Some Hitters to Start Worrying About

(Note: The 2014 numbers below do not include yesterday’s performances.)

It’s still April, and the sample sizes are still small, so it’s important not to overreact to early season performances, both positive and negative. Still, we have passed the eighth pole, and it’s not too early to peel back a layer or two of batted-ball data and identify a few players whose early season slumps may be about to cross the line toward becoming somewhat significant trends possibly indicative of a change in true talent level.

A search for poor offensive performers should begin at or near the bottom of the wOBA rankings, but a number of those guys reside there due largely to unusually low line drive rates that are likely to regress at least somewhat as the season continues to unfold. Other players are off to slow starts because they have been looked upon unkindly by the BABIP gods in the early going. We’re not focusing on those guys – we’re looking for players with poor fundamentals, whose batted-ball profiles, K or BB rates, or some combination thereof suggestion potentially significant issues that need to be addressed. Here are a few guys in both leagues that you just might want to start worrying about.

Brett Lawrie – Lawrie is currently sitting next to last in the AL in wOBA (.223), with an incredibly low line drive rate (5.2%) that ranks last among qualifiers in both leagues. He has managed to combine that extremely low liner rate with an extremely high IFFB% of 24.0%, tied for sixth highest in the AL. It’s been a dizzying plunge for Lawrie after his brilliant .293-.373-.580 debut in 2011. After hitting nine homers in 150 at-bats in 2011, he hit just 22 in 978 at-bats over the next two seasons. What happened to his plate appearance outcome frequency percentile ranks over that time?

2012 37 27 46 19 18 84
2013 33 34 54 15 41 80

The six major plate appearance outcome frequencies are expressed in percentile rank form above. Lawrie’s main issue in 2012-13 was a fairly extreme ground ball tendency (84 and 80 percentile ranks). This had not been the case in his 2011 debut, which is not listed above due to the small sample size. That year, Lawrie racked up fly balls at a rate that would have netted him a 90+ percentile rank over a full season. His hard fly ball rate plunged, his weak ground ball rate surged, and his overall average batted ball authority and exit angle both declined sharply. The good news – Lawrie is hitting the ball in the air more than in the past two seasons. The bad – his K and BB rates are still not good enough to accommodate a mediocre batted-ball profile that has too much going on at the extreme high (popups) and low (ground ball) ends of the spectrum.

Raul Ibanez – This is what the end of a career looks like. In 2013, Ibanez sold out on all levels to harvest every last kernel of pull power production possible – a look at his plate appearance outcome frequency percentile ranks below show that he struck out and popped up at rates well beyond career norms to create the fly balls necessary to do so. What is not seen below is his extreme pull tendency, which created a massive hole on the outer half of the plate to be exploited by pitchers.

2008 50 57 68 59 59 32
2009 82 63 41 77 11 53
2010 56 74 39 51 43 58
2011 60 20 53 48 17 66
2012 35 53 82 39 49 46
2013 89 59 93 89 44 3

So far in 2014, Ibanez has a .237 wOBA despite a 23.1% HR/FB rate. He is struggling to hit the ball in the air with any degree of consistency – his ground ball percentage of 56.8% ranks 9th among AL qualifiers, and is way out of whack with recent career norms. Toss in his typically poor K and BB rates, and it’s a bad scene. Ibanez wrung out every last bit of remaining offensive usefulness in the first half of 2013, and left behind a legacy of overly aggressive pull-happiness to the young players he was brought in to mentor in Seattle.

Billy Butler – Here’s an interesting one. Let’s jump right into his plate appearance outcome frequency data, a very interesting snapshot of a unique offensive portfolio.

2008 24 33 25 57 8 84
2009 44 50 18 46 51 74
2010 15 71 23 26 63 76
2011 33 72 17 61 53 60
2012 39 47 13 31 73 75
2013 33 90 23 9 57 89

Butler rode a strong K/BB ratio and a consistently high line drive rate (above average in each of the last five seasons) to a productive run in Kansas City despite a steady decline in his fly ball rate and a corresponding steady increase in his ground ball rate. As long as he was crushing a solid percentage of the relatively few fly balls he hit, he remained very productive. This ended in 2013, however, when his hard fly ball rate plunged, and he became roughly a league average hitter on fly balls. This is a no-no for a plodding ground-ball hitter with no complementary skills. Only Derek Jeter and Elvis Andrus have hit fewer fly balls among AL qualifiers, and they have slightly different skill sets than Butler, to put it mildly. This may be a harbinger of the premature decline phase often faced by a relatively unathletic, bat-only player.

Abraham Almonte – This one is all about strikeout and walk rates. Especially strikeout rates. Entering Wednesday’s play, Almonte was tied with Justin Upton for the MLB strikeout lead with 31, and his 34.4% K rate ranked behind only Chris Carter and Colby Rasmus in the AL and Mark Reynolds, Upton and Ian Desmond in the NL. The obvious difference between those guys and Almonte is the superior power possessed by the others. They trade contact for power, with varying degrees of success. Almonte’s batted-ball mix to date is fairly ordinary, with no red flags, but no real upside either. There simply isn’t enough contact, or enough power to justify this level of contact. This hasn’t stopped him from playing every inning of every game to date, with 100% of his plate appearances out of the leadoff slot. If this is allowed to continue, records will be broken, and I don’t mean that in a positive way.

Allen Craig – Craig has basically been the NL version of Billy Butler to date. Here are his plate appearance outcome frequency percentile ranks for his first two seasons as a regular.

2012 45 37 41 83 16 50
2013 53 39 20 36 97 49

Low K and popup rates for an authoritative hitter, a massive liner rate in 2013, and a fairly neutral fly ball/ground ball tendency. That hasn’t been the case thus far in 2014 – Craig’s 66.1% grounder rate is third in the NL behind Jean Segura (see below) and Ben Revere, and let’s just say that Craig can’t quite run with those two. His September 2013 foot injury may be a factor here, as may his position switch from first base to the outfield. Feet are a big deal for hitters, especially power guys, and feet take a greater pounding in the outfield than at first base. If Allen Craig can’t use his lower half to elevate the baseball, goodbye power numbers, at least temporarily.

– Jean Segura – Segura has had a terrible batted-ball profile since his arrival in the majors, and 2014 has been no different – his 75.0% ground ball rate ranks first in MLB, and isn’t that far out of whack with his 2013 plate appearance outcome frequency percentile ranks.

2013 20 7 26 4 24 96

Segura rarely hits the ball hard, even on the ground, and his line drive rates have consistently been quite low throughout his brief major league career. He does have a couple of significant factors working in his favor, however – his low-K, low-popup combo means that he gives away very few free outs, and his top-of-the-charts speed allows him to outperform his expected production on batted balls by a substantial margin. In 2013, Segura posted an actual .276-.286 line on ground balls, as opposed to an expected .206-.216 line based on speed/angle off of the bat. That’s 73% more production than expected on grounders. He also outperforms expected production on liners and fly balls, largely because of his ability to stretch singles into doubles and doubles into triples. That’s the good news. The bad news is that this speed premium will decline over time, and the strength he is likely to add over time won’t do him much good if he is unable to hit the ball in the air with any degree of consistency. Also worrisome is his ongoing inability or unwillingness to draw a walk. Very quietly, Segura has been a near replacement-level offensive player over his last few hundred at-bats, and needs to make some adjustments.

Kolten Wong – Another worrisome combination here. Wong too struggles to get the ball into the air – his 64.8% grounder rate ranks 4th in the NL, but the ball too often stays in the infield when he does elevate it, as evidenced by his 25.0% IFFB%, which is tied or 2nd highest among NL qualifiers. Wong’s offensive game lacked bells and whistles, even in the minors – he has always relied on minimizing negative events, like K’s and popups, rather than maximizing positive ones. Thus far, his MLB K rate has been quite good, and his BB rate low but acceptable. His batted-ball mix to date, however, suggests that he would in a best-case scenario hit for a rather empty .260-.270 average at the major league level.

Curtis Granderson – The Mets probably should have seen this one coming. Below are Granderson’s plate appearance outcome frequency percentile ranks from 2008-12.

2008 67 76 71 75 35 25
2009 73 65 95 89 45 4
2010 81 68 63 96 49 9
2011 92 92 72 98 15 3
2012 95 85 85 97 60 2

2013 was more of the same, albeit in an injury-shortened sample. He strikes out a ton, hits a bunch of popups, never hits the ball on the ground, and generally doesn’t hit many line drives. He draws plenty of walks, and has always derived an exceedingly high percentage of his offensive value from home runs. As the years have passed, he has become more and more pull-oriented, and the odds of him hitting even a couple of homers to the opposite field over the course of a season have grown quite long. Only a very select group of players consistently hit the ball as high in the air on average as does Granderson. Then he moves from:

Yankee Stadium – 2013 RCF fly ball park factor = 202.9 (2nd) – 2013 RF fly ball park factor = 136.2 (5th) to
Citi Field – 2013 RCF fly ball park factor = 92.7 (17th) – 2013 RF fly ball park factor = 69.7 (27th)

These park factors are based on my calculations using granular batted-ball data. Citi Field helped break Ike Davis and it might do the same to Granderson. He does very little offensively at this stage besides hit fly balls to the pull side, not a good thing in his new home.

Some Other Guys to Watch – These players are also showing weakness in one or more fundamentals in the early going, but the situation has yet to reach the truly worrisome stage. Robinson Cano has very quietly developed a strong ground ball tendency in recent years (ground ball percentile ranks ranging from 67 to 78 in five of the last six years), but this year’s 59.7% grounder rate is even more extreme. For now, expect his line drive rate to positive regress toward the stratospheric region (88 to 92 percentile ranks in each of the last four seasons) that drives his offensive game. Prince Fielder‘s batted-ball authority levels dropped from the elite level in 2012 to merely a bit above average in 2013, and there hasn’t been a bounce-back yet this season. His K and BB rates are very strong, but his grounder rate is way up in 2014 – as with Butler, we may be witnessing a premature decline from a bad-body, bat-only player.

Brad Miller appears to be engulfed in the team-wide offensive malaise sweeping through the Mariner clubhouse. Player after player has abandoned the approach that allowed them to graduate from the Seattle farm system, becoming overly aggressive in a single-minded pursuit of pull-side power at the major league level. Miller’s walk rate has cratered, and he has become one of the most pull-oriented hitters in the game. His K and grounder rates are up, though he should see some positive regression in his line drive rate.

Ian Desmond’s 30/4 K/BB ratio is becoming a cause for concern. Though his poor line drive rate (9.6%) should positively regress before long, it should be noted that he did post low line drive percentile ranks ranging from 27 to 34 from 2010-12 before a surge to 86 in 2013. And finally, Starling Marte‘s poor K/BB ratio was the only blemish on a sterling first full major league season in 2013, but the K rate has shot even higher this season. His speed allows his ground ball tendency to play up, but he simply lacks the juice to be a productive player with a 32.3% K rate.

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What is the value in using Percentiles in things like these rates? Wouldn’t it be more valuable to state the relative trend in a given player, not to the rest of the league, especially since we’re focusing on slow starts in 2014? Not trying to argue, I just don’t understand. Thanks


Agreed. I liked the use of batted ball data, but the lack of results based stats for comparison was tough also. Good article, but the presentation was a little bit confusing.


League-wide stats have been very stable the past few years. I disagree. Showing percentiles puts the numbers in context. You’re seeing two data sets at once: the individual trend and the relationship to the rest of the league (which with large sample sizes would follow the normal curve very closely). It’s more information this way. Which is better.

Urban Shocker
Urban Shocker

More information is not by definition better, and in fact can lead to overconfidence in a model, given said model’s potential resistance to falsifiability. Here the data for 2014 is presented in a rate format, which is then contrasted with 2013 & earlier data. This comparison data is presented in a percentile rank format, which sows confusion and weakens the conclusions drawn by the author.

Put another way, we are awash in articles that make an introductory caveat about SSS, and then proceed to infer wildly from stats that we all know don’t stabilize for another month.


You’re right, fangraphs should just be on hiatus for the first two months of the season.


There should be no articles looking at IFFB% at this point of the season, or even at the end of single season for that matter. At this point, a single IFFB will massively change the player’s percentage. Why is author trying to draw conclusions from 1 or 2 balls in play?


The post may well use 2014 rate stats because, slim as the totals are, 2014 percentile stats would be simply absurd. But I concur with the overall criticism: Using individual rate stats as one sample and comparing them to league normalized percentile standings for prior seasons is methodologically faulty. This is true even if the conclusion is sound, which I think most of the player remarks actually are; I see nothing to disagree with in the 2014 player assesments.

Comparison of non-comparables gives a ‘statistical patina’ to snapshopts which looks ‘number like’ but isn’t really. In that sense, the approach is deceptive however unintentially so. I would FAR rather hear Tony’s opinons and insights without the ‘number like’ bunting which in itself simply can’t be relied on. The conclusions may be the same. Misuse of statistical data doesn’t improve them, however.


I just thought it was very confusing trying to decipher the percentiles numeral alongside the rate %, often in the same sentence.


percentiles more clearly shows performance deterioration relative to league wide performance. take strikeout rates for example. They’ve been increasing significantly across the league, but granderson’s increased at a much higher rate. Thus he’s gone from middle of the pack in ’08 to just among the worse in the league. percentiles allow you to see this without having to compare percent changes in strikeout rates for granderson vs. the league.