GB% – This stands for ground ball percentage, which is the percentage of balls a player hits that end up as ground balls. The league average on grounders last year was just .239, which means that only about 24% of ground balls end up as hits. So, because of that, you would expect players who hit a lot of grounders to have a lower BABIP, right? This is not necessarily true, however, because most ground ball hitters end up being the speedsters that are more likely to beat out grounders than your average player. In general, you can expect players with a high GB% to have a slightly higher BABIP, but you definitely want to take a look at their speed before making that assumption.
Staying connected to the body's rotational energy starts when the hitter steps into the batter's box to prepare the launch position. To acquire a powerful launch position, the batter's upper body and shoulders must rotate to a fully loaded position. An inward turn of the upper torso and shoulders stretches the muscles of the upper body and pelvic region. Some refer to this as loading. With good transfer mechanics, the contraction of these muscles combined with the energy of hip rotation is converted into angular acceleration of the bat-head. The video below shows, and discusses, a powerful launch position.

To test this, I collected all batters in the Retrosheet database since 1975 who logged at least 300 plate appearances in two consecutive seasons. (Multiple batters, of course, could appear multiple times.) This covered 5,607 batters, from Barry Bonds's 2002 (.582 OBP, .587 gOBP) to Mario Mendoza's 1979 (.216 OBP, .219 gOBP). As before, I fit a linear relationship between each statistic in year 1 and the same statistic in year 2, and determined the respective correlation coefficients.
This is often overlooked but feeling torque in your front side is important. Work on this by trying to hit a ball as far as you can off a tee. Feel the hands back as your bottom half starts your swing. The torque created from separation is extremely important if you want to hit the ball further.  Click here for more tips on how to achieve good separation in your baseball swing.
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Watching a player in batting practice will tell you whether or not he can square up a baseball. If he is hitting one-hoppers through the infield that land in the dirt to line drives that are short-hopping the wall, he is squaring up the baseball. If he is consistently hitting balls that land within 45 feet of the plate or are high pop flies, his swing plane is not right and he will not be able to hit at a high level.
Prior to 2010 we only listed the top 100 and monitored those who made and slipped off the list. Here is that original fast fact preserved and now useless due to the list including 1000 names: Modern superstars are making the list as they meet the one-thousand minimum games played threshold: In 2001 Jeff Cirillo & Manny Ramirez met the requirements and joined the top one-hundred. In 2002 Cirillo slipped off the chart and Jason Giambi made it while Chipper Jones & Alex Rodriguez missed the cutoff by less than 2/1000 of a point. In 2003 Jason Giambi slipped off the chart, Chipper Jones just missed it once again (his career average is .30870), and Vladimir Guerrero vaulted onto the list at forty-first — higher than any other active player, that is until 2004 when Todd Helton launched into the top 20 all-time.

Overall, BABIP is a stat that is largely out of the batters control, which makes sense because as a hitter, once you hit the ball onto the field, you can’t affect what happens next. The league average BABIP is usually right around .300, meaning balls in play typically land for a hit about 30% of the time. So in theory, if a player has a BABIP of .350, you might say he had a “lucky” season, and you could expect him to regress the following season, right? On the surface it makes sense, but the whole point of this article is to look beyond just the surface stats, and that is exactly what we will do.

Now that we’ve taken a good look at the stats that compromise a typical slash line, we can move onto the next category which is measuring a player’s plate discipline. The first stats I wanted to touch on are fairly simple ones, yet quite important: K% and BB%. These are essentially the same thing as strikeouts and walks, but applied as a rate-based stat by dividing it by the player’s total number of plate appearances.

Batters actually hold a decent level of influence on their BABIP, which is something that not a lot of people realize. Because there are different types of hitters (mainly speed, power, and contact hitters), not everyone should be expected to have the same “30% outcome” for balls in play. The main source of this influence comes from what is known as a player’s “batted ball profile,” which consists of the following stats:
On base percentage (OBP) or on base average (OBA) is an important component in a sabermetrics styled view of offensive productivity, but it is by no means the ultimate statistic to measure a hitter’s value. Unlike AVG and SLG, OBP does take walks into account, but it gives the same weight to a home run as it does to a single or a walk. Obviously, those are events in a baseball game that don’t have the same value in terms of producing runs. Billy Beane was quoted once as saying that OBA is three times as important as SLG. Well, is it? Not from a sabermetrics view point. Sabermetrics isn’t based on money at all. Bill James and the folks that blazed the trail for the development of sabermetrics certainly know that a home run has more value than a walk. It just so happens that players that had an ability to get on base were not paid as well as some of those who racked up RBIs. Obviously, the players who do it all get paid the most.
Back in the day when fantasy baseball was in its infancy, the standard 5×5 categories many leagues still use today seemed like a good thing.  Well times they are a changing.  Stats have evolved over the years, especially with the introduction and advanced use of sabermetrics throughout our real and fake teams.  So if things have come this far, then why are we still using the same archaic scoring methods that were instituted by our founding fathers? 

For small numbers of at-bats, it is possible (though unlikely) for a player's on-base percentage to be lower than his batting average (H/AB). This happens when a player has almost no walks or times hit by pitch, with a higher number of sacrifice flies (e.g. if a player has 2 hits in 6 at-bats plus a sacrifice fly, his batting average would be .333, but his on-base percentage would be .286). The player who experienced this phenomenon with the most number of at-bats over a full season was Ernie Bowman. In 1963, with over 125 at-bats, Bowman had a batting average of .184 and an on-base percentage of .181.
IFFB% – This stands for infield fly ball percentage, which is the percentage of fly balls a player hits that end up as infield pop ups. Lazy flies to the infield are about as easy to field as they come, so they are considered essentially automatic outs. Because of that, it would be fair to say that a player who hits a lot of infield flies is not likely to have a very good BABIP. However, even the player with the worse IFFB% last year was at just 17.3%, so hitting a lot of automatic outs isn’t going to make a huge difference, but definitely a noticeable one. Batters who avoided these easy outs last year (better-than-league average IFFB%) had a better BABIP (.312) than their counterparts who did not (.298).
Hitting Mechanics and other factors.  When you hit, scouts will be looking at your looking at hand path and head movement.  A lot of head movement makes it difficult to see and hit the ball, showing poor hitting mechanics.  Jim also watches intelligence, decision-making at the plate, with 2 strikes, facing left handed pitchers, day time and night time games.
While watching a New York Mets game early this season, before one plate appearance the broadcast graphics displayed that catcher John Buck had a batting average (AVG) of .400 and an on-base percentage (OBP) of .396. Several games later I saw a similar phenomenon for Buck, whose OBP was again several points lower than his AVG. (In other words, the stats presented were very likely to be actual and not an on-screen typo.)
It is important to remember that there will almost certainly be some “bleeding” of the phases.  As much as a hitter might train, their will always be tiny little timing and mechanical mistakes leading to some of the “bleeding effect” of the phases.  The most important thing to remember as a hitter is really to be great at preparing to swing properly followed by being great into Phase 1.  If the the transition from your load into Phase 1 is executed at a high level, then Phase 2 and 3 will require very little attention.  Eliminate early mistakes and prepare to feel effortless power.
Now that we’ve covered slash lines, plate discipline, and batted ball data, that about does it for the hitting side of advanced baseball stats, but before I wrap up, I need to mention one important thing. All of the statistics that I used were from players who had a qualifying season (3.1 plate appearances per team game which is roughly 500 PA). The pre-mentioned stats are most effectively used when you have a good sample size of data to work with, and you should watch out for stats that are skewed by small sample sizes. Make sure that when you are evaluating a player’s skill set, they have accumulated enough plate appearances (usually you want to aim for a minimum of 100) to make the data you’re working with relevant.
the reason i think XBH is the perfect stat is for the same reason you dismissed it, because it does not consider HRs more important than doubles and triples… One problem with the traditional 5×5 is that we count HRs 3 times, Power is not the only important stat… and using XBH gives speed guys a little more value because now they can contribute well in the same amount of categories a power hitter can…
An example is the Internet Archive, which uses the term in ranking downloads. Its "batting average" indicates the correlation between views of a description page of a downloadable item, and the number of actual downloads of the item. This avoids the effect of popular downloads by volume swamping potentially more focused and useful downloads, producing an arguably more useful ranking.
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