I feel like every year we’re out here saying Travis d’Arnaud has had a lost season. He has injured a different part of his body each time, too.  That is probably the most gut wrenching part.  This isn’t a guy who suffered some chronic issue, like a bad back or a bum knee.  Instead, he suffered a broken wrist from a hit by pitch, and a broken foot from a foul ball, and a hyper extended elbow from a collision at the plate.  Every year it is something different.  In 2016, he had four problems:

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Over the past few weeks I have been writing about xStats outliers, and to date I have covered Gary Sanchez, Trea Turner, and Jay Bruce. You may think Jay Bruce is the odd man out on that short list, but all three of these guys have big question marks around their power potential for different reasons, and you can read the three pieces for more information.  Today I want to focus on Trevor Story.

Trevor Story became a national sensation after he hit 7 home runs in his first 28 plate appearances, then hit 7 more over the course of the next few weeks.  Two months into his rookie season and the guy had 14 home runs, only nine shortstops hit more than 14 home runs through the whole of the 2015 season, three of whom had 15. His power persisted through the warm mid summer months, where he hit five home runs in June and eight more in July prior to suffering a season ending thumb injury on August 2nd.

Trevor Story hit 27 home runs, slugged .567, had a .272 batting average over the course of 415 plate appearances last season.  His power numbers have him ranked as the seventh best short stop – eighth if you count Trea Turner- and his ADP appears to have stabilized somewhere between 30 and 34.  Of course, you may ask, is this power sustainable? Read the rest of this entry »

In baseball, the best players rise to the top through consistency of talent. As a result, it is only natural for players, managers, and fans alike to assume a player will produce at roughly career averages year after year. Obviously this cannot last forever, and father time will eventually have his final say. Today, I’m looking at three players on the back end of their careers; Jose Bautista, Edwin Encarnacion, and Adrian Beltre. I’m going to look at their combinations of exit velocity and launch angles and see if there are any clear warning signs for these players going into spring training. Read the rest of this entry »

xStats seems to excel at identifying changes in small sample sizes, which might make it ideal in season tool for fantasy players, since it can rapidly adapt to a player’s changing profile. When you start looking at players with larger samples, other projection systems like Steamer or ZiPS exceed the predictive value of xStats. This is a weakness I hope to address in the future, through a combination of more data and refined algorithms. In the meantime, projecting players with little major league experience is a valuable trait. In the past few weeks I have written articles about Trea Turner and Gary Sanchez. Sanchez is particularly interesting due to his ridiculously over the top power numbers, and I think the method I came up for adapting his batted ball numbers to a more realistic projection is reasonable (feel free to tell me if you disagree). This week I’m casting a wider net and looking at a larger group of young players.

For the purposes here, I’m looking at players under the age of 26 who have at least 300 plate appearances in my records (and my records doesn’t necessarily line up with MLB records, due to various measurement and reporting errors). This isn’t an exhaustive list, moreso focusing on players who likely have some fantasy value. Read the rest of this entry »

We have been blessed with many outstanding rookie seasons throughout the history of baseball, especially in recent decades. Ichiro Suzuki crossed the Pacific and instantly turned into a super star. Mike Trout, well, he did Mike Trout things. We’ve seen Mike Piazza, Britt Burns, and Troy Tulowitzki all put up 7 WAR rookie campaigns. Each of these stories are amazing in their own right, but they are all about guys with truly phenomenal rookie seasons. Emphasis on season. Gary Sanchez, well, he was just a little bit different.

Gary Sanchez put up similar power numbers to a lot of those guys I just mentioned, he hit 20 home runs and 12 doubles, not too shabby for a rookie.  That isn’t the story here, of course.  No, he did this all in less than half a season, 229 plate appearances.  Closer to a third of a season, really, and in that time he put up over 3 WAR and made a strong case for the league ROY (and MVP, which lead to many silly arguments).

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Jay Bruce has become a bit of conundrum for the Mets and their almost ludicrously deep corner outfield depth. They have Curtis Granderson, Michael Conforto, and Jay Bruce as their starting right fielders, plus Cespedes patrolling left field. Juan Lagares is their lone center fielder, although he’s going to have to wait in line for playing time. Oh, and Brandon Nimmo is waiting on the wings down in AAA.  Of these, Granderson, Conforto, Bruce, and Nimmo are left handed batters, so we’re talking about four left handed corner outfielders. Whether you wish to consider Lagares a starting center fielder or not is a bit irrelevant here, because one of the corner outfielders will, probably, move to center.  Granderson, most likely, perhaps Conforto on occasion.

The Mets took on Bruce’s 13 million dollar option early in the offseason with the clear intent to trade him. Some may claim the Mets held onto him as insurance in case the Mets lost Cespedes to free agency, but that doesn’t appear to hold much water. Without Cespedes, their starting outfield would be Conforto in left, Granderson in center, and Bruce in right.  Three left handed corner outfielders patrolling the outfield.  Granted, the Mets have some flexibility in the infield, since both Walker and Cabrera are switch hitters, but David Wright would be the only dedicated right handed batter in the lineup, an untenable position.  It appears trading Bruce was a focus this off season, which has not gone well and the team has now settled on tentatively naming him the starting right fielder.

Much has been written about the various factors limiting Bruce’s value on the market, ranging from his weak defensive skill to the host of alternatives on the market. I’m not going to get into either of those topics, instead I want to delve into the offensive merit of Jay Bruce, and the various changes to his batted ball profiles over the span of his career. Read the rest of this entry »

Projecting players, especially younger players coming off short rookie campaigns is a difficult endeavor, and there are many different systems out there you probably already turn to for advice and perhaps encouragement. You have Steam, ZIPs, PECOTA, Marcel, etc. Today I’d like to consider the relative value of Statcast and by extension xStats as a potentially worthy companion in your quest to evaluate young talent in the league. To be clear, I’m not trying to say xStats is on the level of those other systems, because it isn’t.  The real projection systems are much more sophisticated and created by much more intelligent people, xStats is only meant to offer a different lens through which you may look at different aspects of the game and hopefully lead you to asking a few questions you may not have otherwise asked. Please don’t take this too seriously! Read the rest of this entry »

A few weeks ago I delved into the ideal launch angle and exit velocities for home runs, and I discovered balls hit between 21 and 36 degrees vertically and equal to or greater than 96 mph have wound up as home runs nearly half of the time (46.9% to be exact). This was initially somewhat surprising, this seems like a pretty large range of values, but after reflection it seems to check out. When you hit the ball 96 mph in a general upwards sort of trajectory, you’re giving it a ride.

I have spent the past few days playing around with this data to see if it can highlight any more players who may be trending upward or downward with these sort of ideally hit balls, and I have created a few very simple metrics along the way, all of which will be in an attached spreadsheet. You’ll see average exit velocities and batted ball distances for all balls in play along with pushed/pulled splits. I did this again for all batted balls that fit into this ideal launch window, 21-36 degrees and 96+ mph. I have counted how many home runs a player has hit, and how many of those home runs were hit ideally. Finally, I have found the ratio of ideally hit home runs to home runs.

I’m running on the assumption that these ideally hit balls are much less reliant on park and game factors, and instead more representative of a player’s ability to make extraordinary contact on what are, more than likely, pitcher mistakes. Whether this is a true repeatable skill, I don’t know, that is an area to look into. For now, I’m rolling with this assumption, because it might get us somewhere interesting. Read the rest of this entry »

Last week I posted the year to year correlations for xStats and their standard variants, and it came up with a few interesting results.  The xStats variants were much more consistent year to year, for better or worse, and in general they were better at predicting future performance. Not by much in some cases, but hey, every bit helps, right?  It made me curious how it may translate to groups of players with smaller sample sizes, so this week I’ve taken these stats to relief pitchers, with those year on year correlations in mind.  Yes, it is frustrating that we only have two seasons to look at, but this is the best we have at the moment so let’s see where it gets us.

As you might remember, vertical launch angle was very consistent (.75) between 2015 and 2016 for all pitchers, and as it turns out this holds true for every innings limit you can imagine.  Whether you want to talk about guys with 30 innings, 200 innings, or anything in between.  Vertical angle appears to stabilize fairly quickly.  So, that begs the question, how does vertical launch angle change batter performance?  Hopefully this chart will answer your questions.

Between roughly 10 degrees and about 35 degrees batted balls have high value, with batting average peaking around 13 degrees, slugging around 25 degrees, and home runs around 27 degrees.  So, if we know vertical launch angle is stable between seasons, and batted balls between 10 and 35 degrees are bad (for the pitcher), then perhaps aiming for pitchers who have average launch angles outside of that zone would be ideal. Read the rest of this entry »

Earlier this year I made my first attempt at integrating horizontal and vertical launch angle in addition to exit velocity.  As I explained in my first post, I split batted balls into 5 degree by 5 degree launch windows, then split each window into buckets based upon the exit velocity, and in doing so I created an array of buckets that is about 20 units wide, 36 units deep, and 60 units tall. So, in other words, each batted ball could fall into one of 43,000 buckets, give or take. I then found the success rates of each bucket, how many go for singles, doubles, triples, home runs, errors, or outs, and I assigned each ball in the bucket the same probability.

This system has some strengths and quite a few weaknesses.  For its strengths, it is easy to implement and debug, the code runs pretty fast (it can classify about 50k batted balls per second while running on a modest computer), and it gave results that both made sense and outperforming similar stats.  However, this method draws a hard and firm line between potentially similar batted balls merely because one crossed an arbitrary threshold and landed in an adjacent bucket which could have radically different average success rates.  This problem is best expressed visually with a chart for Value Hits. Read the rest of this entry »