In his first plate appearance he knocked a two run double that short hopped the deepest part of the ballpark on his way to a three hit, four RBI major league debut.  He registered Division, Championship, and World Series starts during his rookie season.  He has a career 3.16 ERA after his sophomore season, a talent for spinning various household objects on his finger, and his grandfather is a baseball meme.  Of course I am talking about Steven Matz, the 25 year old Metropolitan South Paw.

A few weeks ago I claimed Steven Matz ranked 7th among the top starting pitchers using xStats (xOBA, VH%, scFIP, etc).  This may have been a little controversial to some, and I know it brought a smile on a few others.  While that ranking was, more or less, algorithmic, I do stand by the assessment of Matz.  He is good.  He is very good.  He may be one of the most underrated starters right now, and that needs to change.

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Statcast has afforded us many new ways of examining well struck batted balls. We’ve been given quantifiable evidence that Giancarlo Stanton hits the ball harder than anyone else in the game, for instance. That is a neat trivium to exhale after witnessing one of his line drives, but it isn’t particularly helpful for analysis. Factoring in the vertical launch angle certainly gets us much closer to valuable information. We have statistics such as ‘Barrels’, which display the league average values for batted balls based upon those with similar exit velocity and vertical launch angle. However, this two dimensional approach fails to fully explain the three dimensionality of the game we love.

Balls hit to center field are significantly different, on a qualitative level, than those hit down the line. For starters, the fences are deeper in center field and more shallow down the lines. Additionally, balls hit down the line will have a different spin profile than those hit to center field. They may spin at a different rate, and in a different direction, causing the ball to slice or hook, or draw or fade if the effect isn’t as severe. Furthermore, once a ball has sufficiently sliced or hooked, it will begin to lose the benefit of the lift bestowed by its backspin, and as a result it will fall ever more quickly out of the air as it travels, limiting the maximum attainable distance.

I’ve sought to find exactly how much home run rates change with horizontal angle when assuming ideal exit velocities and vertical launch angles, which players hit the most balls on these ideal angles, and what their individual success rates look like when compared to league averages. Read the rest of this entry »

Asdrubal Cabrera has had a number of up and down seasons in the past few years, and from my outside perspective it seems to be, at least in some part, related to a significant quadriceps injury he suffered in 2013 (view the video). Cabrera entered the 2013 season as a two time All Star shortstop, and during the first two months he was off to a pretty standard Asdrubal Cabrera type season: above average offense and mediocre defense.  After this injury, from which he missed three weeks of playing time, he languished offensively for more than two entire months.  From June 26th, the day he returned, until September 4th, he produced a miserable .221/.276/.329 line with .267 wOBA and 65 wRC+. From September 6th on, he went back to his more standard .272/.330/.519 with .368 wOBA and 134 wRC+.  With the benefit of hindsight, we can all agree he likely came back from his quad injury too soon. 

The struggles of the 2013 season may have prepared Cabrera for his 2016 campaign, as it turned out to be very similar to 2013 in many ways.  During spring training, Cabrera suffered another quadriceps related injury, this time to his patellar tendon, the bit that connects your kneecap to your lower leg.  This injury served to plague him throughout the season, leading him to the disabled list in early August after suffering what, to me anyway, looked like a potentially serious injury (view the video).  Similar to 2013, Cabrera came back from this injury exceptionally quickly, this time missing only 18 games, but, unlike 2013, this time came back with a fury. And a new hair color.

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It might be hard to imagine now after his 36 big league homers, but just two short years ago everyone questioned how well Jung Ho Kang’s power would translate from the Korean Baseball Organization to Major League Baseball.  Many assumed the power would be substantially reduced, and Kang’s leg kick, and his timing mechanisms along with it, would suffer at the hands of superior pitching.  Well, his rookie campaign last season put those fears to rest pretty quickly, when he hit .287/.355/.461, including 15 HR, over 467 plate appearances. Unfortunately, the season ended prematurely when he suffered a terrible knee injury while attempting to turn a double play.

Kang returned to play on May 6th and immediately returned to the same standards of production for Pirates. He lost a few miles per hour off his average exit velocity, but his average launch angle increased, netting lower BABIP, lower batting average, more fly balls and more home runs. Overall, this turned into a 10 point increase in wOBA. This may have been influenced by luck to some degree, because his xOBA in both seasons are effectively identical, at .347 in 2015 and .345 in 2016.  No matter how you look at it, though, Kang had two months in 2016 that really stand out on the scoresheet: July and August- but before we get to that we’re going to have to talk about what happened in June.

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Sometime between mid June and late July of 2015, something clicked for Daniel Murphy.  He transformed from a career singles hitter into a monster at the plate. He now threatens the defense with elite contact skill, pull power, gap to gap line drives, and an uncanny knack for slap hits.  He’s an all around threat at the plate, capable of out thinking some of the best pitchers in the game, breaking defensive shifts with slap hits, and pulling even great pitches for home runs. Murphy is difficult to pitch to or defend against, and as a result he’s been one of the best hitters in the game for the past year and a half.  This is a remarkable transformation, and very few people could have predicted just how great he has become.

There are a few things you need to know about this guy. For one, he’s a bit weird. I’ve watched just about every game he’s played since his rookie season back in 2008, and I feel like after watching this guy for a few years you see a little bit of everything.  Some of the most bizarre displays I’ve seen on a baseball field have included this guy in some manner or another.  I vividly remember the first defensive play he made in the major leagues, and I’m sure you can guess what happened, judging by his defensive reputation.  He whiffed a routine ground ball, slammed his glove on his knee, and then faked a throw to first base.  Just kidding. You might want that to have been his first play, because it’s fitting, but in reality he made a miracle leaping grab in left field that left most of the fans and broadcasters speechless. Oh, and he turned it into a double play, because of course he would.  Clearly, that sort of defensive play did not become his norm.

Through all of the ups and downs of Murph’s defensive woes, between the miracle spin-o-ramas, throwing to the wrong base, blind behind the back tosses and balls rolling through the wickets. Through everything fans have marveled and endured while watching him play, one thing has remained constant:  his elite ability to put bat to ball.

This is not the story of a player who got lucky or significantly changed his skill set at a relatively advanced stage in his career.  It is very tempting to paint that picture if you only casually watched his performance through the years.  Yes, he used to be a high average, no power guy.  Now he is an even higher average guy with power.  It’s weird.  Daniel Murphy is weird. But this isn’t about a change of skill set, this is about neuroticism. In order to understand his story you need to thoroughly understand his oddities, because they play a big part in his career trajectory. Read the rest of this entry »

Freddie Freeman had the best season of his career in 2016. He set career highs in just about every stat you can name: home runs, extra base hits, slugging, on base percentage, walks, BABIP and strikeouts. All of that sounded pretty great up until those last two, right?  You wouldn’t be alone if you felt that way.  Freeman has always been a good player, I doubt many have felt otherwise. It seems that every year Freeman marches into the season, puts up solid numbers at first base, shows off his leadership skills on and off the field, and then quietly goes into the offseason. This year was different, though. In 2016 Freeman had a true break out season worthy of MVP consideration. He had a substantial increase in performance across the board, in every major statistical category, and yet, there is still question about his ability to repeat this performance in 2017.  All due, in large part, I think, to one little number: BABIP.  

Freeman posted a .370 BABIP in 2016. This is significantly higher than his career averages .344 respectively, but it certainly isn’t unprecedented for a slugger to maintain a BABIP this high in the major leagues. Paul Goldschmidt, for example, has posted a .369 BABIP since 2014.  J.D. Martinez has hovered around the .366 mark as well of that same time frame.  Neither of these guys are horrible comps for Freeman.  Neither are speedsters, we know that much.  Although both are probably faster than Freeman by a decent margin, and I feel comfortable saying both are better power hitters as well.  We know the key to BABIP is hitting the ball around 14-18 degrees vertically, and the harder, the better.  Those sorts of hits will turn into singles pretty frequently, and if you can knock the launch angle up north of 24 degrees every once in awhile, you’ll hit home runs as well.  It’s easier said than done, but, in general, that is how you’re going to achieve consistently high BABIP over multiple seasons. Otherwise you start introducing the concept of luck.  

I have a few tools to examine just how ‘lucky’ Freeman may have been in 2016, though.  xStats examines each batted ball measured by statcast, and determines the league average success rate by comparing it to similarly hit balls (those with similar exit velocity along with vertical and horizontal launch angle).  So, for example, if the ball is hit 105 mph on a 22 degree vertical angle and 22 degree horizontal angle, xStats will compare that batted ball to all those hit between 104-106 mph and 20-25 degrees vertically and 20-25 degrees horizontally; count how many singles, doubles, triples, and homeruns were hit in that group divided by the size of the group; and then adjust these numbers for the running speed of the batter.  So, these numbers should be, theoretically, neutral for both park and fielding effects. Read the rest of this entry »

Twice during the course of the season I highlighted Cameron Rupp for his offensive performance.  In May I brought up a concern about Rupp over performing his talent level, since he had a massive and unsustainable leap in exit velocity, but I questioned exactly how much he would regress.  In 2015 he had a relatively low 89mph average EV, and by the end of May he was hitting north of 96mph.  A month later, in late June, I wrote about him again, by this point his EV had setting to around 92mph, and by mid to late June we had seen enough of Rupp to know the changes were real. He had a different spray chart, heat map, higher exit velocities, much more high quality batted balls, and a huge leap in offensive production.

Lets take a step back, though. Upon the conclusion of the 2015 season, the Phillies management told Rupp he needed to dramatically improve his offensive performance during the 2016 season or he could end up losing his job with the team.  Rupp spent the offseason with a batting instructor he has worked with since childhood, Chris Edelstein, and together they refined his swing and approach.  Their work seemed to pay off noticeably from day one this season, with his April production significantly exceeding his 2015 numbers.  After a weak month of May, he went on a tear in June, July, and August where he put up the best numbers of his career.  His season ended on a low note, with a September so underwhelming that it threatens to wash out the success he had during the heart of the season.Rupp had three scorching hot months, one pretty decent month, and two exceedingly weak months.  He finished the season batting .252/.303/.447, with .321 wOBA, 16 HR, 36 R, and 54 RBI.  Among catchers, he ranked 20th in HR, 18th in R, 13th in RBI, 17th in AVG, 27th in OBP, 8th in SLG, and 36th in strike outs.  This may not be especially exciting, but there are some good signs here. Read the rest of this entry »

Last week I wrote about this season’s top pitchers and batters according to xStats. The top players in each category weren’t especially controversial, Clayton Kershaw, Aroldis Chapman, and Mike Trout respectively for Starting Pitcher, Reliever, and Batter. You could perhaps debate Chapman, maybe you prefer Andrew Miller for instance, but generally these guys are universally regarded as the top in the game. This week I want to look at the most improved players. I am using the same weighted rank I used last week. It isn’t any sort of sophisticated weighting, it is more of a back of the envelope type estimation for how each of the associated stats relate to run scoring. I’m just giving xOBA and VH% 40% of the weight, xSLG, xBACON, and xOBP share the next 40%, and PH%, xAVG, and xBABIP share the remaining 20%. I feel this roughly represents each of their predictive power, relative to one another, but is gut feeling, these rankings are very subjective.

I’ve taken the 15 most improved batters from 2015 with at least 400 PA using according to the ranking I described above. Batters had to have as least 400 PA in both 2015 and 2016 in order to qualify.

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Well, the season is over! This is the second full season of xStats, and they have undergone numerous upgrades over that span. I some of you found them interesting! Perhaps even useful. With this second season under the belt, it feels fitting to throw out a few xStats awards: Best Starting Pitcher, Best Relief Pitcher, and Best Batter. So, without further ado, here we go:

Best Starting Pitcher: Clayton Kershaw.

Not a terribly big surprise. He has the best curve ball in MLB by xOBA, registering only .126 (min 200 thrown). His slider has the 7th highest swinging strike rate, 23.5% (min 200 thrown). You can see all of the pitch stats here.  It will come as no surprise when I say Clayton Kershaw is the best pitcher in baseball, he’s just about the best in every individual category xStats measures. No other pitcher really got anywhere close to his dominance. While Noah Syndergaard and Jose Fernandez got somewhat close to Kershaw scFIP and xOBA respectively, the gap between Kershaw and the second best picture is still impressively wide. There is little more I can say about Kershaw, he needs to get called up to a higher league to face better opponents, MLB is too easy for him. Read the rest of this entry »

It has been well documented that there have been more home runs this seasons compared to the past few years. It is particularly interesting because guys we may not necessarily associate with home runs have received a large bump, while the higher end power hitters haven’t had any noticeable increase. Daniel Murphy, Asdrubal Cabrera, Jose Altuve, and Brad Miller have hit 20-30 homers this year, guys like Robinson Cano and Brian Dozier are getting huge boosts to already good power production, and others like Anthony Rizzo and Manny Machado don’t seem to have any significant change at all.

There are a ton of variables involved here, pretty much everything under the sun could be brought up as an explanation.  You could point to the individuals and claim some players happened to have bad seasons last year, or good seasons this year. Maybe certain guys have corrected flaws in their swing or pitch selection.

Even when accounting for all of that, we’re seeing a real change in production this season, something that goes beyond small blips or statistical noise. Many researchers have shown, using various methods, that exit velocity has gone up this season. I’m sure you’ve already read the arguments, and if you haven’t here is a link. I’m more interested in why certain players may be benefiting while others are not. So, yes, on the aggregate, we know exit velocity is up, but how is it affecting batted ball distance, and are the changes helping some sorts of players more than others? Read the rest of this entry »