After watching Nelson Cruz this year and all the noise he has been making, on top of a recent report by Buster Olney stating, “The average distance of the fly balls pulled by Ryan Braun this season is down 42 feet, from 302 to 260…”, it inspired me to look up the numbers for players suspended in the Biogenesis case. The big four suspended were Alex Rodriguez, Ryan Braun, Nelson Cruz, and Jhonny Peralta. Other position players involved and suspended were Everth Cabrera, Jesus Montero, Francisco Cervelli, and Jordany Valdespin.

This article will focus on the big four with the exception of A-Rod because he has been suspended all season. Obviously enough this is a small sample size so take heed. I will be making a couple of assumptions, the main one being that these players had been using steroids for at least 3 years (2010-2012) prior to their being caught and suspended. The other assumption being that enough time has passed for the effects of the steroids to have worn off and that their bodies/abilities are back to their more natural state.

The main thing that jumps out at you is that Cruz and Peralta are statistically putting up some of the best numbers of their careers (without a doubt, top 3)! Braun, however, is having his worst season of the 4 above, while Peralta and Cruz both are having their most powerful seasons yet. Their HR/FB rates are each at their highest as well as their ISO numbers, while again Braun’s are at his worst of the 4 seasons. Looking at WRC+ and OFF, Peralta is having his 4th best season ever, Cruz is having his 2nd best ever, and Braun is having the worst season of his career to date (with the possible exception of 2008).

Using ESPN’s hittrackeronline.com I looked up each player’s True Distance on home runs this year as well as the average exit speed velocity of their home runs. Ryan Braun has lost 3 mph which has correlated to a shortage of almost 20 feet on his balls. Nelson Cruz has lost about 2 mph and 20 feet off his home run balls from his peak of the four years. Jhonny Peralta, on the other hand, is showing his best numbers this year.

So what does all this mean? In summary, I believe the main thing we can take away from this is that each player who used steroids should be assessed on a case by case basis. Every player is affected differently. We cannot group all steroid users together. Using the above statistics as proof, after being charged in the Biogenesis case, 2 players are having among the best seasons of their careers while another is having his worst. In addition the best all-around athlete and youngest of the 3 (so therefore closest to his prime) is the one who is struggling most, Ryan Braun! Whether it is the HOF vote, or evaluating future value of perceived steroid users, we can’t lump them all into the same group and assume that they will automatically decline. Yes, using steroids is absolutely cheating, however it doesn’t necessarily mean that those players wouldn’t have been just as productive had they chosen legal supplements or nothing at all.

We all know Miguel Cabrera and Mike Trout are elite hitters.  Yes, I am going to compare the two.  And yes, I know that’s been done many times before.  However, I’ve come up with a stat that really separates the two. I’ll be looking at their complete offensive package, so this is not at all related to WAR, as it does not include defense.

Cabrera has won the MVP for the past two years, and Trout is putting up seasons never seen before from 20-22 year olds.  When you compare what they’ve done since 2012, they are very similar hitters. (Stats through Aug. 9, 2014)

Trout: .317/.408/.563 with a 172 wRC+, .247 ISO, .415 wOBA (1860 PA)

Cabrera: .330/.403/.592 with a 167 wRC+, .263 ISO, .420 wOBA (1828 PA)

As you can see, they’re almost identical.  Cabrera has a slight advantage in the power department with a 16 point advantage in ISO and a 29 point advantage in SLG. What I want to do is take this a bit further and analyze how much speed and athleticism gives Mike Trout an advantage.

WAR takes everything a baseball player can do into account.  Trout has had the edge over Cabrera since 2012 with a 26.5 mark compared to Cabrera’s 17.7, a pretty significant gap.  Many people don’t buy into WAR, so I wanted to show how speed changes Trout’s offensive game.  Again, I am not looking at defense for this piece.

As we know, SLG is total bases divided by plate appearances.  However, it does not include every single base a hitter collects.  For example, walks and HBP are not included.  There are many more things that it does not include, and that’s what I looked at in order to create a new stat, adjusted SLG, if you will. I used FanGraphs and Baseball Reference to find every single base an offensive player can collect, whether it’s after they hit the ball or after they reach base. In addition to hits, walks, and HBP, I looked at extra bases taken, reaching on errors, net stolen bases, pickoffs, and double plays grounded into.  I included double plays because they make a huge impact.  It’s two outs on one play, so I took an extra base away for each double play, as it eliminates another base runner.  For extra bases taken, I included five things:

• Times a runner is on first, then reaches third or home on a 1B
• Times a runner is on first, then scores on a 2B
• Times a runner is on second, and scores on a 1B
• Bases taken on fly balls, passed balls, wild pitches, defensive indifference, balks
• Minus outs made at bases (doubled off, trying for double/triple/HR, advancing on fly balls, wild pitch, passed balls)

Other things to keep in mind; I added up every single base, then subtracted a base for when a guy gets picked off or bounces into a double play.  For the final percentage, I took all the bases each player collected and divided it by plate appearances.  It’s a very simple stat, once you gather all the information needed.

Here is a table for what I calculated (ROE—reached on error. NSB—net stolen bases. XBT—extra bases taken.  PO—pickoffs.)

As you can see, the speed of Trout has pushed him way over the top when it comes to being a complete offensive player.  He has reached on an error 15 more times than Cabrera (24-9).  Speed has a lot to do with this by putting pressure on defenders, especially infielders, who often rush throws when a speed guy is running down to first.  Trout also has 76 more net stolen bases than Miggy (82-6) as he has racked up 94 steals since 2012 while being caught just 12 times.  He also grounds into a double play far less than Cabrera, with 19 since 2012 compared to Cabrera’s whopping 63.  Trout also takes more bases while on the base paths.

When you consider that Trout and Cabrera both get hits, extra-base hits, and walks at a fairly similar rate, it’s alarming to see how much Trout goes ahead of Cabrera when you take speed and baserunning into account. Trout’s “adjusted slugging percentage” (or fill in another creative name here) is .747 since 2012, compared to Cabrera’s .673, a very noticeable difference of 74 points.  This percentage, and all of the counting stats that are included with the table, is reliable because they both have almost the same number of PA since 2012, with Trout at 1,860 and Cabrera at 1,828.

Everybody loves to compare Trout and Cabrera.  This is just another way of showing that Trout is ahead of Cabrera, because it shows how well Trout does the things that are smaller and often unnoticed things well.

Jed Hoyer and Theo Epstein have been praised over and over for how well they draft and how they sign pitchers like Scott Feldman and Jason Hammel to one-year contracts and flip them for Jake Arrieta, Addison Russell, and Billy McKinney.  The hype they have created about the Cubs farm system is unimaginable and deserving.  But I’m not here to talk about how great the farm system is, it’s been repeated to us a million times.

Chicago’s 2013-2014 offseason signings were headlined by players like Nate Schierholtz and Emilio Bonifacio (especially after his hot start), but the best free agent pick up came from a minor league contract and has been undervalued by the Cubs fan all season.

I’m here to talk about the Curious Case of Chris Coghlan.

Chris Coghlan was the Rookie of the Year in 2009 when he played for the Marlins.  He put up a .321/.390/.460 line and had a wRC+ on 127.

In 2010 Coghlan became an average hitter putting up a pedestrian line of .268/.335/.383.

His decline continued until he hit rock bottom in 2012 only playing 39 games with the big club and putting up numbers that shouldn’t be uttered.  But just so you don’t have to go look them up yourself: .140/.212/.183.  *He did miss a lot of time due to injury

In 2013 Coghlan put up numbers comparable to his 2010 season and the Cubs front office must have liked the upward trend because they signed the 29-year-old to a minor-league contract that gives them team control until 2017.  This was not an investment but a very low-risk speculation, and right now the Cubs have their second-most productive hitter only making ~$500,000 this year.

Yeah, I said it: Chris Coghlan is the Chicago Cubs’ second-most productive hitter. (Behind Rizzo)  Not Castro, not Baez (yet, needs more PA), not Ruggiano, the only player relatively close was Bonifacio.

Coghlan has put up numbers that are comparable to his Rookie of the Year season:

2009:                                                                                   2014:

BABIP: .365                                                                      BABIP: .333 (2^nd on Cubs)

wRC+: 127                                                                         wRC+: 135 (2^nd on Cubs)

wOBA: .374                                                                       wOBA: .369 (2^nd on Cubs)

Walk Rate: 10.9 %                                                           Walk Rate: 10.6% (2^nd on Cubs)

K Rate: 13.6%                                                                    K Rate: 16.9 % (1^st on Cubs)

Right now Chris Coghlan realizes 35% more value in Runs Created than the average position player.  And although he doesn’t have enough PA to be qualified for the FanGraphs leaderboards, plugging his numbers in would put him in the class of players like Carlos Gomez, Matt Kemp, Melky Cabrera, Ryan Braun,  and Ben Zobrist.

What those players will be making this year followed by their wRC+ and wOBA:

Carlos Gomez: 7 Million, 135, .370

Matt Kemp: 21 Million 133, .358

Melky Cabrera: 8 Million 137, .374

Ryan Braun: 10 Million 129, .362

Ben Zobrist: 7 Million 132, .356

Chris Coghlan: 500k, 135, .369

The Chicago Cubs are paying 500k dollars for the offensive production of Carlos Gomez.  It’s almost scary how similar their numbers are:

Name                    Slash                                      wRC+                    wOBA

Gomez                 .289/.352/.490                   135                         .370

Coghlan                .288/.367/.477                   135                         .369

With the assumed call up of Soler in September, there is one outfield spot left for Coghlan.  And with the development of Almora stunted a little bit in his call-up to AA it seems Coghlan has some more time to prove himself, and also prove he brings value to the Cubs in other ways.

With the army of prospect the Cubs will be calling up these next couple years it would be downright crazy to believe that some players aren’t going to struggle.  I really don’t feel like I have to draw the conclusion for you but I will anyways.  Even if Coghlan’s playing time and numbers decrease next year, the Cubs will have a 30-year-old who has been Rookie of the Year while also having a 30-year-old player who has gone through major slumps and bounced back. Chris is (hopefully) somebody who can be a mentor for the up and coming while still giving value of somewhere between 115-120 wRC+.

For all of the things that Theo and Jed have done for the Cubs, I think I’m right here to argue that the signing of Chris Coghlan has realized the most value of any position player signing they have made.  The Chicago Cubs are paying $500k for Carlos Gomez offensive output, let that sink in.

Maybe the Curios Case of Chris Coghlan is just like The Curious Case of Benjamin Button (but with better alliteration) in the fact that Coghlan is playing younger as he’s getting older.

Coming into the year, the Boston Red Sox were riding high after the 2013 title in which they’d gone from worst to first. Just about everyone with a worthwhile opinion thought that’d they at least be in contention for the playoffs again this year, and it wasn’t uncommon to see people picking them to repeat in 2014.

One of the few questions people did have about the team was how would they integrate their two young players, Jackie Bradley, Jr. and Xander Bogaerts, in their first full seasons as starters. Of these two players, Bradley was the one that people seemed most concerned about. This made sense, since he was less regarded as a prospect than Bogaerts (number 2 overall on most prospect top 100 lists). But while Bradley has been a complete zero with the stick (57 wRC+), his defense has carried him to 1.5 fWAR so far this season. Bogaerts, on the other hand, has a wRC+ of 82, which combined with mediocre defense has left him hovering around replacement level.

Now, there’s no doubt that people are disappointed by Bogaerts’ season, and they have every right to be. Bogaerts was hyped as the rare prospect with superior skills and a significant amount of polish, and he showed why when he played like a veteran down the stretch in last year’s playoffs. Nobody was expecting him to be replicate Mike Trout’s rookie season, but a league average regular was probably a reasonable expectation. Obviously Bogaerts has underperformed relative to that standard.

Guys like Trout, Yasiel Puig and Manny Machado have essentially ruined the kind of expectations we now put on guys going through their first full seasons. Do you know how many batting-title-qualified rookies have had an OPS lower than Bogaerts’ current .650? 311! And of that 311, 283 of them were older than Bogaerts’ current 21 years of age. Bogaerts is struggling, but that’s what rookies do. There’s no greater jump in professional baseball than the one to the majors.

Bogaerts is actually hitting pretty well against fastballs and changeups. The crux of his issues this year have been against breaking balls. And there’s really no way to sugarcoat it. He’s been terrible against any and all spin, hitting just .143 and slugging .167. Unfortunately, opposing pitchers have noticed, and Bogaerts has only seen more breaking balls as the season has progressed.

As the rate of breaking balls has gone up against Bogaerts, his numbers have gone down. The Red Sox shortstop was actually a well above average hitter heading into June (119 wRC+ in March/April, 149 wRC+ in May), but then everything fell apart. Bogaerts posted an almost unthinkable .426 OPS in June, a number less than half (.897) of what he posted the month before. He followed that up with a much improved, but still terrible July (.595 OPS) and continued to struggle in August.

Bogaerts’ struggles with breaking balls coincide with the part of his game that has perhaps regressed the most as his season has progressed: his plate discipline. After working 25 walks through the end of May, Bogaerts has been told to take his base just seven times since. A large part of that has been the decline of his ability to discriminate between a breaking ball thrown for a strike, and one thrown for a ball.

As you can see in the graph above, Bogaerts has stayed fairly steady against fastballs and changeups, but his ability to recognize breaking balls has completely melted away. As for why this has happened, that’s difficult to say. Maybe Bogaerts has always struggled against breaking pitches. But the most likely answer is that he’s a rookie struggling to adjust against pitchers capable of taking advantage of his weaknesses. Nevertheless, it’s at least been a prolonged slump, and one that Red Sox fans have to hope isn’t a glimpse into continual struggles for their youngest player.

Then, putting aside things that we can actually measure, there’s the possibility that Bogaerts is simply in his own head right now. As a ballplayer, he’d probably tell you he’s trying to do too much. There’s certainly something to that side of the argument. It can’t be easy to fail so spectacularly after being hyped as the next face of one of the most prestigious franchises in the game.

There’s also an argument to be made that some responsibility for Bogaerts’ struggles can be set at the feet of his manager, John Ferrell. There have been rumors that Ferrell was the person in the organization pushing the hardest for the Red Sox to resign Drew, which they ultimately did in late May. Drew, who had never played any position but shortstop in his big league career at that time, would be forcing Bogaerts over to third base, the position he played down the stretch of the 2013 title run. Bogaerts expressed some disappointment at time as a result, and an argument can be made that the team’s decision to resign Drew shook his confidence. Before Drew joined the lineup on June 2nd, Bogaerts was batting .296/.389/.427. Since then he’s hit .169/.201/.279. You might say that those dates are arbitrary and coincidental, and you can make of them as you wish. I will say that confidence is a huge part of succeeding in this game, and it should not be overlooked.

Overall, Bogaerts probably won’t look like he belongs back in AA forever, though we may have to wait until 2015 to see the player we were all hoping for. We got that player in the first couple months of this season, but pitchers’ adjustments, along with Bogaerts lack of adjustment to those adjustments, have torpedoed what was initially a very promising rookie year. That said, young players with Bogaerts pedigree and polish often turn into solid players at the very least, and I’m still as excited as ever about his career going forward. He’ll figure it out.

Does Troy Tulowitzki suffer without Carlos Gonzalez in the lineup?

Several weeks ago, in the same way my last article on rookie first and second half splits was inspired, my attention was alerted when a podcast personality contrived that Troy Tulowitzki, before his most recent bout with the injury bug, had performed poorly because Carlos Gonzalez had been out of the lineup.

The pundit grabbed the lowest handing fruit he could find in an effort to create a narrative, and a dogmatic one at that, as to why the Colorado Rockies slugger had not lived up to his pre All-Star break numbers.

******* *******’s (I’d prefer the article to be more about the subject of Tulowitzki and Gonzalez than the podcast member) argument was that without Carlos Gonzalez in the lineup, pitchers could approach Tulowitzki without fear, give him less strikes, and that is why his hitting has declined.

While this pundit surmised that Troy Tulowitzki’s performance declines when Carlos Gonzalez is out of the lineup, the numbers tell a much different story.

While we will look at the more direct numbers in a moment, the idea that Tulowitzki plays worse without Gonzalez is essentially the idea of lineup protection at a micro level. There have been countless instances that have debunked the idea of lineup protection, and, to my knowledge, none that have proved its existence.

The research looked at all games from 2010—Carlos Gonzalez’ first complete season—to today.

The results paint a much lighter picture than the Guernica that ******* ******* painted.

In games where Tulo has played without Cargo, he has had a higher AVG, OBP, OPS, and BB%. One might think that Tulowitzki would continue his normal performance without Carlos Gonzalez in the lineup, but, as this information suggests, it is hard to imagine that Tulo plays better because Carlos Gonzalez is not in the lineup, which leads me to believe what one would normally think about out of the ordinary performances in a small amount of at bats.

The utility of these results should be used for descriptive, and not predictive, purposes. Troy Tulowitzki has only had 479 plate appearances without Carlos Gonzalez, and that is far from a large enough sample size to be deemed reliable.

But because of the recent remarks made by Tulowitzki, it seems like it will be more likely than not that sooner rather than later we will see a large enough of a sample size of Tulo in another uniform to see if this trend continues.

While Tulo has played worse and is hurt as of late, we might expect that it is because he was unlikely to live up to the performance he had in the first half, and not because of Cargo’s presence or lack thereof in the lineup. Over the course of the first half of the season, Tulowitzki’s posted the 15^th best OPS in a half of a season since 2010.

Tulo’s latest play suggests a regression to the mean, and while we are powerless to know exactly why regression happens, some pundits proclaim to know the reason (i.e. Tulo plays worse without Carlos Gonzalez), when really their specious statement is noise with a coat of eloquent words painted upon it.

When the next “expert” tells you that Tulo has preformed poorly, because “ he wants out of Colorado” or  “he wants to be traded”, you’ll know to be more skeptical and not passively agree.

If he gets healthy at some point this season, we should expect Tulowitzki to perform close to his projections in all areas for the rest of the year, and it will be with or without Carlos Gonzalez, not because of him.

When Spring Training rolled around the Yankees had one the better rotations in baseball on paper. CC Sabathia lost weight, Huroki Kuroda was back for another season, Ivan Nova was poised for a breakout and they had two new big additions to the staff. Masahiro Tanaka was fresh off setting records in Japan and signing a massive contract and Michael Pineda was healthy and finally ready to contribute. However, at this point in the season Kuroda is the only one who remains from that highly touted staff. Nova and Sabathia have suffered season ending injuries with Tanaka out since the All-Star break and his rest of season and possibly even 2015 season in question. Pineda is currently on a rehab stint and could rejoin the rotation as soon as Wednesday after missing most of the season to this point with a multitude of injuries.

However, despite all of these injuries Brian Cashman has made a few minor moves and some strategic callups to help build what has become a very successful rotation. Kuroda has still remained part of the rotation with Cashman adding Brandon McCarthy and Chris Capuano and calling up pitchers like Shane Greene and Chase Whitley. David Phelps had also joined the rotation replacing the injured starters yet he himself has also gotten injured and found himself on the disabled list. They also added Esmil Rodgers who in a spot start on Friday pitched well earning himself a win and potentially another start until Pineda returns.

The question remains though although this rotation has been extremely successful to this point can they maintain the success enough to carry the Bronx Bombers to the playoffs? The Yankees currently sit six games out of first in the division while also trailing in the race for the second wild card spot by 1.5 games need to the rotation to pitch well in order to make a run at October.

As of right now the four guys poised to remain in the rotation for the foreseeable future are Kuroda, McCarthy, Capuano, and Greene with the fifth spot likely being Pineda’s when he returns, likely in the next two weeks.

Kuroda has pitched much like the Yankees had expected of him throwing to a 3.97 ERA, which is slightly above his 3.46 career ERA, but it is an anticipated regression for a pitcher in his age 39 season. For his career Kuroda although he has thrown less innings had been a better second half pitcher (3.52 ERA vs 3.39) and this season the trend has continued with Kuroda throwing to a 4.10 ERA in the first half and he has a 3.42 ERA so far in the second half. The Yankees have tried to limit the aging Kuroda’s pitch count and innings so far this season wanted to ensure the right hander was stronger down the stretch run as Kuroda faded in 2013 late in the season. If Kuroda figures to maintain his career splits and pitch better in the second half he should be able to maintain his success to this point in the season and be the pitcher he was expected to be early on in the season.

The two minor trades that Cashman made before the trade deadline are also going to factor into the Yankees postseason chances. Thus far McCarthy and Capuano have been huge for the Yankees pitching to a 2.21 and 2.84 ERA respectably over 9 starts combined and have a combined 5-1 record in those 9 starts. So far over his 36 innings as a Yankee McCarthy is pitching much better than his career averages in K/9, BB/9, and HR/9. He has faced 155 batters as a Yankee meaning only his K rate has stabilized (70 BF). Thus the other two statistics especially his HR rate which is currently at .74 is much improved compared to his career 1.03. The improved HR rate is likely what has caused his vast success to this point, and pitching down the stretch in the power-hitting AL East and in Yankee Stadium, chances are this will regress back to his career averages and McCarthy will once again be a back-of-the-rotation starter, as opposed to the ace he has been for the Yankees so far since the trade.

Although Capuano’s sample size has been smaller than McCarthy’s his success has been similar. According to career averages Capuano is striking out around a half batter more per nine and walking about a half batter less. Those don’t account for the increase in success he’s had. So far in 19 innings in New York Capuano has yet to allow a home run. However, looking back at his time earlier this season with the Red Sox his season HR/9 is at .53 significantly lower than his career 1.20. Unless at the age of 35 and in his 10^th season Capuano has magically figured out the secret to keeping the ball in the ballpark he will likely regress back and beginning pitching more like he has in the past with his ERA moving back into the range of his xFIP which currently sits at 3.35 as a Yankee and 4.07 for his career.

Lastly, that leaves the rookie revelation that has been Shane Greene. As Eno Sarris points out, looking at Greene’s pitch mix gives him a few good comps of successful major-league starting pitchers. However, Greene’s minor league track record did not signal anything similar to this type of success he’s had since being called up. However, there is room for excitement as Greene has posted the lowest K/9 rate since his call up than he did at any point in his minor league career meaning that rate could see an increase. Also, his walk rate seems to be on par with his minor-league record, especially when looking at his numbers over 2013 and the first half of 2014.

Where Greene has succeeded in the big leagues has been with his ability to limit BABIP (.268) and his low HR/9 numbers. Throughout his minor-league career the highest HR/9 Greene posted at any stop was in rookie ball when he posted a .79 rate over 23 innings. Thus far in 37 big league innings Green’s HR/9 has been .72. He has a track record of being very successful at keeping the ball in the ballpark. However, what remains to be seen is if his BABIP comes back down to Earth and his K rate remains low. If he doesn’t retain the ability to strike batters out like he did in the minors and regresses to his minor-league BABIP numbers — only one stop lower than .330 — Greene figures to regress to the below-average pitcher he was in the minors

Over the last month the Yankees’ makeshift rotation has been keeping them alive in the playoff race. However, looking at each member of their rotation, there is reason believe that significant regression is coming with Kuroda being the only one performing near his career averages. Unless each of these arms continues this unprecedented success or Pineda and potentially although unlikely Tanaka return and pick up right where they left off it doesn’t seem like this current Yankee rotation has what it takes to reach the playoffs.

Big-league teams today employ a myriad of data-driven strategies to eek every last drop of value from the players on their rosters. Many of these strategies consist of matching up hitters and pitchers based on their handedness. Between lineup platoons and highly-specialized bullpens, managers today go to great lengths to ensure they’re putting their players in the best possible situation to succeed.

It’s easy to see why. With very few exceptions, Major League hitters hit much better against opposite-handed pitching. In terms of wOBA (vs. opposite-handed – vs. same-handed), lefties perform about .031 better against righties, while righties hit .043 better against lefties. Yet not all platoon splits are created equal. Players like Shin-Soo Choo, David Wright, and Jonny Gomes are notorious for their drastic splits, while others put up comparable numbers no matter who’s on the mound. Ichiro Suzuki and Alex Rodriguez are a couple of the no-platoon-split poster boys.

Ok, so some batters have bigger platoon splits than others, but is there any particular reason for this? Take Choo for example. Is there something inherent to his skill set or approach that causes him to struggle against lefties?

Hoping to find an answer, I ran some regressions in search of attributes that might make a player more likely to have an exaggerated platoon split. I tested all sorts of things out there — from walk rate and swing% to a player’s height and throwing arm — but didn’t come away with much. Aside from a hitter’s handedness, attributes that proved statistically significant included: a hitter’s overall wOBA, his line drive rate, his strikeout rate, and his contact rate on pitches out of the zone, but even those relationships are extremely weak. It takes .100 points on a batter’s wOBA, or a 10% increase in K% or LD%, to move a batter’s platoon split by just .010 points. This tells us something, but not a ton, and at the end of the day, these variables account for a nearly negligible 4% of the variation in hitters’ platoon splits. Here’s the resulting R output. My sample included all batter seasons from 2007-2013 with at least 100 plate appearances against both lefties and righties, excluding switch hitters:

Good hitters or guys who strike out frequently might be a little more prone to having large platoon splits. But for all practical purposes, a player’s ability to hit one type of pitching better than the other seems to be a skill that’s independent of all others. Aside from going by a player’s platoon stats, which can take years to become reliable, there’s little we can do to anticipate which hitters might fare particularly bad against same-handed pitching. And with the exception of players with long track records of unusual platoon splits — like Choo and Ichiro — it’s generally safe to assume that any given hitter’s true-talent platoon split is within shouting distance of the average: .043 for lefties and .031 for righties.

In the off season I wrote about how Manny Machado’s 2013 second-half struggles lied in his inability to select pitches he could hit. Essentially, his innate ability to get bat to ball combined with a poor understanding of knowing which pitches he could drive led to him swinging and making contact on pitches he could not barrel up. This led to an increase in fly balls – especially infield fly balls – which indicate poor contact is being made. Machado was swinging at junk and this caused his batting average and extra base hit production to plummet in the second half of 2013.

Fast forward to now, and Machado has been hitting .301/.340/.494 for the last two months after a cold start coming off of knee surgery. He has a .193 ISO during that time period as well as a 24.3% line drive rate. He certainly has been barreling up the ball for the last two months and has been one of the only Orioles hitters  doing so since the All Star break. Therefore, I wanted to see if Machado has changed his approach in any meaningful way and has learned to be selectively aggressive. Meaning, while he still is never going to be an on base machine, he can still be patient enough to wait on pitches he knows he can hit and hit well rather than making contact on pitches he cannot hit well.

Looking into his basic 2014 plate discipline numbers, interestingly, reveals little to no positive change from 2013. He is swinging more at pitches in the zone and out of the zone. He has an O-Swing% of 32.8%, a Z-Swing% of 68.6% and an overall swing% of 49.9% all of which are two to three percentage points higher than last year. Furthermore, he is making less contact on pitches in and out of the zone. His O-Contact% is 63.5% and his Z-Contact% is 85.4% alongside an overall contact% of 77.9% all of which are three to four points lower than last season. If Manny was swinging and barreling up better pitches to hit his swing rate may be the same, but he should not be swinging at pitches out of the zone more often. Furthermore, his contact rate would be higher especially on pitches in the zone, which it is not. Also, his swinging strike rate is up and his pitches seen in the zone are down. So, if those numbers are not showing why Manny is being more successful to date this year, then either there is another reason or it has simply been luck so far.

A quick look at some other figures tells a slightly different story.  His walk rate is nearly two points higher to date this season and his pitches per plate appearance is up from 3.53 P/PA to 3.68 P/PA. While that may not seem like an astronomical increase, it is significant. Manny had 710 plate appearances last season, if he had this season’s rate of P/PA he would have seen 106.5 more pitches last year. Therefore, his increasing strikeout rate is not surprising simply because he is seeing more pitches. He also is not striking out at an absurdly high rate to begin with, only slightly above 2014 league average. Basically, Machado is seeing more pitches this year than last, and this has led to a higher walk rate and a higher strike out rate.  This, however, does not quite prove the theory of selective aggression that I am purporting.

Using heat maps, this theory can truly be put to the test. Manny may be swinging slightly more and making a little less contact, but what matters here is whether or not he is swinging at good pitches for him to hit, which his recent numbers and line drive rate would suggest he is doing. Below are two heat maps. One is of Manny’s 2013 season swing rates by pitch location, the whole season, and the second one is his 2014 season swing rates by pitch location to date.

Of note, Manny Machado thus far in 2014 has swung significantly less at pitches out of the zone that are down and away, down and in, and up and in.  Also, he has focused on swinging at pitches that are middle in, middle, down, middle up, and even up and away. This allows him to extend his arms and drive the ball, especially the other way. In 2013, Manny focused much more on pitches in the middle of the plate and up and in. The swings at pitches that are up and in especially, and the other problem areas as well, zapped his ability to make solid contact and nosedived his 2013 offensive production.

Next up in this what is turning more and more into a slideshow are contact rate heat maps for 2013 (first picture) and to date in 2014 (second picture).

Manny seemed to make much more contact on pitches inside and outside the strike zone in 2013.  In particular, he made contact at a much higher rate on pitches up and in, down and in, and up and away. These are pitches that Manny simply cannot drive well, which means that if he is making contact with these pitches they are most likely to be outs, which in turn led to his struggles in the second half of 2013.  In 2014 his contact rates are much more concentrated within the strike zone and specifically middle in, down, and up. He is still making lots of contact on pitches too far up and away and down and away, but much lower than he was in 2014. This minimizes the bad contact and allows him to see more pitches that he can make hard contact on.

To bring it all home, below are two more heat maps. These heat maps are Manny’s batting average by pitch location again for the entirety of the 2013 season and the 2014 season to date. Again, the first one will be 2013 and the second one will be 2014.

These heat maps reveal more about how Manny’s approach at the plate has transformed. In 2013, the averages were decently high all around the plate and even out of the zone. However, this is not necessarily a great thing. Manny was swinging at pitches wherever they may be and his average was not great in many of those pitch locations. Fast forward to 2014, and the hitting zones are much more concentrated and with higher batting averages. The section that is middle in Manny is hitting .242 on pitches thrown to that location and is swinging 82% of the time at pitches in that location, tied for highest of any spot on his 2014 swing map.  He is swinging and driving pitches that are middle in, up, and down. He can drive the ball by extending his arms on up and away pitches and he can pull his arms tight to either pull the middle pitches or inside out them to center field or right field. These are the pitch locations that Manny can hit and hit hard and he is swinging more at those pitches than he was in 2013.

The adjustments made to Machado’s plate discipline provide a selective aggression that make him a better batter. As stated before, he is unlikely to become an on base machine. But, Manny has shown that he can hit doubles and home runs. If he maintains a higher average and his selectively aggressive eye at the plate he can continue to be an all star level player for the Orioles. Time will tell how pitchers adjust and how he adjusts, but the developments this year over last provide a great picture into Machado’s ability to adapt and thrive.

This post was originally posted to www.Orioles-Nation.com on 8/8/2014

Many are questioning the thought process behind Ruben Amaro Jr. standing pat at the non-waiver trade deadline.  The Phillies have a lot of veterans under fairly large contracts.  According to Philly.com, when asked about why he didn’t move some of his veterans, Amaro stated

“In this day and age, I think one of the most over-coveted elements of baseball are prospects,” Amaro said. “I don’t know how many prospects that have been dealt over the last several years have really come to bite people in the a**. I think what’s happened is, I think teams are really kind of overvaluing in some regards.”

I thought it would be fun to actually go back and see how many prospects or minor league players who were traded at the deadline panned out.  I went back to 2005 and used every single transaction that involved both an MLB player and a prospect (I considered a prospect a guy who had never been in the MLB, or a guy who had been in the MLB but had yet to achieve rookie status).  I also strictly used trades that were done on July 31, in each year from 2005-2011.  I skipped 2012 and 2013 because it’s harder to get a gauge on whether or not prospects traded will make it or have any success.  Also, from 2011 until now, prospects have had about three years to get to the big leagues and I felt that was a good place to end. 

There were 53 transactions in that time, some very minor, some very major, and some in between. I took each transaction and compiled each player’s WAR after the trade (WARAT).  I still applied this criteria if there was a player who was traded on two different July 31s.  For example, Jake Peavy was traded twice, so his WARAT will be different from one trade to the next.  Some players appear as prospects and MLB guys as well, like Jarrod Saltalamacchia, who was traded as a prospect, and later on once he was not considered a rookie anymore.

I will look at the percentage of prospects that never made it, the percentage that made it but provided negative WAR, and the percentage that made it and provided positive WAR.  I will then look at the MLB guys who were traded and the percentage of guys who provided positive and negative WAR for the remainder of their careers.

The data I found was very interesting.  There were 85 “prospects” traded and 66 MLB guys traded. Below is a table with each trade.  In parenthesis, I noted whether each player was a prospect (P) or an MLB guy at the time.  I will then have their WARAT, or WAR after trade.  If a prospect never made it to the show, I use the abbreviation “NMI.”

 As you can see, some trades worked out better than others.  Of the 85 prospects, 72.9% of them (62) made it to the big leagues.  So, that means 23 prospects, or 27.1% of those traded, never stepped on a big league field.  Of the 62 that made it, 32 were good for positive WAR after the trade, 21 were worth negative WAR, and 9 were at 0 WAR. The WAR of all the prospects that made it adds up to 97.8.  That’s an average of about 1.2 WAR per prospect. 

Now we can analyze the MLB guys. There is a wide variety of age in the group of 66 MLB players.  Some were traded fairly early in their MLB careers; some were traded as their career was winding down.  I found that 69.6% of these players (46) were good for positive WAR after they were traded.  19 players (28.7%) were worth negative WAR, and 1 player was worth zero WAR after the trade. When you add their WAR together, you get 178.8, averaging 2.7 WAR per MLB player traded.

So, on average, teams were trading an MLB guy that would be worth 2.7 WAR for the rest of their career, for a prospect that would turn out to be worth 1.2 WAR in that same time period.

In addition, if you add up the total WARAT for each individual trade, the MLB player’s WARAT was higher than the prospect’s WARAT in 32 of the 53 trades (60.3%).  The prospect’s WARAT was higher in 17 of 53 trades (32%).  Finally, there were three trades that cancelled each other out, and were neutral.

There are many ways to look at this and some things to keep in mind.  It may seem like trading an established big leaguer is not smart from these numbers.  However, it depends on the situation a team is in.  Also, most of these “prospects” have yet to finish their MLB careers, so they are still in the process of racking up WAR. Good examples include Kluber, Masterson, Moss, Murphy, Andrus, Davis, and Feliz. On the other hand, some of the MLB guys were traded when they were still pretty young.  Saltalamacchia, Martinez, Teixeira and Encarnacion are examples, but they are still older than most right now.  These guys are providing most of the WARAT for the MLB guys. Also, some of the MLB guys were so old that they only lasted another couple years in the MLB. 

You have to take money into account as well.  For some trades, teams are not only getting prospects in return, but they’re dumping salary and now have money they could spend elsewhere in the off-season. One example of a trade that worked out really well for one team and not so well for another was the huge Braves-Rangers trade.  The Braves received Mark Teixeira, and traded four prospects that have all turned out well.  Teixeira was great for Atlanta, but was only there for half of 2007 and half of 2008, with the Braves not even advancing to the postseason with him.  The Rangers however, got guys who helped the Rangers reach the World Series in 2010 and 2011.  Be careful with the prospects you trade away.

Since I am relating this article to Ruben Amaro Jr., I will connect this data to the Phillies’ current situation.  The evidence shows it probably would have been smart for them to move their older, more expensive players for prospects, even if they aren’t considered top prospects.  Amaro stated that he doesn’t know how many prospects in past years have come back to bite teams.  Yes, not every prospect is going to pan out.  And yes, some of them could come back to bite.  However, as mentioned before, over 70% of prospects dealt at the deadline from 2005-2011 at least made it to the major leagues.  There is also a good chance that most prospects that make it will contribute positive WAR.  That’s a pretty good turnout. Hamels, Utley, Rollins, Papelbon, Howard, Burnett, and Byrd will all be north of 30 years old next year, with some over 35.  So, they do not have young guys who are already established, like Martinez, Encarnacion, and Teixeira like I talked about earlier.  They are old.  The current Phillies team has proven it’s not going to win, so why wouldn’t they trade off some of their assets, and take a chance on some prospects panning out, while at the same time free up money for future off-seasons? They are not going to win in 2015 or 2016 most likely, so even if their current players still provide positive WAR in the next two years, what’s the point in keeping them around?  Go out and completely reload and blow the roster up.  With the amount of guys they could trade, or could have traded, you’re bound to have some of the prospects you get in return pan out, as the data above suggests.  Stock up the minor league system, and take the hit at the major league level for a couple years.  Add that to the money they will be saving, and they will be well-equipped to contend in three years.

Prospects are not “over-coveted” in baseball.  The problem for Amaro and the Phillies is that they do not have the right people in charge of evaluating and developing prospects.  They have traded for prospects in the past, such as the Pence and Victorino trades in 2012 (not included above) and have not gotten good returns.  So, maybe Ruben Amaro Jr. just isn’t very good at what he does, and wants to believe that giving up major-league veterans for prospects when your team is completely out of it is not a good idea.

Over the last few weeks, I have written a series of posts looking into how a player’s stats, age, and prospect status can be used to predict whether he’ll ever play in the majors. I analyzed hitters in Rookie leagues, Short-Season A, Low-A, High-A, Double-A, and Triple-A using a methodology that I named KATOH (after Yankees prospect Gosuke Katoh), which consists of running a probit regression analysis. In a nutshell, a probit regression tells us how a variety of inputs can predict the probability of an event that has two possible outcomes — such as whether or not a player will make it to the majors. While KATOH technically predicts the likelihood that a player will reach the majors, I’d argue it can also serve as a decent proxy for major league success. If something makes a player more likely to make the majors, there’s a good chance it also makes him more likely to succeed there.

After receiving a few requests, I decided to apply the model to players of years past. In what follows, I dive into what KATOH would have said about recent top prospects, look at the highest KATOH scores of the last 20 years, and highlight some instances where KATOH missed the boat on a prospect. If you’re feeling really ambitious, here’s a giant google doc of KATOH scores for all 40,051 player seasons since 1995 ( minimum 100 plate appearances in a short-season league or 200 in full-season ball).

Before I delve into the parade of lists, I want to point out one disclaimer to what I’m doing here. KATOH was derived from the performances of historical players, so applying the model to those same players might make it look a little better than it is. Take a player like Jason Stokes for example. Although he was a very well-regarded prospect in the early 2000’s (#15 and #51 per Baseball America in 2003 and 2004), KATOH consistently gave him probabilities in the 70’s and 80’s. But part of that is likely because Stokes’ data points were incorporated into the model. If I had created KATOH in 2005, Stokes’ MLB% may have been a few percentage points higher. Even so, a few data points generally aren’t enough to substantially change a model that incorporates thousands. In other words, it’s probably safe to assume that a player’s MLB% using today’s KATOH is roughly in line with what he would have received at the time.

Now, onto the results. Here’s what KATOH thought about some of the most recent top 100 prospects:

2013 Top 100 Prospects

2012 Top 100 Prospects

2011 Top 100 Prospects

Next, lets take a look at some of the highest KATOH scores of all time, namely those who received a score of at least 99.9%. There aren’t any complete busts among these players, as virtually all of them went on to play in the majors.

All-Time Top KATOH Scores

All of the players who registered a KATOH score of at least 99.9% did so while playing in either Double- or Triple-A. This isn’t all that surprising since these are the levels closest to the big leagues. But what about the lower levels? Like we saw in Double- and Triple-A, there weren’t any complete busts among the highest ranking hitters from full-season A-ball. For both full-season leagues, each of the 20 top ranked players has either made it to the majors, or in the case of Carlos Correa, is young enough to still has an excellent chance to do so. But on the bottom two rungs on the minor league ladder, we come across a few instances where KATOH whiffed, most notably in Garrett Guzman (74%), Richard Stuart (72%), and Pat Manning (72%).

Top KATOH Scores for Seasons in High-A

Top KATOH Scores for Seasons in Low-A

Top KATOH Scores for Seasons in Short-Season A

Top KATOH Scores for Seasons in Rookie ball

Now for KATOH’s biggest whiffs. Looking at seasons prior to 2011, the following players had very high KATOH ratings, but never made it to baseball’s highest level. The biggest miss was Cesar King, a defensive-minded catcher from the Rangers organization. Though to KATOH’s credit, King did spend five days on the Kansas City Royals’ roster in 2001 without getting into a game. Following King are a couple of busted Yankees prospects in Jackson Melian and Eric Duncan. Not to make excuses for KATOH, but these guys’ high scores may have had something to do with the way the Yankees over-hyped their prospects back then. If those two weren’t on Baseball America’s top 100 list, KATOH would have pegged them in the 70’s, rather than in the high-90’s.

KATOH’s Biggest Misses

And here are the major leaguers who KATOH deemed least likely to make it when they were in the minors. Its worth noting that a couple of them — Jorge Sosa and Jason Roach — made it as pitchers.

Worst KATOH Scores Who Made it to the Majors

KATOH’s far from perfect, but overall, I think it does a pretty decent job of forecasting which players will make it to the majors. That being said, it’s still a work in progress, and I have a few ideas rolling around in my head to improve on the model. Furthermore, I’m working to develop something that will forecast how a minor leaguer will perform upon reaching the majors, to complement his MLB%. I’ll be dropping these new and improved KATOH projections (for both hitters and pitchers) after this year’s World Series, when we’ll all be desperate for something baseball-related to get us through the winter.

Statistics courtesy of FanGraphs, Baseball-Reference, and The Baseball Cube; Pre-season prospect lists courtesy of Baseball America.