People may argue about the value of plate discipline to a hitter, but you can’t dispute the facts: the average K/BB for a WAR leader is 42% better than league-average, and Gomez’s is 69% worse than league average, and yet he is contending for the WAR lead.

So, what does this mean? Obviously, as I mentioned in the introduction, a large part of Gomez’s value comes from his defense, and thus his offense is probably behind that of many others on this list. Gomez’s season has come out of nowhere, at least to some degree, meaning that it may be a fluke; for that to be determined, we’ll just have to wait and see. Though Brewers fan may be discouraged to hear it, history suggests it probably is.

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¹You know, from here, and here, and here, and here, and here, and here, and here. Also, I’ve now started doing footnotes a la Grantland, although there isn’t any linking yet.

²All stats are as of Tuesday, August 13th, in case this takes some time to get published.

³I’m really getting sick of people using “the league” to refer to MLB as a whole; it’s misleading and it’s wrong. This isn’t the NFL–there are two leagues, not one. When you’re referring to MLB, say “the majors”, not “the league”.

⁴Strikeouts for pitchers go back all the way to 1876 (i.e. when all pitcher stats go back to). Why’d it take 34 years to record strikeouts for batters?

⁵I’ve always hated BB/K–it returns numbers that are much too minuscule. I prefer the larger form of K/BB.

⁶Is that correct, or should there be no “s”?

⁷Reiser’s success that year–166 wRC+–was mainly motivated by a .377 BABIP, 97 points higher than the MLB average that year, and by far the highest of his career.

I was watching the Twins game a few weeks ago when veteran Jamey Carroll effortlessly took an outside pitch to right field, as one might hope he would. The announcers were quick to praise his ability to “go with the pitch”. I’ve seen this play out time after time, often followed by praise for “going with the pitch” and “not trying to do too much”. That got me thinking, do some hitters go with the pitch better than others? Is this a desirable skill or does it leave the hitter vulnerable? Can a defense exploit this trait with a defensive shift much like we see shifts on straight pull hitters?

To dive into this I captured the angle of each hit ball since 2010 and displaced that against the angle that I expected the pitch to be hit. For example, an inside pitch on a right-handed batter could be expected to be hit near the left field line, while an outside pitch could be expected to be hit near the right field line. Everything in between would be evenly spread across the field, relative to the pitch’s location across the plate.

To make it a little more accurate for right-handed hitters vs left-handed hitters, I analyzed the actual pitch placement for pitches that become hit balls. As you can see below, all hitters prefer the ball just a touch on the outside part of the plate. I took two standard deviations of the hit pitches and considered that the spectrum that we’ll map to the field, with unique values for right or left handed hitters. We’ll call this our hit zone.

The players that made it to the top of the data below are the ones that tend to go with the pitch. That is, they take the outside pitch to the opposite field, they pull an inside pitch, and they take a pitch down the middle of the plate straight through center field. They are less random and more predictable.

With that, here are the most predictable hitters of 2013 through August 10th.

For comparison sake, here are the 10 least predictable hitters.

Let’s explain this data before we go any further.

First off, the field is 90 degrees and thus, the values are all in degrees.

• Average Absolute Angle Difference: If a pitch was on the inside of the plate on a right-handed hitter, and was determined it would be “properly” hit somewhere near the left field line, but was actually hit 20 degrees to the right of that expected spot, this number shows that difference, averaged across all hit balls.
• Mean Angle Difference: Some balls are pulled against their expected spot, others are not. Pulled balls show up as a positive angle (for both L or R hitters), while negative angles indicate the batter was behind the pitch. The Average Absolute Angle Difference does care either way, while this metric does. A higher positive value here indicates a pull tendency while a negative value indicates that a batter is more often than not behind the pitch. Those batters with a higher value from 0 indicate they could be a little more predictable to pull or push.
• Standard Deviation: This should give you an indicator as to what kind of angle you could expect ⅔ of a batter’s hit balls to be where you expect them to be. For example, Chris Stewart has a standard deviation of 21.97 degrees. Given a very outside pitch that you’d expect to be hit down the right field line, you can expect that Stewart will usually hit that ball down the line or at most 20 degrees to the left or foul.

Looking at the data back to 2010 I found these players continually near the top. It seems for them, they have always hit this way, and can be expected to continue to hit this way.

• Marco Scutaro
• Ryan Hanigan
• Jamey Carroll
• Denard Span
• Elvis Andrus

Now, what can we do with this knowledge? Can a defense use the left-handed shift on a right-handed hitter? To look at this we’ll look at spray charts, but with a very important distinction from a standard spray chart – we’ll limit the hit balls to those hit on pitches on the outside of the hit zone.

I’ll start you off with a spray chart for someone not on our list – Jose Bautista. This chart shows where he hits outside pitches. He looks like a good spray hitter when you look at only the outside pitches. As a defense, you wouldn’t shift on Bautista AND pitch him outside.

Let’s move on to someone who was continually at the top of our list, Marco Scutaro. You’ll see Scutaro reliably hits balls on the outer third of the hit zone to the right side. He still hits a fair number of ground balls across the infield, so an infield shift wouldn’t be advised. But liners and fly balls in the outfield are heavily weighted to the right. Using a control pitcher, pitching on the outside ⅓ of the hit zone, you could reliably shade the outfield to right field.

The same applies for Jamey Carroll, another player who, like Scutaro, shows up on our list year after year.

Takeaways
I’ve found that the tendency of pushing the ball on outside pitches to be much more predictable with our leaders than pulling the ball on an inside pitch. There’s surely more to be gleaned from this data, but the outfield shift on these predictable push hitters is definitely the most interesting.

Data Collection & Mining Techniques
The metrics for all hitters, year-by-year back to 2010 can be found here: https://docs.google.com/spreadsheet/ccc?key=0AtERgAQ83pATdDItUzAxXzhMZm41cGFPRjgxOEdZa0E&usp=sharing

All of the data used in this post was loaded from MLB’s gameday servers into a MongoDB database using my atbat-mongodb project. This project is open source code that anybody can use, modify, contribute to, etc. Fork me please!
https://github.com/kruser/atbat-mongodb

The following programs were used to mine and plot the data from the mlbatbat MongoDB database.

• https://github.com/kruser/mlb-research/blob/master/src/main/python/HitBallPitchLocation.py
• https://github.com/kruser/mlb-research/blob/master/src/main/python/HitPredictabilityIndex.py
• https://github.com/kruser/mlb-research/blob/master/src/main/python/SprayCharts.py

The Red Sox employed outfielder J.D. Drew from 2007-2011 and signed his brother, Stephen, to a one-year contract prior to the 2013 campaign. The Drews are ballplayers who go about their business in similar ways — they’d prefer to avoid the limelight and just hit the baseball. It’s an admirable quality, but not one that’s so cooperative with the Boston media or fans. For some inexplicable reason, Boston is enamored with players whose highs are raucous and whose lows are dismal. This was never the case with J.D., and doesn’t appear to be the case with Stephen, but the numbers say that they’re some of the best Sox contributors in recent history.

The Background

J.D. and Stephen were high profile prospects in their respective draft classes and both went to Florida State University.* Prior to signing with the Sox, the two had established themselves in the National League. Both brothers, however, followed completely different paths to their contracts with the Boston Red Sox. In 2007, the Sox signed J.D. at the pinnacle of his career to a 5-year, $70 million contract. Stephen signed a low-risk, high-reward deal with the Sox for 1-year at $10 million prior to 2013. He’s the shortstop for now — Xander Bogaerts is the future. Boston fans can’t help but notice the similarities between the two brothers, which extends beyond the striking resemblance to one another and the shared uniform number (#7). Stephen plays the game much same way as J.D. did, with a smooth and dispassionate style that makes hitting and fielding a baseball seem as simple as driving a tractor (because this is all I like to imagine J.D. does now that he’s stepped away from the game). The two have nearly identical left-handed swings and are known around baseball to share one elite quality: their approach to an at-bat and their knowledge of the strike-zone.

Batter’s Eye

J.D. Drew was heralded as one of the most disciplined hitters in baseball when he signed with the Red Sox in 2007. This means he had an excellent understanding of the strike-zone and had the ability to take close pitches for balls to reach base. Less was known about Stephen when he arrived in Boston, as he was a lower-profile signing. But after his first 84 games, it’s clear that he possesses the same skill. The skill can be quantified by using a PITCHf/x statistic called O-Swing%. The stat measures the percentage of pitches a batter swings at outside the strike-zone. If you need more info on O-Swing%, FanGraphs has a good summary. But suffice it to say that the lower a hitter’s O-Swing%, the better handle he has on the strike-zone (there are a few exceptions; for example, Miguel Cabrera does not see very many pitches in the zone, but is still skilled enough to square up balls that are off the plate. He has one of the highest O-Swing% in the MLB). I’ve plotted BB% (a hitter’s rate of drawing walks) vs. O-Swing% for each hitter with at least 300 plate appearances this season and super-imposed J.D.’s numbers he racked up with the Sox (2007-2011):

We can make a couple of observations. First off, BB% clearly trends with O-Swing% — this makes sense: those who swing less often at pitches outside the zone are more likely to walk. Second, we see that Stephen possesses the same plate discipline as J.D., ranking around the 15th percentile in O-Swing%. In fact, both brothers’ BB% is slightly higher than we might expect based on the linear regression (i.e. the data points lie above the trend line). Finally, we notice that if J.D. played in 2013, he would lead the league in O-Swing%. That’s right: J.D. Drew would have the best eye in Major League Baseball if he strapped on the spikes and decided to have another go. Players who are more likely to walk (i.e. who have a high BB%) are more likely to have a higher OBP, one of the fundamental stats for determining a player’s value. It’s not difficult to see why the Drews got the big bucks from Boston.

Fans (including myself) were under the assumption that if you have a great eye, you strike out less. This is not such a ridiculous proposition: if you have an elite knowledge of the strike-zone, then surely you should utilize it with two strikes. But a simple plot of K% (the rate at which a hitter strikes out) vs. O-Swing% demonstrates otherwise:

A blob. The two statistics are not correlated in the slightest. To Sox fans, it seemed that J.D. Drew often took the third strike with the bat on his shoulder — the “Master of the Backwards K”. Since Sox fans knew he had a great eye, it seemed as though this happened at an alarming rate, as the expectation was that a lower O-Swing% should also lead to a lower K%. The two stats are not correlated and Drew did not strike out at an alarming rate at all — if he decided to step into the batter’s box in 2013 he’d be right around the league average in K%. Because J.D.’s eye was touted (for good reason) as one of the best in the league, many fans unfairly jumped to conclusions about how often he should strike out. Also, if we take a look at where Stephen lies in the data spread, we see that he strikes out at a much greater rate than his brother, but seems to take less heat from Red Sox Nation. This might be because Sox fans love players with a flair for the dramatic — something Stephen has shown he possesses whereas J.D. never did.

The “Anti-Clutch”

The biggest hit I remember from J.D. Drew was a grand slam in Game 6 of the 2007 ALCS, which turned the tide of the series. As for walk-offs, I remember one biggie: a line-drive over the head of the right-fielder in Game 5 of the 2008 ALCS against the Rays to cap a massive Sox comeback. Gordon Edes of ESPNBoston reminds us that there was, in fact, one more, but goes on to summarize J.D.’s reputation brilliantly: “Mr. Excitement, he was not.”

“The Anti-Clutch” was the nickname bestowed to J.D. Drew by my dad, who was often frustrated with his performance in tight spots. But my dad’s a stubborn guy and may have been swayed by one strikeout (he also championed the nickname “Master of the Backwards-K”). Certainly he hasn’t done a fair analysis of the relevant statistics, so I’ll do it here. CLUTCH is a complicated statistic that attempts to quantify a player’s performance in high-pressure situations. It utilizes WPA (win probability added) and LI (leverage index, a measure of just how “high pressure” the situation truly is) and normalizes the league-average player to zero. You can read more about CLUTCH here, but the number generally ranges from -1 to 1. Thus, a player with a positive CLUTCH can be considered just that (clutch) but a player with a negative CLUTCH often chokes in the tight spots. So how did J.D.’s numbers look during his time in Boston?

Yikes. That’s all there really is to say about that, except for it likely validates the opinion of Dr. D’Andrea. For reference, Stephen Drew’s CLUTCH is 0.64 during his first season in Boston, which checks in at well-above average. Nonetheless, J.D. Drew has had a tremendous, all-star career, similar to the likes of Eric Davis, Raul Mondesi, and Kirk Gibson.

Stephen’s Trend

Jose Iglesias started the season as the Red Sox shortstop when Drew missed much of spring training due to a concussion. When Drew returned, Iglesias was optioned to Pawtucket, but was recalled when Stephen missed time in July with a hamstring injury. Iglesias was traded to the Tigers in the deal that brought Jake Peavy to the Sox, clearing the way for Drew to re-assume the everyday job on the left side of second base. Drew’s season trend, especially as it pertains to his batting average, was likely a main reason why GM Ben Cherington felt comfortable giving up Iglesias, a defensive wizard:

While Drew’s not even half the fielder that Iglesias is, he has the potential to carry a team for weeks at a time with his bat. Fitting his season trend to a third-degree polynomial (this is not a “random” choice — he has clearly had two critical points over the course of the year), we can see that Drew is heating up as the season turns to August. In the best-case scenario (the one in which Drew continues or surpasses his current surge), he could be hitting .300 by September 1st. In a more realistic scenario, Drew will continue his current hot streak, and then regress to his career average of .264 by the time September rolls around. In any case, the remainder of the season is looking promising for the Red Sox shortstop, which is a good sign for a team that’s in desperate need of production from the position. In the wake of the Peavy deal, my favorite Globe writer Chad Finn had this to say about the brothers: “And yes, I’m kind of chuckling at the thought that the unfairly maligned Stephen Drew is still here while Iglesias has moved on. The Drews, they’re survivors, man.”

*J.D. Drew was drafted by the Phillies second overall in 1997, but failed to sign a contract. He and agent Scott Boras demanded $10 million whereas the Phils were only willing to offer $2.6 million. He played with an independent league team for one year, then was drafted fifth overall by the Cardinals in 1998, signing for $7 million. Phillies fans booed him for the entirety of his career.

Vince D’Andrea is a rising senior at the Massachusetts Institute of Technology. He is an avid Red Sox fan and his blog, Dave Roberts’ Dive, can be found here.

I think one of the most fun parts of baseball is this part of the year; as we wind down, you can start to root for unlikely things to happen. For example, I’m kind of hoping the Pirates manage to lose at an .800+ clip and keep their sub-.500 streak alive. I’d love to see the Royals make the playoffs. Finally, I’d love to see Yasiel Puig win the NL batting title.

The rules of the game are that you have to have 502 plate appearances to win a batting title. If you’re short, you’re given an 0-fer for the rest. So if Puig finished with 492 PAs, he’d take an 0-for-10 for the purposes of the batting title. Right now, Puig is projected by STEAMER to finish the year with 435 PAs. We’ll accept that number for now, but given that number, let’s think about how likely it is that he has a high enough batting average to win the title.

The first step is to figure out the mark he needs. Let’s go with STEAMER again, and we see Michael Cuddyer, Joey Votto, Yadier Molina, and Chris Johnson all projected to finish at about .320. Let’s assume that one of those four players finishes right at his 87.5% projection (the middle of the highest quartile)…I’ll say Joey Votto, who is projected to go .302 for the rest of the year (the highest of the bunch). Using the binomial distribution, there’s a 16.2% chance Votto finishes 51/149 or better given his “true” .302 batting average. We’ll say that that is the target Puig has to reach: Votto (or one of the others) adds something like 51/149 to his current stats, for a .329 batting average.

What are the chances Puig reaches that clip? To keep it simple, let’s assume STEAMER is right on the number of PAs, ABs, and Puig’s true chance of getting a hit, and then figure out Puig’s chance of getting enough hits to finish at .329 or better. He’s going to end the year with 435 PAs and 390 ABs, if he keeps up his current pace. To that, add an 0-for-67 to get him up to 502 PAs. So he needs enough hits to have a .329 batting average in 457 ABs. That number is 150. He currently has 85 hits in 224 ABs, so for the rest of the year he needs 65 hits in 166 ABs.

Given that STEAMER projects a .293 batting average for the rest of the year, it’s pretty unlikely that he’ll hit at a .392 clip. In fact, his chances of doing so are only about 0.4%, using the binomial model.

What could help his chances? First, there’s no guarantee Votto/Johnson/Molina will get hot enough to make the mark .329. If we drop the required average to .320, using the same method as above, he’d only need 146 hits, which raises his chance to about 2.3%.

Another possibility is that he’s a better hitter than STEAMER projects. If he only regresses to .310, which would make him one of the better hitters in the league admittedly, he has about a 1.6% chance of winning the batting title. And if he is truly a .310 hitter, AND none of the other players near the top of the leaderboard stay hot enough to beat .320, Puig has a whopping 6.6% chance of winning the batting title.

Yeah, I know batting average is stupid. And I know this is a minuscule chance. But isn’t it amazing that Puig has a chance to do something like this at all, after making his debut in June? Baseball!

Note: I have no idea if I’m the first to do this, but quite frankly I don’t care.

Today, it was reported that seven-year veteran and noted ump hater* Mark Reynolds was released by the Indians. As an Orioles fan who enjoyed watching Reynolds, this was disheartening for me–I’ve always liked TTO guys, and it’s hard to find a more TTO guy than Reynolds**. However, I was (and am) also a fan of the Orioles, meaning I would want them to win, preferably as often as possible. This means that starting a player with a career WAR of 7.4 (in nearly 4000 plate appearances , no less) probably isn’t the best way to accomplish that goal.

Now, about that WAR…

As of  Thursday, August 8th, 2013 (i.e. the day of his release), Reynolds is 322nd all-time in homers, and has nearly 200–for the record, there are 311 players with 200 dingers, as of the aforementioned date. Anyone who has watched Reynolds knows that he has formidable power, and his stats, at least for his career, reflect that–his .232 career ISO*** would rank 16th in the majors this year. However, that power comes at a price: namely, every other aspect of his game. Like, seriously. Plate discipline, baserunning, fielding, everything. The end result of this is the aforementioned WAR value, which translates to 1.2 WAR per 600 plate appearances; as a point of reference, these scrubs have WAR/600PA numbers of 1.9 and 1.8, respectively.

Now, the main point to get out of this is that Reynolds–a player with nearly 200 career long-balls, considered by the small-minded to be the symbol of all success–has a single-fucking-digit career WAR, when some players are able to get double-digits in a single season. This led me to the question: how many other players, of the 322 with 200 round-trippers, can fit this dubious distinction? This question led me to the answer: three. They are listed below in order of lowest to highest WAR, for your amusement, along with my best guess as to why this person was so shitty.

Jose Guillen–214 career bombs; 4.5 career WAR (.4 per 600 PAs)(!)

Guillen is  remembered for a few things:

1. Pulling a reverse Bedard (i.e. protesting when his manager removes him from the game) and being suspended for the Angels’ 2004 playoff trip; this actually happened during a decent season for him (3.0 WAR), so don’t be too sure he wouldn’t have helped them had he participated.

2. Holding that grudge with him**** for the rest of his career.

3. Being an all-around genial person.

3. His exceptional rookie year, which earned him comparisons to the immortal Neifi Perez, in addition to being, as of last June, the worst season for a right fielder ever.

4. Being, y’know, a generally horrible baseball player.

For all the talk recently of Jesus Montero being terrible despite PED usage, Guillen was pretty bad, and he juiced, too. In terms of career numbers, he had a triple-slash of .270/.321/.440, and a .330 wOBA; while he never really played in a hitter’s ballpark (he had brief stops in Cincinnati and Arizona), he still played in a hitter’s era, meaning his career wRC+ was only 98. His D, however, was what truly set him apart: -56.7 fRAA for his career, and it would’ve been even worse, if not for a ridiculously fluky 2005 (12.5 fRAA, by far the highest of his career). He also wasn’t a particularly good baserunner (-16.5 BsR).

He didn’t strike out nearly as much as Reynolds (17.2% career), but he also didn’t walk nearly as much (5% career), and his ISO was considerably lower (.169).

Dante Bichette–274 career four-baggers; 8.9 career WAR (.8 per 600 PAs)

The career of Bichette was best epitomized by his unfathomable 1999 season; I’ll provide a quick summary. Bichette had a triple-slash of .298/.354/.541 over 659 PAs, which translated to a .376 wOBA. A casual sabermetrician would look at that figure and say, “Well shoot, that’s pretty darn good!”, not knowing that it came while he played for Colorado, in 1999 (i.e. one of only three seasons in MLB history where teams averaged more than 5 runs a game). Thus, after adjusting for park and league effects, Bichette’s wRC+ for that season sat at a mere 100–he was an average hitter. For the sake of comparison, Josh Donaldson has a .372 wOBA for the Athletics this year–and a 139 wRC+. As Mr. Remington points out in the article*****, Bichette in 1999 was one of just two seasons where a hitter had a .370 wOBA or higher and a wRC+ of 100 or lower; the other season was Jeff Cirillo in 2000, playing for–you guessed it–the Rockies.

Focusing on Bichette’s career as a whole, he hit .299/.336/.499, for a .359 wOBA; however, because a lot of that was spent in Colorado, his career wRC+ was a mere 104; this, combined with poor defense (career -92 fRAA) and relatively poor baserunning (career -1.2 BsR), gave him the undesirable WAR seen above.

Bichette’s K% and BB% were somewhat similar to Guillen (15.7% and 5.2%, respectively), meaning they were considerably lower than Reynolds’ numbers; his ISO (.200) was considerably lower than Reynolds, though not as low as Guillen.

Deron Johnson–245 career circuit clouts, 9.7 career WAR (.9 per 600 PA’s)

The only old (i.e. pre-UZR) player who fit the criteria, Johnson was, allegedly, described by Pete Rose as the hardest ball-hitter he had ever seen. It’s too bad he struck out in nearly 20% of his plate appearances (high for the time period, when the average was about 15%).

Johnson only had one 4-win season (4.3 in 1965 for the Reds); in that year, he had a .370 wOBA, albeit with -9 fRAA. Fielding was his main problem (career -63 fRAA); his career triple-slash of .244/.311/.420 comes out to a .326 wOBA and a decent 102 wRC+, and his BsR was only -3.0. His K% and BB% (8.8% and 19.9%, respectively) were higher than the averages for his era, but not to the degree of Reynolds’, though his ISO (.176) was pretty high for the time.

He’s the least spectacular of the bunch, probably because he played back in the 60’s and, therefore, is completely insignificant.

So what was the point of this? To use as many variations of the word “home run” as possible?****** Possibly. To find the closest companions to a favorite player? Possibly. Was this whole thing completely, utterly pointless? Definitely.

————————————————————————————————–

*He actually made some good points in the rant. Here’s the quote that really resounded with me: “…It’s a shame [the umpires] don’t have accountability. They don’t have any, if they make a bad call, it’s like, ‘Ho-hum, next day is coming.’ If we have a bad couple of games we get benched or we get sent down. They have nobody breathing down their throats. They have nobody, they are just secure in their jobs.”

**To be fair, Reynolds acknowledges his approach may not always be the best.

***Reynolds’ and Jose Reyes‘ 2011 seasons are a perfect example of why SLG% is overrated. At the conclusion of the season in question, Reynolds’ SLG% was 10 points higher than Reynolds’ (.493 to .483), despite Reynolds having an ISO a HUNDRED AND SIX points higher (.262 to .156). Now, in the context of this season, was Reynolds a better overall hitter? Certainly not (in case you forgot, this was Reyes’ last year with the Mets, when he had a phenomenal year, leading the league in batting average, etc.). Was Reynolds a better power hitter? Certainly yes. Hmmmmm…not sure if “Certainly yes” is grammatically correct. Whatever.

****The quote from Guillen should really win an award for Worst Butchering of the English Language (particularly the first sentence).

*****In the article, Remington cites Bichette as having a 98 wRC+ in 1999, when on his player page, it lists him as having a 100 wRC+. Have the park or league factors changed since last year?

******I used homers, dingers, long-balls, round-trippers, bombs, four-baggers, and circuit clouts. Thanks to this post for supplying me.

Predictive analysis of baseball statistics is an art, and there are very few well-accepted rules and principles. Even still, common sense dictates that it’s ridiculous to read too much into one performance. So to compare Rubby de la Rosa to an MLB star based on 10 electric fastballs in the 9th inning of a 15-10 Houston shootout would be simply outlandish. But, hey, why not?

The Background

De La Rosa’s pitch speed was touted as his single best attribute when he arrived in Boston as part of the package traded from LA in the Gonzalez-Crawford-Beckett deal. He was coming off Tommy John surgery, but the list of pitchers to match or surpass their pre-surgery velocity upon their return is too long to post. Below is a sampling of stats from De La Rosa’s 2011 campaign (he missed a full season to surgery, except for one brief appearance in 2012:

Rubby (pronounced “Ruby,” as in red) was used primarly as a starter in his rookie season with Los Angeles, and drew comparisons to Pedro Martinez due to his height (5’11”) and also due to his sizzling fastball and wicked changeup. In fact, the Sox hired Pedro as a Special Assistant this spring to work specifically with De La Rosa, and Pedro raved about the 24-year old’s prospects. Clearly, Rubby has the “stuff” to be a top-end starter: the average velocity on his fastball was 95.4 MPH in 2011, which would rank third in the majors this year (behind Matt Harvey and Stephen Strasburg) amongst qualified starters. While De La Rosa has worked as a starter with Pawtucket in 2013, the organization has made it clear to manager John Farrell that he can use De La Rosa with the big-league club in whichever bullpen capacity is necessary to win.

The Performance

While there were many noteworthy aspects in Tuesday’s outing, Rubby impressed me most with the command he showed with his fastball while managing to maintain his velocity. De La Rosa threw all of his pitches — fastball, changeup and slider — and racked up strikeouts on his slider and fastball. His ability to get ahead in the count allowed him to vary the speed of his pitches over the course of his outing on nearly ever pitch:

The ability to stay in a pitcher’s count makes his pitch selection more unpredictable for the batter, allowing him to capitalize on the exceptionally low 63.9% contact percentage he generates when he throws his changeup. Also, his fastball was simply electric in his Sox debut: he managed 2 swinging strikes on the pitch that he threw, on average, at 98.17 MPH. If he managed to keep that velocity for the remainder of the year, he would vault directly to the top of the leaderboard for relievers’ average velocity, surpassing Cincinnati’s Ardolis Chapman and Kansas City’s Kelvin Herrera. De La Rosa also warmed in the pen on Sunday afternoon with the Red Sox leading 4-0, but Farrell deemed the situation too “high leverage” to bring him in. Finally, in front of a nearly empty stadium during a 15-10 slugfest, Rubby made the most of his first opportunity to pitch for the Sox.

The Comparison

Those who watched the 2002 Angels-Giants World Series remember an energetic young Venezuelan by the name of Francisco Rodriguez.

Much like Rubby De La Rosa, K-Rod burst onto the scene in the Angels bullpen late in the season; he made his major league debut on September 18th, 2002, which is more than five weeks later in the season than De La Rosa debuted for the Sox in 2013. In 2002, Rodriguez pitched in five games before the playoffs, striking out 13 batters while allowing exactly zero runs. He experienced even greater success for the Angels in the playoffs, where he struck out a whopping 28 batters over 11 games while posting a 1.93 ERA. In doing so, he cemented himself as one of the key pieces helping Anaheim to a World Series title. While PITCHf/x data is not available from 2002, K-Rod’s bread and butter consisted of his sizzling fastball coupled with a biting slider. It’s a slightly different arsenal than De La Rosa’s (Rubby’s might be even deeper due to his advanced changeup), but both were clearly gifted with elite power “stuff” as emerging young pitchers.

For those who are wary about how De La Rosa’s arsenal and approach will translate to a late-inning relief role from the starting niche he’s held all year in AAA, consider the following: K-Rod was a struggling starter for Angels single-A affiliate Rancho Cucamonga in 2001 (the year before his debut), posting a 5.38 ERA and an 11.6 K/9 (while his major league rate over his first three years was 14.59 K/9). In a similar career trajectory to K-Rod, Rubby De La Rosa has yet to truly embrace his potential at Pawtucket in a starting role. Perhaps the transition into a late-inning role is just what he needs — and just what the Red Sox bullpen needs — to become the elite pitcher his “stuff” dictates he should be. So, in a year where the Red Sox are unexpectedly contending for a title, taking a chance on a pitcher like De La Rosa might just be the wild card that pushes them over the edge — hey, it worked for the Angels.

The Risks

There are a number of risks for both the Sox bullpen and De La Rosa’s development if they decide to convert him to a late-innings reliever. As noted above, one spectacular performance in one game is a small sample size, and De La Rosa can be erratic with his command, especially with his fastball. The last thing a pitcher wants to do in a strikeout situation is to walk a man, particularly when Rubby’s HR/9 rate has not been ideal in Pawtucket (1.06). But the Sox have holes to fill in their injury-depleted bullpen, and you have to think that De La Rosa can fill in better than Pedro Beato or Jose De La Torre due to is elite arsenal of strikeout weapons.

Finally, there are a couple of risks the Sox must consider as they pertain to Rubby’s development as a pitcher. There is a slight bit of concern about re-injuring his surgically-repaired elbow if he slots in during late-inning situations. There is more strain on the arm as a bullpen piece than as a starter because the pitcher throws so much harder over a much shorter period of time in the ‘pen. If the Red Sox truly view De La Rosa as the “next great Pedro”, they’d be kicking themselves if they took the risk of putting him in the bullpen only to see him blow out his elbow again. But, when contending for a title in Boston, sometimes the “now” must precede the “future” in calculated situations. Putting De La Rosa in the ‘pen may be one such risky decision.

Also, if Rubby experiences any sort of failure in a high-leverage situation, it could emotionally ruin the great prospect (think Richie Sexson’s grand slam in Cla Meredith’s forced MLB debut). One must remember, however, that this is not Rubby’s first rodeo: his debut came in 2011 with the Dodgers as a 22-year old and he’s shown a great deal of resiliency already to recover from Tommy John surgery. If I’m manager John Farrell, I consider De La Rosa ready for the limelight right now. I take a chance and stick him in some pressure situations to see if I can’t make lightning strike twice: the 2013 Red Sox version of vintage K-Rod could be the last piece to put Boston over the edge in their contention for the 2013 World Series Championship.

Jeff Locke and Rick Porcello are two pitchers with large gaps between their xFIP and ERA. How you value them depends largely on your faith in defense-independent pitching theory. Porcello sports a 3.27 xFIP but a 4.28 ERA. While his ERA- is a pedestrian 105, his xFIP- is an excellent 82. Porcello ranks 42nd among qualified pitchers in FIP WAR at 2.1 while his RA9 WAR ranks 57th at 1.5. Locke on the other hand has posted an unsightly 4.09 xFIP but a sparkling 2.47 ERA. His ERA- is a sterling 68 while his FIP- is 101. Based on FIP WAR, Locke ranks 58th at 1.4 while RA9 WAR puts him at 13th with 3.9. RA9 or “actual run prevention” says Locke is a real ace, the 5th best pitcher in his league, and Porcello is a slightly below average pitcher. xFIP says Porcello is an excellent pitcher, while Locke is merely a middling arm.

In order to understand the difference between Porcello and Locke, I dug deeper into their peripheral stats. Both have similar strikeout rates, with Locke at 18.1% and Porcello, who does not have the luxury of facing his own kind, at 17.8%. While Porcello has a 5.1% walk rate, Locke’s 11.3% is well above the MLB average of 8.0%. Porcello has been victimized by the long ball, as his 13.5% HR/FB rate is the highest since his rookie year, and two full points above his career average of 11.5%. On the other hand, Locke has managed to suppress home runs, as he has posted a 6.8% HR/FB rate. Some of this can be attributed to their respective home fields, as Comerica has a home run factor of 101, while PNC Park’s home run factor of 92 makes it the 3rd most difficult park to hit a home run. I would be wary of attributing any home run avoidance skills to Locke, as he allowed 9 home runs in 51 innings with the Pirates over 2011-12. ZiPs has him projected for a 9.9% HR/FB rate over the remainder of the season. Locke has also enjoyed an excellent LOB%, as his 82.2% is currently 5th in the majors among qualified starters while Porcello’s 69.5% is 74th. MLB average LOB% is 73.3. While Locke’s LOB% seems destined for regression (ZiPS projects it to be 69.0% ROS), a below-average LOB% may be part of Porcello’s profile, as his 69.5% is actually a career-best number.

However, the biggest reason for the ERA separation between Porcello and Locke is the defense behind them. Both Porcello and Locke are groundball pitchers, and their higher than average contact rates make them heavily dependent on their fielders. Porcello’s GB% of 57.2 is 2nd highest in the MLB, while Locke’s 53.3% is 8th highest. The Tigers have a team BABIP% against of .300 which ranks 6th highest in the MLB, while the Pirates are 2nd lowest at .271. Porcello’s BABIP of .313 is 13th highest among qualified starting pitchers, while Locke’s .261 is 75th. The following hand-picked GIFs illustrate the difference.

Porcello works with this:

  (muckracker)

(He doesn’t actually but I imagine the Tigers’ ballboy was inspired by their defense)

And Locke has this:

 (From Forbes to Federal)

The difference in their defenses has contributed to the Tigers’ pitchers underachieving their xFIP, and the Pirates beating their xFIP. While the Tigers pitching staff has a league-best 3.38 xFIP, their team ERA is 6th-best at 3.57.  The Pirates have the 5th-best xFIP at 3.67, but a team ERA of 3.09 that leads the league by a wide margin, with the Braves next at 3.24. Put in other terms, the Tigers ERA is 106% of their team xFIP, while the Pirates ERA is 84% of their team ERA. Rick Porcello’s ERA is 131% of his xFIP, while Jeff Locke’s ERA is 60% of his xFIP.

After an analysis of the Locke and Porcello’s defense-independent stats and their defense-dependent stats, I thought it would be interesting to see what combining the best and worst of both worlds would be. The following chart is Porcello’s actual ERA and then his ERA calculated by multiplying his xFIP by the “Pirates Factor.”

And this chart shows Locke’s actual ERA and then his ERA calculated by multiplying his xFIP by the “Tigers Factor.”

I know, it’s a back-of-the-napkin calculation. xFIP doesn’t adjust for park and league factors, and Porcello’s LOB% probably wouldn’t jump to the Pirates’ team average of 77.1%.  Nevertheless,  its an interesting example of the difference that defense, park, league, and luck factors can have on a pitcher’s ERA over the course of a season. If Porcello pitched for the Pirates, he would probably be widely recognized as a very good pitcher, while if Locke pitched for the Tigers, he would most likely look average or worse. A change of scenery could have a big impact on either pitcher. But hey, who knows, maybe the recent acquisition of this guy can help Porcello look a little better.