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Looking statistically at BABIP in Minors
Examining just how 'lucky' baseball's top players were in 2013
01/14/2014 11:32 AM ET
Byron Buxton helped create his own "luck" with his bat and speed.
Byron Buxton helped create his own "luck" with his bat and speed. (Mark LoMoglio/Tampa Yankees)

The top prospects in baseball are among the brightest young stars for a reason.

The best hitters are usually those with a combination of quick hands, keen eyes, plus speed and raw power. The elite pitchers tend to have advanced command, overpowering stuff and a good feel for one or more secondary offerings.

But as good as a player is in the box or on the mound, luck -- or at least perceived luck -- can go a long way to explaining past performances and predicting the future. One of those "lucky" elements is BABIP.

For the uninitiated, batting average on balls in play -- abbreviated as BABIP -- calculates the percentage of batted balls that remain in play and fall for hits. A BABIP of around .290 to .300 is generally considered to be average, with significantly higher or lower numbers suggesting unsustainable performances.

The equation is: BABIP = (H-HR)/(AB-K-HR+SF)

Home runs are not counted among a player's hits (because the ball leaves the field of play). Similarly, strikeouts are not included in the player's at-bat totals (because the ball wasn't put into play), but sacrifice flies are included in the calculation, even though it doesn't count as an official at-bat when calculating a player's batting average.

There are many factors that can influence BABIP, which is frequently displayed as a decimal in the same way as batting averages and slugging percentages.

A few to things to consider:

  • Speedy runners are more likely to have higher BABIPs because of their ability to beat out infield hits.
  • Fly balls are the least likely type of batted ball to fall for a hit (about 20 percent are hits in the Majors). Ground balls (about 25 percent) are more likely than fly balls, but less likely than line drives, which produce the highest hit rates (about 70 percent).
  • Luck, defense and classification all play a part in BABIP statistics. Consider a broken-bat blooper that fall for a hit or a pitcher snaring a sharp comebacker behind his back. Regarding classification, fielding percentages increase with level, but hit environments vary throughout the Minors, from the hitter-friendly California League to the pitcher-friendly Florida State League.
  • Using BABIP data to predict regression to the mean is more useful when evaluating pitchers than hitters. Most pitchers have very little control over what happens to a batted ball in play, whereas hitters can somewhat influence the outcome of whether their batted ball results in a hit because of their speed and produce more line drives. Consider that, in the Major Leagues, BABIP correlates just .20 for pitchers and .35 for hitters. In other words, on average a pitcher can "control" only 20 percent of what happens when a ball is put in play whereas a batter has about 35 percent "control."

In its most simplistic understanding, a pitcher allowing a high BABIP or, to a lesser extent, a hitter possessing a high BABIP will likely see a regression to average in future performance, while the reverse is also true. In both cases, a player's BABIP is generally expected to move toward the mean over time. There are exceptions (knuckleballers, for instance, tend to have lower BABIPs against), and not all players regress at the same rate.

MiLB.com examines which top prospects may see an increase or decrease in statistical performance in 2014 based on their BABIP numbers from last season. 

Hitters

Here are the top and bottom five BABIPs among Top 100 prospects with more than 350 Minor League at-bats in 2013.

Highest BABIP among Top 100 Prospects
NAME G BABIP AVG H HR SO BB SB
Byron Buxton 125 0.403 0.334 163 12 105 76 55
Delino DeShields 111 0.387 0.317 143 5 91 57 51
Chris Owings 125 0.386 0.330 180 12 99 22 20
Garin Cecchini 129 0.383 0.322 146 7 86 94 23
George Springer 135 0.377 0.303 149 37 161 83 45

Among those players with at least 350 at-bats, Buxton, MLB.com's top prospect, had the highest batting average. No. 84 prospect Owings ranked second, Cecchini was fourth and DeShields was fifth. It comes as little surprise they had some of the top BABIP numbers as well, all far above average.

Also note that all five players above are fleet of foot. Buxton and DeShields -- baseball's No. 74 prospect -- ranked 12th and 13th respectively in steals in the Minors in 2013, and each of the five swiped at least 20 bags. Also highlighting his speed, Buxton recorded 30 infield hits -- almost 20 percent of his total of 163.

Also note the high walk rates. No. 83 prospect Cecchini drew 94 walks, 10th in the Minors, and Springer, ranked 23rd, earned 83 free passes, placing him in a tie for 21st overall. Buxton (76) also ranked inside the top 50, suggesting there's also a correlation between a player's eye, their BABIP and their batting average. It makes sense that players who can best distinguish balls from strikes are also able to select the best pitches to drive, or at worst lay off enough balls to get to either get into a hitter's count or avoid making weak contact on balls out of the zone.

Lowest BABIP among Top 100 Prospects
NAME G BABIP AVG H HR SO BB SB
Courtney Hawkins 103 0.236 0.178 68 19 160 29 10
Mike Olt 107 0.262 0.201 75 15 132 55 0
Kaleb Cowart 132 0.280 0.221 110 6 124 38 14
Gary Sanchez 117 0.280 0.253 115 15 87 41 3
Mason Williams 117 0.284 0.245 117 4 79 40 15

At the other end of the spectrum, the above five hitters saw the lowest BABIPs among baseball's top hitting prospects.

When you look specifically at Hawkins, Olt and Cowart -- ranked 67th, 58th and 78th respectively -- a few things are noticeable, particularly average to below-average speed, low contact rate and lack of plate discipline.

While this trio of factors tends to negatively impact performance across the board, it becomes extra damaging when coupled with an "unlucky" low BABIP. Regression tends to suggest some rebound is imminent, but there's something to be said for players making their own luck, too.

Better pitch recognition and improved plate patience would lead to more balls in play. It means more balls could be squared up, resulting in more hard-hit balls and line drives, the type of contact most likely to fall for a hit.

On the other hand, for a player like the Yankees' Williams, there's long been question about his ability to make hard contact, and an inability to do so last season appears to have offset his plus speed in limiting his BABIP. Again, though, we should expect at least some bounceback from him and the others in the above list in 2014.

Pitchers 

And here are the unluckiest and luckiest pitchers, sorted by BABIP.

Highest BABIP among Top 100 Prospects
Name BABIP ERA IP H HR BB SO GO/AO AVG
Matt Barnes 0.361 4.13 113.1 115 11 48 142 1.12 0.261
Rafael De Paula 0.336 4.29 113.1 97 8 53 146 0.45 0.232
Lance McCullers 0.336 3.18 104.2 92 3 49 117 2.00 0.239
Jose Berrios 0.336 3.99 103.2 105 6 40 100 0.99 0.262
Yordano Ventura 0.330 3.14 134.2 119 7 53 155 0.92 0.238

On the surface, neither Matt Barnes or Rafael De Paula had great seasons. Barnes, the No. 2 right-handed pitching prospect in the Red Sox organization and No. 54 overall, went 6-10 over 25 starts and De Paula, the top Yankees hurler in the system and No. 99 overall, went 7-5 with a 4.29 ERA between Class A Charleston and Class A Advanced Tampa.

But there's reason to expect improvement in their traditional metrics -- like ERA -- for 2014.

Both pitchers had solid strikeout numbers -- more than 11 strikeouts per nine innings -- as well as strikeout-to-walk ratios of around 3:1. In addition, they sported the two highest BABIPs among MLB.com's Top 100 prospects with at least 100 innings.

To put it into perspective, if Barnes had an average BABIP of around .300 in 2013 -- instead of his actual .361 -- he would have surrendered 17 percent fewer hits. That, in turn, means opponents would have hit .229 against him instead of .261. With those numbers, it's not difficult to imagine a much lower ERA. Assuming Barnes starts 2014 back in the Eastern League, expect a significant jump in performance, especially since he will have a year of Double-A ball under his belt.

Meanwhile, for De Paula, the prognosis is possibly even simpler. The right-hander struggled when he earned a promotion from the South Atlantic League, where he was pitching in one of the least hitter-friendly ballparks on the circuit, to the Florida State League. The fact that Tampa's George M. Steinbrenner Field does not easily surrender home runs and that the league as a whole heavily favors hurlers was negated by the jump in competition, something that De Paula struggled with.

Opponents hit almost 100 points higher against him in Tampa. He gave up more home runs in fewer innings than in Charleston and his strikeouts dropped as walks increased. He proved at Class A that he can both command pitches and induce swings and misses. With more experience and a little more luck with the balls that are put in play (Tampa had the worst fielding percentage in the league), De Paula will have every chance to post better numbers in 2014.

Lowest BABIP among Top 100 Prospects
Name BABIP ERA IP H HR BB SO GO/AO AVG
Tyler Glasnow 0.218 2.18 111.1 54 9 61 164 1.16 0.142
Eddie Butler 0.228 1.80 149.2 96 9 52 143 2.14 0.180
Allen Webster 0.249 3.60 105 71 9 43 116 1.38 0.190
Henry Owens 0.253 2.67 135 84 9 68 169 0.89 0.177
Anthony Ranaudo 0.273 2.96 140 112 10 47 127 0.92 0.219

It's too simplistic to say the five prospects above were only successful because they got lucky in 2013.

Though fewer batted balls against them fell for hits than on average, there were other factors to consider in the quintet, who sported a combined 48-23.

The biggest thing may be the high strikeout totals. Owens, Ranaudo and Webster ranked first, third and fifth among Red Sox pitching prospects, Glasnow led the Pirates organization and Butler was second among Rockies farmhands. When you combine fewer balls being put in play with an already-low hit rate, a player's ERA is likely to drop.

Even though they combined to allow 46 homers, 11 more than the five pitching prospects with the highest BABIPs, the effects of the long balls were lessened since fewer runners were on base.

But there's also a cautionary tale to observe. As good as these players were, the chances of a repeat in 2014 are slim.

Firstly, good seasons are more likely to be rewarded with promotions to higher levels where hitters are better and more patient. Secondly, low hit rates are notoriously difficult to maintain, considering a pitcher has little effect on what happens to the balls in play once the pitch leaves his hand. Glasnow, for example, surrendered one-third fewer hits than he would have if his hit rate had been average.

Similarly, was Ranaudo (11-5, 2.96) that much better than his Sea Dogs teammate Barnes (6-10, 4.13) this year? They both threw 64 percent of pitches for strikes at the Double-A level and they had similar strikeout-to-walk ratios.

Pitching in front of the same defense in the same parks, the difference could have been as subtle as Ranaudo allowing a couple more fly balls (which are the least likely to fall for hits), allowing few hits with runners on base or pitching deeper into games. The first two factors would have a direct impact on the third.

There's a reason Glasnow (No. 97), Butler (88), Webster (46), Owens (52) and Ranaudo (80) are among the top 100 prospects in baseball. But it's important to place their seasons in context to get a complete picture of where they are not and where they could be at this time next year.

One more table to wrap up:

Comparison of High- and Low-BABIP Groups
Subset HR/9 BB/9 K/9 K/BB ERA
High BABIP Pitchers .55 3.84 10.43 2.72 3.73
Low BABIP Pitchers .65 3.80 10.10 2.65 2.60

Above is a look at the subsets of the high-BABIP pitchers and low-BABIP pitchers. You can see that their strikeout, walk and home run rates are nearly indistinguishable, but their composite ERAs are more than a run different. Expect those numbers to come together this year, and, in 2014, keep an eye on how a pitcher's BABIP is influencing his ERA and coloring your perception of his performance.

Ashley Marshall is a contributor to MiLB.com. Follow him on Twitter @AshMarshallMLB. This story was not subject to the approval of the National Association of Professional Baseball Leagues or its clubs.
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